eScience Center awards 13 projects from 2023 open calls

14 Dec 2023 - 2 min

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The Netherlands eScience Center is pleased to announce 13 winning project proposals. Each year, the eScience Center publishes open calls for researchers in any scientific discipline. These winning projects were awarded from the Open eScience Call (OEC) and Software Sustainability Call in 2023. The projects will officially kick-off in 2024.

The Open eScience Call 2023 aims to collaborate with Netherlands-based researchers on projects that could benefit from the development and application of research software. The Software Sustainability Call aims to work with researchers who require expertise to apply quality standards to ensure the continuity and advancement of their research in the long term.

Each research team will be partnered up with eScience Center research software engineers (RSEs) who will advise and (co-)develop sustainable research software, lead and/or contribute to workshops, collaborate on research papers and much more. Learn more about how we collaborate on research projects here.

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The eScience Center helps researchers develop the open-source software they need. For an overview of the full breadth of our research software across all disciplines, check out our Research Software Directory.

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Learn more about the awarded projects

Open eScience Call (OEC) 2023 winners

OSLA: Open-source laboratory automation

Lead applicant: Y. Mulla, Vrije Universiteit Amsterdam

Discipline area: Life Sciences

Robots have transformed pharmaceutical research, but most basic science labs can’t afford commercial systems. To address this, we aim to create open-source lab automation software, enabling affordable access and facilitating research, for instance into screening bacteria-killing viruses to combat antibiotic resistance.

AGILE: Accelerating astrophysical fluid dynamics with GPUs

Lead applicant: Dr. O.J.G. Porth, Universiteit van Amsterdam 

Discipline area: Physical Sciences and Engineering  

To enhance efficiency and allow researchers to address complex problems in solar and high-energy astrophysics, we intend to upgrade the open-source AMRVAC framework with high-performance computing (HPC) advancements, particularly accelerators like GPUs. This project, supported by a robust international community, aims to meet the growing demand for higher resolution and larger scale 3D simulations in astrophysical research.

TMSR: Text mining systematic reviews

Lead applicant: Dr. C.J. van Lissa, Tilburg University 

Discipline area: Social Sciences and Humanities  

This project will address the challenge in systematic reviews to summarize scientific literature by developing COSMAS, a cloud-hosted service that provides researchers legal access to full-text scientific publications. Our project will also include a pre-processing pipeline for homogenizing text and metadata, connecting to Tilburg University’s Text Mining Systematic Reviews (TMSR) methods to extract causal diagrams for generating testable hypotheses in research.

PROTEUS: An adaptive numerical framework to simulate lava exoplanets

Lead applicant: Dr. T. Lichtenberg, University of Groningen      

Discipline area: Physical Science and Engineering

Utilizing the James Webb Space Telescope, this project aims to characterize hot rocky extrasolar planets, which resemble conditions of early Earth, to better understand the geologic factors that contributed to life’s origin. To enhance this effort, the research team proposes to modularize the PROTEUS framework for advanced simulation, fostering code sustainability and interoperability, and enabling breakthroughs in interpreting exoplanet observations.

QANS: Questionnaire and nomination software

Lead applicant: Dr. J.L. Pouwels, Radboud Universiteit 

Discipline area: Social Sciences and Humanities  

In the social sciences and educational practice, peer nominations are a common and reliable methodology to assess behaviors, relationships, status and social networks in groups (e.g., classrooms). While peer nomination methods have become completely computerized, existing software programs are expensive and not sufficient. Therefore, many researchers have to hire RSEs to program their assessment and pre- and post-process the data. In this project we: (a) improve QANS’ workflow technologies and software practices, (b) make QANS sustainable and user friendly, and (c) add functionality for automatic data visualizations and classroom reports.


Lead applicant: Dr. J. Waagen, Universiteit van Amsterdam 

Discipline area: Social Sciences and Humanities  

DroneML addresses the challenge of processing large and complex archaeological datasets generated by state-of-the-art sensor-equipped drones. By developing software for the rapid screening of multiple feature types, the research team aims to significantly enhance the efficiency of archaeologists and expand research possibilities in heritage and remote sensing across various disciplines. 

MINE-DD: Mining the past to protect the future

Lead applicant: Dr. V.C. Harris MD PhD, Amsterdam UMC  

Discipline area: Life Sciences

Climate change poses a threat to both human and planetary health, particularly impacting children as diarrheal diseases remain a significant global threat. To anticipate future risks and inform policymakers, we are proposing to employ artificial intelligence to analyze existing literature and predict how climate change may affect the burden of diarrheal diseases, aiding in community preparation and decision-making. 

CRiSp: City River Spaces, a tool for automated and scalable delineation of urban river spaces with spatial-temporal big data

Lead applicant: Dr. C. Forgaci, Technische Universiteit Delft 

Discipline area: Social Sciences and Humanities

The intersection of accelerated urbanization, climate change and the need for environmental resilience highlights the significance of urban river spaces in global urban transformations. To address the complexities of riverside urban areas, we propose developing the City River Spaces (CRiSp) open-source software, fostering interdisciplinary research and enabling comprehensive spatial analyses for sustainable urban river space transformations.

Urban-M4: Urban morphology for microscale meteorological modelling

Lead applicant: Dr. ir. G.J. Steeneveld, Wageningen University & Research 

Discipline area: Physical Sciences and Engineering

Addressing the urban heat island effect (UHI) exacerbated by climate change and urbanization, this project aims to enhance UHI modelling and warning strategies. By incorporating high-resolution urban morphology information from Amsterdam, including reflective properties of roofs, roads and building walls obtained from technologies like Google Streetview and , we seek to improve the accuracy of urban weather models for effective forecasting and validation.

Extreme-scale Navier-Stokes solvers for turbulent flows: GPU performance portability and sustainable development

Lead applicant: Dr. P. Simões Costa MSc, Technische Universiteit Delft 

Discipline area:  Physical Sciences and Engineering

Within this collaboration, we will advance turbulence research by enhancing a Direct Numerical Simulation (DNS) solver, leveraging massively-parallel HPC resources for high-speed flow dynamics at high Reynolds numbers. Our project focuses on improving sustainable solver development workflows and achieving performance portability across diverse hardware configurations for efficient simulations.

FAIVOR: FