eWaterCycle II

Overcoming the challenge of locality using a Community Multi-Model Environment

Overcoming the challenge of locality using a Community Multi-Model Environment

An accurate global hydrological model will enable us to predict droughts, floods, navigation hazards, and reservoir operations. Creation and dissemination of such information to the global community would have tremendous societal value. In addition, such a model will allow determination of anthropogenic and climate change impacts on the hydrological cycle. The eWaterCycle II project builds on results of the eWaterCycle project by taking on the scientific challenge of extreme spatial variability in hydrology.

From a hydrological point of view, every field, every street, every part of the world, is different. We understand quite well how water moves through plants and soils at small scales but the medium is never the same from one spot to the next. This is the curse of locality. It is difficult to capture such processes with a single global model. Instead, we introduce a community multi-model environment that allows rapid and easy combination of local hydrological models with global models, leading to a collaborative environment where anyone can easily contribute to the greater goal of a community built and shared global Hydrological model.

The eWaterCycle II project will build and maintain an e-Infrastructure that allows for quick and safe inclusion of sub-models and model concepts into global hydrological models, leading to a better understanding of the Hydrological cycle. The foreseen e-infrastructure will have a number of unique advantages, including an ability for knowledge gap discovery, machine-assisted model curation, and easily changeable model parts.

The eWaterCycle II project offers a set of community tools that can be of use to all scientists studying the hydrological cycle. Although used in this project in a hydrological setting, the underlying framework will be suitable outside of hydrology, wherever a collaborative environment is required. eScience aspects such as large scale data assimilation (DA) techniques, generic multi-model multi-scale environments, FAIR data as well as FAIR software, will all benefit from research done in this project. The largest non-technical challenge will be to build a user community. We will make use of the “challenge” model, a highly successful open science approach for gathering a community to work towards a common goal.

Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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Inside the filter bubble

A framework for deep semantic analysis of mobile news consumption traces

A framework for deep semantic analysis of mobile news consumption traces

Online and mobile news consumption leaves digital traces that are used to personalize news supply, possibly creating filter bubbles where people are exposed to a low diversity of issues and perspectives that match their preferences. Filter bubbles can be detrimental for the role of  journalism in democracy and are therefore subject to considerable debate among academics and policymakers alike.

The existence and impact of filter bubbles are difficult to study because of the need to gather the digital traces of individual news consumption; to automatically measure issues and perspectives in the consumed news content; and to combine and analyse these heterogeneous data streams.

We will develop a mobile app to trace individual news consumption and gather user data (WP1); create a custom NLP pipeline for automatically identifying a number of indicators of news diversity in the news content (WP2); integrate and analyze the resulting heterogeneous data sets (WP3); and use the resulting rich data set to determine the extent to which news recommender algorithms and selective exposure leads to a lower diversity of issues and perspectives in the filter bubbles formed by news supplied to and consumed by different groups of users (WP4).

This allows us to determine the impact of biased and homogenous news diets on political knowledge and attitudes. The software developed in this project will be open source and re-usable outside the scope of this project by scholars interested in mobile behavior and news production and consumption.

Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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SecConNet

Smart, secure container networks for trusted Big Data Sharing

In SecConNet we research novel container network architectures, which utilize programmable infrastructures and virtualisation technologies across multiple administrative domains whilst maintaining security and quality requirements of requesting parties for both private sector and scientific use-cases. For this, we exploit semantically annotated infrastructure information together with the information on the business and application logic and apply policy engines and encryption to enforce the intents of the data owners in the infrastructure and thus increasing trust.

Containers are lightweight alternatives to full-fledged virtual machines. Containers provide scientific, industrial and business applications with versatile computing environments suitable to handle Big Data applications. A container can operate as a secure, isolated and individual entity that on behalf of its owner manages and processes the data it is given.

Containers can exploit policy engines and encryption to protect algorithms and data. However, for multi-organisation (chain) applications groups of containers need access to the same data and/or need to exchange data among them. Technologies to connect containers together are developed with primary attention to their performance, but the greatest challenge is the creation of secure and reliable multi-site, multi-domain container networks.

The project will deliver multiple models of container infrastructures as archetypes for Big Data applications. SecConNet will show that containers can efficiently map to available clouds and data centers, and can be interconnected to deliver these different operational models; these in turn can support a plethora of Big Data applications in domains such as life sciences, health and industrial applications.

Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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FEDMix

Fusible Evolutionary Deep Neural Network Mixture Learning from Distributed Data for Robust Medical Image Analysis

Automated Medical Image Analysis (MIA) has the potential to truly innovate clinical practice by offering solutions to routine, yet key tasks, such as segmentation (i.e., delineating organs). Especially with recent advances in machine learning (ML), in particular in Deep Neural Networks (DNNs) that have led to an explosive growth of successful MIA studies reported in academic literature, the time appears right for such innovations to find widespread real-world uptake.

Yet, labor-intensive manual performance of these tasks is still often daily clinical practice. In this proposal, we integrate DNNs with other state-of-the-art computational intelligence techniques, in particular evolutionary algorithms (EAs), to overcome 2 key obstacles in moving toward widespread clinical uptake of computationally intelligent MIA techniques: 1) observer variation in the definition of a ground truth, and 2) image quality variation due to different acquisition protocols and scanners at different institutes.

In particular, we design and develop efficient-computing-compatible implementations of mixtures of DNNs, the results of which can be fused with results learned from other  data sets (i.e., from different institutes).

To maintain sufficient focus while doing so, we consider an elementary, but key MIA task: segmentation. Moreover, by means of an application in radiotherapy treatment planning, in collaboration with the Academic Medical Center in Amsterdam, we validate the newly developed technology on real-world patient data within the runtime of the proposed project.

Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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FAIR is as FAIR does

Integrating data publishing principles in scientific workflows

The FAIR guiding principles for data management and stewardship (FAIR = Findable, Accessible, Interoperable, Re-usable) have received significant attention, but little is known about how scientific protocols and workflows can be aligned with these principles.

Here, we propose to develop the FAIR Workbench that will enable researchers to explore, consume, and produce FAIR data in a reliable and efficient manner, to publish and reuse (computational) workflows, and to define and share scientific protocols as workflow templates. Such technology is urgently needed to address emerging concerns about the non-reproducibility of scientific research.

We focus our attention on different types of workflows, including computational drug repositioning to illustrate fully computational workflows and related systematic reviews to illustrate mixed (manual/computational) workflows. We explore the development of FAIR-powered workflows to overcome existing impediments to reproducible research, including poorly published data, incomplete workflow descriptions, limited ability to perform meta-analyses, and an overall lack of reproducibility.

We will demonstrate our technology in our use case of finding new drugs and targets for cardiovascular diseases, such as heart disease and stroke. As workflows lie at the heart of data science research, our work has broad applicability beyond the Life Science top sector.

Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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Scalable high-fidelity simulations of reacting multiphase flows at transcritical pressure

physics and beyond

Scalable high-fidelity simulations of reacting multiphase flows at transcritical pressure

Scalable high-fidelity simulations of reacting multiphase flows at transcritical pressure

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

We will perform unprecedented large-eddy simulations (LES) of high-pressure liquid-fuel injection and reacting multiphase flows in modern energy conversion systems, such as rocket engines, gas turbines and Diesel engines, to provide detailed insight into high-pressure injection phenomena and contribute to the solid physical understanding necessary to further improve the efficiency of these technical systems.

For this purpose, we recently developed a two-phase model based on cubic equations of state and vapor-liquid equilibrium calculations, which can represent supercritical states and multi-component subcritical two-phase states, and an efficient finite-rate chemistry model, which can accurately predict ignition and the transition between deflagration and detonation.

However, combining these readily available models efficiently in a single high-fidelity multi-physics simulation is challenging. With any classical domain decomposition, their uneven computational intensity severely limits the scalability of the simulation as described by Amdahl's and Gustafson's laws.

During this project, we will solve this scalability problem through a dynamic multi-level parallelization, which will be implemented in form of a generic shared library for scalable high-performance multi-physics simulations. The library will be integrated into our existing and next-generation flow solvers and is anticipated to have a major impact on other multi-physics applications that require massively parallel high-performance computing.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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Accurate and Efficient Computation of the Optical Properties of Nanostructures for Improved Photovol

physics and beyond

Accurate and Efficient Computation of the Optical Properties of Nanostructures for Improved Photovol

Accurate and Efficient Computation of the Optical Properties of Nanostructures for Improved Photovol

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

The key challenge we address in this project is to accurately and efficiently compute the effects of unavoidable fabrication disorder on functional 3D nanostructures that trap light for photovoltaic conversion.

Traditionally, optical measurements of real nanophotonic structures are compared to an idealized model. Unfortunately, however, this does not allow to assess the consequences of unavoidable fabrication imperfections, and hampers rational development of efficient solar cells.

Recently, we pioneered X-ray holotomography as a probe of complex 3D nanostructures with 20 nm spatial resolution. When combined with Maxwell computations this provides unprecedented opportunities to study real 3D nanofabricated structures for photovoltaics.

The giant tomography data set of voxels requires, however, important computational innovations: i) the use of polytopic meshes to allow significantly smaller meshes than dictated by the domain’s geometric complexity; ii) the development of discontinuous Galerkin discretizations for the Maxwell equations using polytopic elements; iii) the use of unit-cell Bloch-mode basis functions for robust numerical algorithms that greatly improve the computational efficiency of ultralarge superstructure computations.

Since the software development will be based on the hpGEM discontinuous Galerkin toolkit, our project has spin-off to other applications, including DGEarth for seismics and HamWave for nonlinear water waves.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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Parallel-in-time methods for the propagation of uncertainties in wind-farm simulations

physics and beyond

Parallel-in-time methods for the propagation of uncertainties in wind-farm simulations

Parallel-in-time methods for the propagation of uncertainties in wind-farm simulations

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

Large eddy simulations (LES) of turbulence resort to coarse-grained models of the small scales of motion for which numerical resolution is not available.

LES can be applied for the aerodynamic analysis of wind farms at sea. However, the model that describes the nonlinear unresolved-resolved interactions is a major source of uncertainty. Therefore, we aim to study the nonlinear propagation the uncertainties in LES of wind farms.

To start, a comparative study of Polynomial Chaos, Gaussian process and Karhunen-Loeve based surrogate models for uncertainty propagation (UP) is performed and the best method is tailored to turbulence. The number of cores needed for this UP is so large that a space-only parallelization does not suffice; hence parallel-in-time (PinT) algorithms are applied.

Basically, multiple time steps are introduced and the serial dependencies are shifted to the largest time step. Parareal is a prime example which has been applied with success to many problems. For turbulent flows, however, parareal suffers from convergence problems and artificial dissipation. Both problems are addressed by improving the coarse-time operator. The PinT-software is set up such that it can be used for Navier-Stokes solvers; the software may also be (re)used for the time integration of similar pde’s.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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eScience Technology to Boost Quantum Dot Energy Conversion

More efficient lighting and solar energy conversion devices

physics and beyond

eScience Technology to Boost Quantum Dot Energy Conversion

eScience Technology to Boost Quantum Dot Energy Conversion

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

More efficient lighting and solar energy conversion devices

Quantum Dots (QDs) are versatile nanoscale materials that are increasingly used to boost efficiency in lighting and solar energy conversion devices.

While QDs can be tailored to exhibit desirable opto-electronic properties, their synthesis still requires a lengthy trial-and-error procedure to find the right starting reagents (precursors) and ideal experimental conditions.

In this proposal, we aim to greatly speed up this process by developing a robust and reliable automated screening workflow in which quantum chemical software packages are combined with statistical data analysis tools. Unique and crucial in this approach is the ability to explicitly include the experimental conditions in all stages of the QD synthesis.

In this manner, we create reliable models for which we can design highly parallelized Python workflows to quickly filter out suitable precursors for the preparation of novel QDs.

The machine-learning libraries necessary for statistical analysis and pattern recognition will be deployed inside QMWorks, a Python package constructed to support massively parallel execution of quantum chemical modelling workflows. Using the multiscale modelling facilities in QMWorks, we will be able to avoid redundant calculations and achieve a prediction speed that allows for direct interaction with experimental colleagues that will ultimately test the candidate materials.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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A light in the dark

Quantum Monte Carlo meets solar energy conversion

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

Quantum Monte Carlo meets solar energy conversion

The in silico optimization of solar energy conversion devices in which light is used to separate charge and generate power requires advanced quantum mechanical approaches to describe the photon-harvesting component and the initial charge-propagation process in the excited state.

Computing excited states, however, is highly demanding for electronic structure methods, which often struggle to ensure accuracy or treat the large, relevant system sizes. To overcome these limitations, we work in the sophisticated framework of many-body quantum Monte Carlo (QMC) methods, we have been actively developing in recent years for the accurate treatment of excited states in complex systems.

Here, we propose to professionally structure and further accelerate our methodology for energy-related applications into a set of open and re-usable software tools addressing three key elements of QMC simulations: fast computation of observables, effective non-linear optimization schemes, and efficient graphics-processing-units kernels.

With these enhanced tools, we will in parallel proceed to establish a computational protocol to optimize the primary elements of a dye-sensitized solar cell and provide robust reference data for the characterization of one of the major limitations in efficiency, namely, the charge-recombination process at the interface between dye and semiconductor.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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Passing XSAMS

Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

Non-equilibrium plasma sources are promising devices for the transformation of carbon dioxide into methane and other value-added chemicals.

Numerical simulation is an indispensable tool for the design and optimization of source concepts, but further progress mandates a professionalization that requires a blend of mathematical, physical and E-Science techniques.

We propose new numerical schemes for the transport fluxes in plasmas with excessive numbers of chemical components, and to develop new tools for the introspection and “chemical reduction” of the complex chemical models for such plasmas.

A major contemporary issue is the lack of reproducibility of results from plasma simulations. This is addressed by the application of modern web-based methods for the dissemination of tools and underlying data sets.

The project will result in a vendor-neutral infra-structure that will be made available to workers in plasma, combustion and chemical reactor science.

An important aspect is the adoption and further development of the “XSAMS” XML/Schema file format for atomic data and its promotion in the low-temperature plasma physics community. In-house testing and application will focus on microwave plasma systems for the production of “Solar Fuels” that are currently under development at the DIFFER institute and at Eindhoven University of Technology.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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A phase field model to guide the development and design of next generation solid-state-batteries

Safer batteries with higher energy densities

physics and beyond

A phase field model to guide the development and design of next generation solid-state-batteries

A phase field model to guide the development and design of next generation solid-state-batteries

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

Safer batteries with higher energy densities

The major bottleneck towards large-scale electrical transport is the restricted energy density and safety issues of current Li-ion batteries. Solid-state-batteries are intrinsically more safe and promise higher energy densities.

However, their power densities are far below the demands. One of the key challenges is to understand this limitation, which is determined by the complex interplay of charge transport processes.

Current modelling approaches are not able to predict the properties of these next generation systems, which requires introduction of a physically realistic Gibbs Free Energy, the exact shape of which determines the locally large Li-ion concentrations and strong ion-vacancy interactions in solid-electrolytes.

The associated computational challenge is the very fine and inhomogeneous finite element grid, necessary to describe the atomic-scale processes a the interfaces in macroscopic complete batteries. Here we propose a fundamental approach by integrating detailed Free Energy functionals for the solid-electrolytes, determined by first principle methods, into current state-of-the-art Phase Field models.

The correct physical description on the atomic-scale will result in a realistic general description of the interfaces, that play a pivotal role in solid-state batteries. The proposed model will boost the understanding and guide the design of these important next generation battery systems.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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Integrated omics analysis for small molecule-mediated host-microbiome interactions

Advancing our understanding of molecular mechanisms of health and disease

life sciences and ehealth

Integrated omics analysis for small molecule-mediated host-microbiome interactions

Integrated omics analysis for small molecule-mediated host-microbiome interactions

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

Advancing our understanding of molecular mechanisms of health and disease

The microbes in our bodies are fundamental to our health. At the molecular level, many of their interactions with human tissues are mediated by microbial specialized metabolites.

While metabolomics provides a powerful technique to profile these, most microbial molecules have unknown structures; hence, over 95% of detected masses cannot be functionally interpreted or linked to their producers. This currently thwarts efforts to understand important diseased states of our microbiome.

Many innovative computational workflows have recently been designed to predict molecular (sub)structures from genomic or metabolomic data; however, these efforts have remained largely unconnected. Integrating these data will make it possible to complement partial information provided by each field to yield much better functional predictions.

Moreover, it will connect vital information from both data types: while metabolomics informs about in vivo relevance, genomics informs about biological origin. Here, we propose to design a novel algorithm to connect molecular substructures identified in tandem mass-spectrometric data to sets of genes within biosynthetic gene clusters (BGCs) detected in (meta)genomic data. Subsequently, we will integrate this algorithm with our previous methods for metabolome (spectral networking, substructure detection) and genome analysis (BGC identification and clustering) in one comprehensive eScience workflow.

Finally, we will demonstrate its potential by identifying molecules prominent during periods of relapse in a longitudinal study of inflammatory bowel disease (IBD) and connecting them to their producers. Ultimately, our workflow will illuminate the vast unknown metabolic space within the human microbial metabolome, and greatly advance our understanding of molecular mechanisms of health and disease.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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MULTIXMAS

Multiscale simulations of excitation dynamics in molecular materials for sustainable energy applications

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

Multiscale simulations of excitation dynamics in molecular materials for sustainable energy applications

Full project team: Alexey Lyulin,and Björn Baumeier.

Guiding design of molecular materials for sustainable energy applications hinges on the understanding and control of excitation dynamics in functional nanostructures. Performance in, e.g., organic photovoltaics, photocatalysis, or soft thermoelectrics, is determined by multiple electronic processes, which emerge from interaction between electronic structure and nano- and mesoscale morphology.

Resolving this intimate interplay is crucial but extremely difficult as it requires linking quantum and classical techniques in an accurate and predictive way. In MULTIXMAS, we will develop bottom-up simulations of charge/exciton dynamics in large-scale morphologies.

Hierarchical multiscale structure equilibration of nanomaterial will be combined with excited state electronic structure theory based on Many-Body Green’s Functions, parameter-free electron-dynamics models, and kinetic Monte Carlo. Essential method development is accompanied by the technological challenge of high-performance and high-throughput computing.

As a prototypical system, we study charge generation in low-cost organic photovoltaic cells (OPVCs) for which a breakthrough increase of power conversion efficiency (PCE) from currently ~11% to or above that of conventional silicon-based devices (20%) is required to play a significant role in meeting the growing demand for renewable energy.

Our tools will provide a general framework for multiscale simulations of excitation dynamics in complex molecular systems, with relevance beyond energy-related applications.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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Stochastic Multiscale Climate Models

sustainability and environment

Stochastic Multiscale Climate Models

Stochastic Multiscale Climate Models

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer

In climate models it will not be possible to capture all relevant processes through a higher resolution or better process description. Ocean models currently use already near eddy-resolving horizontal resolutions (e.g. 0.1°) but many important processes such as upper ocean turbulence and sub-mesoscale eddies, are not adequately captured at this resolution.

To overcome this problem one needs to exploit the property that high-frequency components in the flow get into statistical equilibrium much faster than low-frequency components and, moreover, are locally determined by low-frequency components. This can be accomplished by coupling an implicit low-resolution model to an explicit high-resolution ocean model. One runs the high-resolution model alternatingly with the low-resolution model, for a short and long time period, respectively.

In fact, we will run an instance of the high-resolution model for each grid cell of the low-resolution model, using initial and boundary values computed at low resolution. This leads to an embarrassingly parallelizable set of high-resolution models.

Hence, very suitable for Exascale architectures. For each low-resolution grid cell, the statistics (mean, variance) resulting from these computations will be used to define a stochastic term (state-dependent) in the low-resolution model that parametrizes the behavior of the high-resolution model.

This process is repeated until the model gets into statistical equilibrium. For the coupling of the models, we will extend the eScience tool OMUSE, developed by NLeSC in a recent project, to one which can deal with one low-resolution model that can interact with many high-resolution models.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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MAGIC

Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer

Metrics and Access to Global Indices for Climate Projections

Global Climate Models are a vital source of information on Climate Change. However, gaining insight from the vast amount of data available is problematic. Data is spread out across the world, and with the data sizes in the Petabyte range and increasing, downloading climate model data is quickly becoming infeasible, let alone doing analysis of this data.

Copernicus Climate Change Service

The Copernicus Climate Change Service is still in the development phase and will combine observations of the climate system with the latest science to develop authoritative, quality-assured information about the past, current and future states of the climate in Europe and worldwide. ECMWF operates the Copernicus Climate Change Service on behalf of the European Union and will bring together expertise from across Europe to deliver the service.

The MAGIC project

Within the Copernicus Climate Change Service, the MAGIC project is developing solutions that will help users assess Global Climate Models projections using well-established metrics and manipulation tools and receive outputs tailored to their needs. In particular, the project aims to provide products that address the needs of the coastal, water, insurance and energy sectors.

The system will allow users to access, visualize and manipulate the large data sets that are produced by climate models without having to download them to their own machine. It will combine software that have been developed by partners, either individually or within earlier European projects, into one single system. The software will contain modules to calculate standardized metrics and indices for each model, so that the models’ performance can be assessed quickly.

Users’ benefits are

The MAGIC project is funded by the Copernicus European Union Programme. The lead contractor is the Royal Netherlands Meteorological Institute (KNMI). The eScience Center is in change of the technical work done in the project.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

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eScience Research Engineer Faruk Diblen, MSc

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GlamMap

Visual Analytics for the World’s Library Data

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer

Visual Analytics for the World’s Library Data

Today’s libraries provide online access millions of bibliographic records. Librarians and re-searchers require tools that allow them to manage and understand these enormous data sets. Most libraries only offer textual interfaces for searching and browsing their holdings. The re-sulting lists are difficult to navigate and do not allow users to get a general overview. Further-more, data providers such as OCLC (Online Computer Library Center) are trying to enrich bib-liographic databases with semantically meaningful structures which are essentially lost when represented within a list-based interface.

Visualizations provide a means to overcome these difficulties. Graphical representations provide quick access to bibliographic data, facilitate the browsing and identification of relevant metadata, and provide a quick overview of the coverage of libraries. The fields of Information Visualization and Visual Analytics within Computer Science develop computer-supported, in-teractive, visual representations which allow users to extract meaning from large and hetero-geneous data sets. While such visual techniques have become common practice in the sciences, they are little employed by libraries, despite similar increases in available data.

eScience Research Engineers are collaborating with this project team, which aims to develop a cutting-edge visual analytics toolkit, to answer both the pressing needs of humanities researchers and concrete demands of the library industry. The tools will provide visual interfaces for:

The project team will accompany the toolkit development with extensive expert user testing, involving (e-)humanities researchers and the expert user group of OCLC.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

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eScience Research Engineer Faruk Diblen, MSc

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eScience Research Engineer Tom Klaver, MSc

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Genetics of sleep patterns

Detecting human sleep from wearable accelerometer data without the aid of sleep diaries

life sciences and ehealth

Genetics of sleep patterns

Genetics of sleep patterns

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer

Detecting human sleep from wearable accelerometer data without the aid of sleep diaries

The project aims to identify genetic variants associated with sleep patterns, and to perform Mendelian randomisation studies to identify the downstream causal consequences of disturbed sleep patterns on metabolic diseases such as obesity and type 2 diatbetes. UK Biobank offers a large and high quality dataset to perform above analyses. Over a hundred thousand individuals wore a wearable movement sensor (accelerometer) on their wrist for the duration of one-week (24/7). Previously, eScience Engineer Vincent van Hees developed and published software to analyse this kind of accelerometer data. This was successfully used in preliminary analyses of UK Biobank. The sleep detection functionality of his software is designed to combine sleep diary information with accelerometer information. However, in UKBiobank there is no sleep diary data. Vincent implemented a possible solution for this but did not publish an article on it. In the project we will evaluate the currently implemented algorithm to detect human sleep from wearable accelerometer data without the aid of sleep diaries. Next, we will attempt to develop a better method, e.g. with machine learning, and release as update to the existing open source software.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

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eScience Research Engineer Faruk Diblen, MSc

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eScience Research Engineer Tom Klaver, MSc

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eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

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3D Printing of human body parts

Deep learning algorithms for more accurate implants

life sciences and ehealth

3D Printing of human body parts

3D Printing of human body parts

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer

Deep learning algorithms for more accurate implants

This project focuses on challenges faced in medical 3D printing of human body parts. Medical 3D printing requires translating ‘human data’ into ‘virtual data’. This is error-prone and subsequently results in voids in the 3D surface model of the patient. Critical steps in this proces, even more than the printing process itself, are:

Each of these steps can introduce errors into the fabrication process. This can lead to misfitting 3D printed implants and life-threatening complications during and after surgery. The application of deep learning algorithms may lead to more accurate implants.

Patient image acquisition currently results in voxel-based data (~1GB) representing different tissue types hence grey scales. These grey scales (voxels) have to subsequently be translated into 3D surface models using segmentation and surface rendering algorithms. This process is very compute-intensive and to date requires a wide range of different algorithms and software packages:

The application of deep learning algorithms may lead to more accurate implants. The result of this research could open new avenues for individualized treatments all over the world and will allow surgeries to be performed more accurately, shorten the intervention period, minimize complications and reduce costs.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

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eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

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eScience Research Engineer Dr. Wouter Kouw

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Related projects

Bridging the gap

Digital Humanities and the Arabic-Islamic corpus

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer

Digital Humanities and the Arabic-Islamic corpus

Despite some pioneering efforts in recent times, the longue durée analysis of conceptual history in the Islamic world remains a largely unexplored field of research. Researchers of Islamic intellectual history still tend to study a certain canon of texts, made available by previous Western researchers of the Islamic world largely based on considerations of the relevance of these texts for Western theories, concepts and ideas. Indigenous conceptual developments and innovations are therefore insufficiently understood, particularly as concerns the transition from premodern to modern thought in Islam.

This project seeks to harness state-of-the art Digital Humanities approaches and technologies to make pioneering forays into the vast corpus of digitised Arabic texts that has become available in the last decade. This is done along the lines of four case studies, each of which examines a separate genre of Arabic and Islamic literary history (jurisprudence, inter-faith literature, early modern and modern journalism, and Arabic poetry).

This project seeks to develop a web-based application that will

The project will be inserted into two ongoing ERC projects on Islamic intellectual history housed at the Department of Philosophy and Religious Studies at Utrecht University, and collaborate closely with international initiatives in the field of Arabic Digital Humanities.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

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eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

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eScience Research Engineer Dafne van Kuppevelt, MSc

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eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

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Related projects

TICCLAT

Text-Induced Corpus Correction and Lexical Assessment Tool

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer

Text-Induced Corpus Correction and Lexical Assessment Tool

The Text-Induced Corpus Clean-up tool TICCL, integral part of the CLARIN infrastructure, is globally unique in utilizing the corpus-derived word form statistics to attempt to fully-automatically post-correct texts digitized by means of Optical Character Recognition.

The NWO 'Groot' project Nederlab will deliver by the end of 2017 a uniformly processed and linguistically enriched diachronic corpus of Dutch containing an estimated 5-6 billion word tokens. We aim to extend TICCL's correction capabilities with classification facilities based on specific data collected from the full Nederlab corpus: word statistics, document and time references and linguistic annotations, i.e. Part-of-Speech and Named-Entity labels. These data will complement a solid, renewed basis composed of the available validated lexicons and name lists for Dutch.

In this, TICCL as a post-correction tool will be transformed into TICCLAT, a lexical assessment tool capable of delivering not only correction candidates, but also e.g. more accurately dated diachronic Dutch word forms, more securely classified person and place names. To achieve this on scale, the TICCLAT project will seek a successful merger of TICCL's anagram hashing with bit-vectorization techniques. TICCLAT's capabilities will also be evaluated in comparison to human performance by an expert psycholinguist.

The data collected will be exportable for storage in a data repository, as RDF triples, for broad reuse. The project will greatly contribute to a more comprehensive overview of the lexicon of Dutch since its earliest days and of the person and place names that share its history. Its partners are the Dutch experts in Lexicology, Person Names and Toponyms.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

Profile page
eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

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Related projects

NEWSGAC

News Genres: Advancing Media History by Transparent Automatic Genre Classification

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer

News Genres: Advancing Media History by Transparent Automatic Genre Classification

This project studies how genres in newspapers and television news can be detected automatically using machine learning in a transparent manner. This will enable us to capture the often hypothesized but, due to the highly time consuming nature of manual content analysis, largely understudied shift from opinion-based to fact-centred reporting. Moreover, we will open the black box of machine learning by comparing, predicting and visualizing the effects of applying various algorithms on heterogeneous data with varying quality and genre features that shift over time. This will enable scholars to do large-scale analyses of historic texts and other media types as well as critically evaluate the methodological effects of various machine learning approaches.

This project brings together expertise of journalism history scholars (RUG), specialists in data modelling, integration and analysis (CWI), digital collection experts (KB & NISV) and e-science engineers (eScience Center). It will first use a big manually annotated dataset (VIDI-project PI) to develop a transparent and reproducible approach to train an automatic classifier. Building upon this, the project will generate three outcomes:

1. A study that revises our current understanding of the interrelated development of genre conventions in print and television journalism based upon large-scale automated content analysis via machine learning;
2. Metrics and guidelines for evaluating the bias and error of the different preprocessing and machine learning approaches and of-the-shelf software packages;
3. A dashboard that integrates, compares and visualises different algorithms and underlying machine learning approaches which can be integrated in the CLARIAH media suite.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

Profile page
eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

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Related projects

EviDENce

Ego Documents Events modelliNg - how individuals recall mass violence.

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer

Ego Documents Events modelliNg - how individuals recall mass violence.

Much of our historical knowledge is based on oral or written accounts of eyewitnesses, particularly in cases of war and mass violence, when regular ways of documentation and record keeping are often absent. Although oral history and the study of ego documents both value these individual perspectives on history and its meaning, these research fields tend to operate separately. However, the digital revolution has shaken up the balance between spoken and written text. The paradigm emerging in the application of search technology to digitised oral history is characterised by a post-documentary sensibility: away from text and sensitive to other dimensions of human expression than language. Nonetheless, ‘mining’ of oral history accounts remains valuable in humanities research, especially considering the re-use of digital interview collections throughout the humanities.

EviDENce explores new ways of analysing and contextualising historical sources by applying event modelling and semantic web technologies. Our project suggests a systematic and integral content analysis of ‘ego-sources’ by applying state-of-the-art entity and event modelling methods and tools, in order to explore the nature and value of ego-sources and to disclose existing collections. We focus on representations of mass-violence in two case studies to generate and explore different kinds of events: 1) a synchronic analysis of WW2 events, centered around the oral history collection ‘Getuigenverhalen’ [1] and using the WW2 thesaurus [2], and 2) a diachronic analysis of ego-documents (1573-2012) from Nederlab [3]. In both cases, we use content-related contextual sources from Nederlab [4].

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

Profile page
eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Martine de Vos

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page

Related projects

AutoGraph

Automated multi-scale Graph manipulation with topological and flow-based methods

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
Prof. dr. Hans van Lint
Delft University of Technology
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator

Automated multi-scale Graph manipulation with topological and flow-based methods

Graph theory is the bedrock for modern research into complex systems. Specifically, routable directed graphs are quintessential tools for modelling and analyzing a wide range of flow problems in transportation, logistics, and energy, to name a few.

Analysis of transport networks takes place on multiple (spatiotemporal) scales. One of the key challenges is maintaining a set of mutually consistent directed graphs that represent the same network with all relevant characteristics and components on different scales.

In this research, we will investigate and develop approaches to derive such multi-scale graph representations automatically from data using a combination of topology- and data-driven methods.

Topology-based methods use attributes and characteristics of the network (connectivity, edge weights and priorities), whereas data-driven methods involve characteristics (e.g. traffic flows, travel times) of the physical process using the network.

It is in the combination of these approaches that scientific contributions are needed and possible. The result will be an open-source suite of tools (prototypes, demos) and two (or more) paper(s) describing the methods and algorithms.

Image: ASEugenio (CC License)
https://www.flickr.com/photos/xoterik_images/14779...

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

Profile page
eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Martine de Vos

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page

Related projects

City Cloud

Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
Prof. dr. Hans van Lint
Delft University of Technology
Dr. Nirvana Meratnia
University of Twente
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Rena Bakhshi
eScience Coordinator
Dr. Hanno Spreeuw
eScience Research Engineer
Johan Hidding, MSc
eScience Research Engineer

From the Things to the Cloud and back

Internet of Things (IoT) is a paradigm shift, in which all inanimate and animate ‘things’, are connected and made intelligent while at the same time are embedded and part of the environment. IoT is an integrated technology composed of collaborative sensing, wireless (opportunistic) networking, pervasive computing, in-situ intelligence, sensor data analytics, and active interaction.

Although not an entirely new concept, it has recently gained much popularity especially because of its adoption in many domains, for example health, real-time monitoring and control, and logistics, and new prediction regarding an explosion in number of connected devices in coming years. Unlike their predecessor, i.e., wireless sensor network applications, IoT applications are not application specific, but domain specific and as such bring heterogeneity (in technology, use, requirements, etc), dynamicity, scale, autonomy, and adaptability challenges to a new dimension.

While currently there exist a number of solutions, architectures and platforms supporting co-creation of IoT eco-systems, the diversity and heterogeneity of technological solutions, application segments, requirements, and use cases make it difficult to identify which platform is the best suitable. The challenge is not only to select a platform that solves the interoperability and unification problem of existing IoT technologies and applications, but also the ones not yet foreseen.

This proposal aims to investigate and study the current IoT platforms, identify the required building blocks, design and develop the missing components, and show-case the final unified IoT platform and its potential for three different IoT application segments demonstrating different characteristics and properties.

Image: LindaInpijn (CC License)
https://commons.wikimedia.org/wiki/File:QubyDispla...

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

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eScience Research Engineer Tom Klaver, MSc

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eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

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eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

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eScience Research Engineer Dafne van Kuppevelt, MSc

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eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Martine de Vos

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eScience Research Engineer Dr. Wouter Kouw

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eScience Coordinator Dr. Rena Bakhshi

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eScience Coordinator Dr. Rena Bakhshi

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eScience Research Engineer Dr. Hanno Spreeuw

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eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

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Related projects

Data mining tools for abrupt climate change

Updating our knowledge on abrupt climate change

sustainability and environment

Data mining tools for abrupt climate change

Data mining tools for abrupt climate change

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
Prof. dr. Hans van Lint
Delft University of Technology
Dr. Nirvana Meratnia
University of Twente
Dr. Sebastian Bathiany
Wageningen University and Research Center
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Rena Bakhshi
eScience Coordinator
Dr. Hanno Spreeuw
eScience Research Engineer
Johan Hidding, MSc
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Johan Hidding, MSc
eScience Research Engineer

Updating our knowledge on abrupt climate change

Many recent studies have discussed whether future climate change will be punctuated by abrupt shifts, so-called tipping points. As it would be difficult for societies and ecosystems to cope with such events, it is important to assess the associated risk. However, the list of climate tipping points put forward in scientific studies mainly results from idealized models, qualitative arguments and visual inspection. We will explore the possibility of future abrupt climate change more systematically by using the vastly increasing amount of climate model data.

As a crucial first step toward this goal we will explore the potential of change-point detection and edge detection algorithms to detect and interpret abrupt changes in large model ensembles from existing projects. Moreover, we will scan these datasets for a change in climate variability in order to learn if these changes can predict if, where and why abrupt shifts will occur.

Our approach will update our knowledge on abrupt climate change and will allow a systematic assessment of the feasibility of data mining tools. We thereby set the scene for a larger project with new perturbed-physics ensembles that will allow us to quantify the risk of future abrupt climate change in complex models.

Image: Asian Development Bank
https://www.flickr.com/photos/asiandevelopmentbank...

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

Profile page
eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Martine de Vos

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Dr. Hanno Spreeuw

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page

Related projects

Automated Analysis of Online Behaviour on Social Media

Gaining insights in the use of Twitter by politicians and journalists

humanities and social sciences

Automated Analysis of Online Behaviour on Social Media

Automated Analysis of Online Behaviour on Social Media

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
Prof. dr. Hans van Lint
Delft University of Technology
Dr. Nirvana Meratnia
University of Twente
Dr. Sebastian Bathiany
Wageningen University and Research Center
Prof. Dr. Marcel J. Broersma
University of Groningen
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Rena Bakhshi
eScience Coordinator
Dr. Hanno Spreeuw
eScience Research Engineer
Johan Hidding, MSc
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Johan Hidding, MSc
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer

Gaining insights in the use of Twitter by politicians and journalists

This project applies machine learning to study a) discursive practices of politicians and journalists on Twitter, and b) to what extent institutional differences between agents still matter, or even exist, now they have similar publishing opportunities on social media. While automated analysis of the content of tweets is intensively studied, the project’s focus on behaviour is innovative. It aims to develop a tool for large-scale automated content analysis of latent categories of behavior that should be scalable in terms of big data sets and various social media platforms.

The project builds upon previous work by the research team in which manual content analysis was applied to study discursive practices of politicians and journalists. A detailed coding scheme was designed to code latent categories of online behaviour (or: discursive practices) such as broadcasting, promoting, criticizing, branding, requesting input etc. These annotated data sets will be used to train the computer.

Our work suggests that although journalists and politicians have different roles and goals, their behaviour on social media is surprisingly similar. This hypothesized redistribution of power in the so-called “triangle of political communication” calls for a revision of classic theoretical insights that are key to both political communication and journalism studies.

Image: European Parliament
https://www.flickr.com/photos/european_parliament/...

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

Profile page
eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Martine de Vos

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Dr. Hanno Spreeuw

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page

Related projects

A methodology and ecosystem for many-core programming

Boosting the performance of current and future programs

escience methodology

A methodology and ecosystem for many-core programming

A methodology and ecosystem for many-core programming

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
Prof. dr. Hans van Lint
Delft University of Technology
Dr. Nirvana Meratnia
University of Twente
Dr. Sebastian Bathiany
Wageningen University and Research Center
Prof. Dr. Marcel J. Broersma
University of Groningen
Prof. Henri Bal
VU University Amsterdam
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Rena Bakhshi
eScience Coordinator
Dr. Hanno Spreeuw
eScience Research Engineer
Johan Hidding, MSc
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Johan Hidding, MSc
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Alessio Sclocco
eScience Research Engineer
Dr. Atze van der Ploeg
eScience Research Engineer

Boosting the performance of current and future programs

Computers are going through a radical redesign process, leading to novel architectures with large numbers of small cores. Examples of such "many-cores" are Graphics Processing Units and the Intel Xeon Phi, which are used by about 65% of the top 50 fastest supercomputers. Many-cores can give spectacular performance results, but their programming model is totally different from traditional CPUs. It currently takes an unacceptable amount of time for application programmers to obtain sufficient performance on these devices. The key problem is the lack of methodology to easily develop efficient many-core kernels.

We will therefore develop a programming methodology and compiler ecosystem that guide application developers to effectively write efficient scientific programs for many-cores, starting with a methodology and compiler that we have developed recently. We will apply this methodology to two highly diverse applications for which performance currently is key: Bioinformatics and Natural Language Processing (NLP).

We will extend our compiler ecosystem to address the applications' requirements in three directions: kernel fusion, distributed execution, and generation of human-readable target code. The project should provide applications and eScientists with a sound methodology and the relevant understanding to enable practical use of these game-changing many-cores, boosting the performance of current and future programs.

Image by: Robert Howie

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

Profile page
eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Martine de Vos

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Dr. Hanno Spreeuw

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Research Engineer Dr. Alessio Sclocco

Profile page
eScience Research Engineer Dr. Atze van der Ploeg

Profile page

Related projects

DeepRank

Scoring 3D protein-protein interaction models using deep learning

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
Prof. dr. Hans van Lint
Delft University of Technology
Dr. Nirvana Meratnia
University of Twente
Dr. Sebastian Bathiany
Wageningen University and Research Center
Prof. Dr. Marcel J. Broersma
University of Groningen
Prof. Henri Bal
VU University Amsterdam
Prof. Dr. Alexandre M.J.J. Bonvin
Utrecht University
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Rena Bakhshi
eScience Coordinator
Dr. Hanno Spreeuw
eScience Research Engineer
Johan Hidding, MSc
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Johan Hidding, MSc
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Alessio Sclocco
eScience Research Engineer
Dr. Atze van der Ploeg
eScience Research Engineer
Dr. Lars Ridder
eScience Coordinator
Dr. Elena Ranguelova
eScience Coordinator
Dr. Nicolas Renaud
eScience Coordinator
Dr. Sonja Georgievska
eScience Research Engineer

Scoring 3D protein-protein interaction models using deep learning

Interactions between biomolecules control all cellular processes. Understanding those interactions requires adding a three dimensional structural dimension. Next to experimental structural biology techniques, this can be done by docking, a complementary and high-throughput computational method allowing to model complexes from their known components.

A challenge in docking is scoring – the identification of correct (near-native) models from a large pool of docked models – due to our still limited knowledge of interaction rules. We will tackle this challenge by training deep networks (dNNs) to learn complex interaction patterns from the huge amount of experimental data in the Protein Data Bank (a valuable source of information not yet fully exploited). Our innovative strategy is to treat this problem as a 3D image classification problem: The interfaces of docked models will be represented as 3D images and dNNs will be trained to classify whether they are near-native or not. Unlike other machine learning techniques, dNNs are now able to learn from millions of data without reaching a performance plateau quickly, which is computationally tractable by harvesting GPU and Hadoop technologies.

The resulting scoring function, DeepRank, will markedly enhance our capability to reliably model biomolecular complexes, assisting the scientific community to gain insights into macromolecular aspects of life. It will be implemented in our HADDOCK modelling platform and freely distributed through GitHub and eStep repositories, ensuring a wide dissemination. The impact will be broad since 3D image-based dNNs have applications in many other domains, such as medical diagnoses (MRI), cryo-electron microscopy and computer vision.

Co-applicant: Dr. Li Xue (Utrecht University)

Image by: NIH Image Gallery

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

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eScience Research Engineer Faruk Diblen, MSc

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eScience Research Engineer Tom Klaver, MSc

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eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

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eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

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eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Martine de Vos

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Coordinator Dr. Rena Bakhshi

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eScience Research Engineer Dr. Hanno Spreeuw

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eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Research Engineer Dr. Alessio Sclocco

Profile page
eScience Research Engineer Dr. Atze van der Ploeg

Profile page
eScience Coordinator Dr. Lars Ridder

Lars’ research interests cover (bio)chemical informatics and simulations. He is responsible as engineer and project coordinator for multiple projects in the life-sciences and chemistry domains.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

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eScience Research Engineer Dr. Sonja Georgievska

Sonja joined NLeSC in May 2015. She is an eScience Research Engineer on the project Massive Biological Data Clustering, Reporting and Visualization Tools.

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Related projects

IMPACT

Software Analytics for the monitoring and assessment of the global impact of eScience Software on eStep

Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
Prof. dr. Hans van Lint
Delft University of Technology
Dr. Nirvana Meratnia
University of Twente
Dr. Sebastian Bathiany
Wageningen University and Research Center
Prof. Dr. Marcel J. Broersma
University of Groningen
Prof. Henri Bal
VU University Amsterdam
Prof. Dr. Alexandre M.J.J. Bonvin
Utrecht University
Prof. Dr. Jurgen Vinju
CWI
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Rena Bakhshi
eScience Coordinator
Dr. Hanno Spreeuw
eScience Research Engineer
Johan Hidding, MSc
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Johan Hidding, MSc
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Alessio Sclocco
eScience Research Engineer
Dr. Atze van der Ploeg
eScience Research Engineer
Dr. Lars Ridder
eScience Coordinator
Dr. Elena Ranguelova
eScience Coordinator
Dr. Nicolas Renaud
eScience Coordinator
Dr. Sonja Georgievska
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics

Software Analytics for the monitoring and assessment of the global impact of eScience Software on eStep

Next to research papers, software is rapidly becoming one of the two prime outputs of scientific advancement in practically every field of research. While research papers are passive, research software is active: reusable, reproducible and transferable. The demand on the valuable software products, services and know-how of the eScience center is evidence of this development.

Academic software producers like the NLeSC, but in the broader sense any academic group that produces software, need to make their performance indicators observable: the impact of the developed software should be measured and reported. This is essential to get recognition and credit for the academic contributions in software, as well as to securing continued financial support for the future. Measured impact is also key intelligence for strategic decision-making on the maintenance of eScience software (as >50% of the cost of software is in maintenance).

Software Analytics research was pioneered by CWI SWAT and its partners in the last decade; it is the application of data-analytics to source code versions, installation, reuse, issue tracking, online discussion, etc. to turn this data into actionable insights. We have the goal to transfer this software analytics tooling and knowledge to eScience center: to set up infrastructure for monitoring and assessing the impact of their and their partner’s software. This infrastructure works directly with eStep to support the upcoming scientific evaluation of the center. Moreover, measuring software impact will be an incentive for partners to join eStep (in addition to increased visibility).

Image: Map of scientific collaboration between researchers by Olivier H. Beauchesne

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

Profile page
eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Martine de Vos

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Dr. Hanno Spreeuw

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Research Engineer Dr. Alessio Sclocco

Profile page
eScience Research Engineer Dr. Atze van der Ploeg

Profile page
eScience Coordinator Dr. Lars Ridder

Lars’ research interests cover (bio)chemical informatics and simulations. He is responsible as engineer and project coordinator for multiple projects in the life-sciences and chemistry domains.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Sonja Georgievska

Sonja joined NLeSC in May 2015. She is an eScience Research Engineer on the project Massive Biological Data Clustering, Reporting and Visualization Tools.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page

Related projects

High spatial resolution phenological modelling at continental scales

Understanding phenological variability

escience methodology

High spatial resolution phenological modelling at continental scales

High spatial resolution phenological modelling at continental scales

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
Prof. dr. Hans van Lint
Delft University of Technology
Dr. Nirvana Meratnia
University of Twente
Dr. Sebastian Bathiany
Wageningen University and Research Center
Prof. Dr. Marcel J. Broersma
University of Groningen
Prof. Henri Bal
VU University Amsterdam
Prof. Dr. Alexandre M.J.J. Bonvin
Utrecht University
Prof. Dr. Jurgen Vinju
CWI
Dr. Raul Zurita Milla
University of Twente
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Rena Bakhshi
eScience Coordinator
Dr. Hanno Spreeuw
eScience Research Engineer
Johan Hidding, MSc
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Johan Hidding, MSc
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Alessio Sclocco
eScience Research Engineer
Dr. Atze van der Ploeg
eScience Research Engineer
Dr. Lars Ridder
eScience Coordinator
Dr. Elena Ranguelova
eScience Coordinator
Dr. Nicolas Renaud
eScience Coordinator
Dr. Sonja Georgievska
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Willem van Hage
Technical Lead Analytics
Dr. Romulo Gonçalves
Technical Lead Data Management

Understanding phenological variability

Phenology studies the timing of recurring plant and animal biological phases, their causes, and their interrelations. This seasonal timing varies from year to year and from place to place because it is strongly influenced by weather and climatic variability.

Understanding phenological variability is critical to quantify the impact of climate change on the global biogeochemical cycles (e.g. changes in the carbon and water cycles) as well as to manage natural resources (e.g. timing of animal migration), food production (e.g. timing of agricultural activities), public health (e.g. timing of hay fever), and even for tourism (e.g. timing of excursions).

A major obstacle in phenological modeling is the computational intensity and the extreme data size when working at continental scale and with high spatial resolution grids of explanatory variables (e.g. weather and remotely sensed data). We believe that moving our phenological modelling workflows to a modern big-data platform such as Spark will allows us to more easily experiment with novel analytical methods to generate phenological metrics at high spatial resolution (1 km) and to identify phenoregions (i.e. regions with similar phenology) by clustering time series of phenological metrics.

Image by: Chris Devers

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

Profile page
eScience Research Engineer Bouwe Andela, MSc

Profile page
eScience Research Engineer Faruk Diblen, MSc

Profile page
eScience Research Engineer Tom Klaver, MSc

Profile page
eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dafne van Kuppevelt, MSc

Profile page
eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Martine de Vos

Profile page
eScience Research Engineer Dr. Wouter Kouw

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Dr. Hanno Spreeuw

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Rena Bakhshi

Profile page
eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

Profile page
eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

Profile page
eScience Research Engineer Dr. Erik Tjong Kim Sang

Profile page
eScience Research Engineer Dr. Alessio Sclocco

Profile page
eScience Research Engineer Dr. Atze van der Ploeg

Profile page
eScience Coordinator Dr. Lars Ridder

Lars’ research interests cover (bio)chemical informatics and simulations. He is responsible as engineer and project coordinator for multiple projects in the life-sciences and chemistry domains.

Profile page
eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

Profile page
eScience Research Engineer Dr. Sonja Georgievska

Sonja joined NLeSC in May 2015. She is an eScience Research Engineer on the project Massive Biological Data Clustering, Reporting and Visualization Tools.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

Profile page
Technical Lead Data Management Dr. Romulo Gonçalves

Romulo works on the strategic collaboration between NLeSC and CWI Database group to research, design and implement a data management layer for Big Data problems.

Profile page

Related projects

Googling the cancer genome

Identification and prioritization of cancer-causing structural variations in patient-derived whole genome sequencing data

life sciences and ehealth

Googling the cancer genome

Googling the cancer genome

Dr. Paola Grosso
University of Amsterdam
Dr. Peter Bosman
CWI
Dr. Michel Dumontier
Maastricht University
Dr. Stefan Hickel
Delft University of Technology
Prof. Dr. Jaap van der Vegt
University of Twente
Prof. Dr. Roel Verstappen
University of Groningen
Dr. Ivan Infante
VU University Amsterdam
Prof. Dr. Claudia Filippi
University of Twente - MESA+ Research Institute for Nanotechnology
Dr. Jan van Dijk
TU Eindhoven
Dr. Marnix Wagemaker
Delft University of Technology
Prof. Dr. Dick de Ridder
Wageningen University and Research Center
Dr. Alexey Lyulin
TU Eindhoven
Dr. Fred Wubs
University of Groningen
Wim Som de Cerff
KNMI
Prof. Bettina Speckmann
TU Eindhoven
Dr. Micheal Weedon
University of Exeter
Maureen van Eijnatten, MSc
VU University Medical Center
Prof. dr. Christian Lange
Utrecht University
Dr. Martin Reynaert
Tilburg University
Prof. Dr. Marcel J. Broersma
University of Groningen
Dr. Susan Hogervorst
Open University
Prof. dr. Hans van Lint
Delft University of Technology
Dr. Nirvana Meratnia
University of Twente
Dr. Sebastian Bathiany
Wageningen University and Research Center
Prof. Dr. Marcel J. Broersma
University of Groningen
Prof. Henri Bal
VU University Amsterdam
Prof. Dr. Alexandre M.J.J. Bonvin
Utrecht University
Prof. Dr. Jurgen Vinju
CWI
Dr. Raul Zurita Milla
University of Twente
Dr. Jeroen de Ridder
University Medical Center Utrecht
eScience Center Team
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Valentina Maccatrozzo, MSc
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Christiaan Meijer, MSc
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Niels Drost
eScience Research Engineer
Bouwe Andela, MSc
eScience Research Engineer
Faruk Diblen, MSc
eScience Research Engineer
Tom Klaver, MSc
eScience Research Engineer
Dr. Vincent van Hees
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Wouter Kouw
eScience Research Engineer
Dr. Elena Ranguelova
eScience Coordinator
Dafne van Kuppevelt, MSc
eScience Research Engineer
Dr. Janneke van der Zwaan
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Patrick Bos
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Martine de Vos
eScience Research Engineer
Dr. Wouter Kouw
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Rena Bakhshi
eScience Coordinator
Dr. Hanno Spreeuw
eScience Research Engineer
Johan Hidding, MSc
eScience Research Engineer
Dr. Rena Bakhshi
eScience Coordinator
Johan Hidding, MSc
eScience Research Engineer
Dr. Jisk Attema
eScience Coordinator
Dr. Erik Tjong Kim Sang
eScience Research Engineer
Dr. Adriënne Mendrik
eScience Coordinator
Dr. Alessio Sclocco
eScience Research Engineer
Dr. Atze van der Ploeg
eScience Research Engineer
Dr. Lars Ridder
eScience Coordinator
Dr. Elena Ranguelova
eScience Coordinator
Dr. Nicolas Renaud
eScience Coordinator
Dr. Sonja Georgievska
eScience Research Engineer
Dr. Willem van Hage
Technical Lead Analytics
Dr. Willem van Hage
Technical Lead Analytics
Dr. Romulo Gonçalves
Technical Lead Data Management
Dr. Arnold Kuzniar
eScience Research Engineer
Dr. Sonja Georgievska
eScience Research Engineer

Identification and prioritization of cancer-causing structural variations in patient-derived whole genome sequencing data

Cancer affects millions of people worldwide. With the advent of novel DNA sequencing technologies, genome sequencing has now started to become part of a routine workflow for cancer diagnostics and potentially enables fine-tuned treatment strategies tailored towards individual cancer patients. In spite of the massive genomic data production, systematic and comprehensive analysis of these data, in particular regarding the detection and interpretation of structural variation, are lagging behind due to computational and algorithmic limitations.

In this project, we will create novel analytical and computational frameworks that lead to fast, cost-efficient and comprehensive detection and annotation of structural variations in cancer genomes. We particularly focus on previously neglected variations occurring in unexplored regions of the cancer genome. Our methods will serve as an important component in future genome-first-based clinical-decision making for cancer patients and is essential to drive discovery of novel cancer genes and mechanism from modern-day whole genome sequencing data.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Research Engineer Christiaan Meijer, MSc

Christiaan\'s specialties include machine learning, pattern recognition, computer vision and reinforcement learning.

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Technical Lead Analytics Dr. Willem van Hage

Willem´s main research topics in the past 10 years are semantics, augmented sense making, visual analytics, information integration, and text mining.

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eScience Research Engineer Dr. Niels Drost

Niels works on the water management project as well as general eScience infrastructure. Niels is also part-time guest researcher at the Leiden Observatory, where he applies distributed computing techniques to the AMUSE computational astronomy simulation framework.

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eScience Research Engineer Bouwe Andela, MSc

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eScience Research Engineer Faruk Diblen, MSc

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eScience Research Engineer Tom Klaver, MSc

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eScience Research Engineer Dr. Vincent van Hees

Vincent is specialized in analytical methods for life science projects.

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eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

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eScience Research Engineer Dr. Wouter Kouw

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eScience Coordinator Dr. Elena Ranguelova

Elena is specialized in image processing, and works as an eScience Engineer on medical imaging and other multidisciplinary projects.

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eScience Research Engineer Dafne van Kuppevelt, MSc

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eScience Research Engineer Dr. Janneke van der Zwaan

Janneke works as an eScience Research Engineer on the Texcavator and From Sentiment Mining to Mining Embodied Emotions projects.

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eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

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eScience Research Engineer Dr. Patrick Bos

Patrick works as eScience Research Engineer on Digital Humanities and Physics projects, specializing in data mining and high performance optimization.

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eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

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eScience Research Engineer Dr. Erik Tjong Kim Sang

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eScience Coordinator Dr. Jisk Attema

Jisk works as an eScience engineer on the Summer in the City project and is eScience coordinator for the humanities projects.

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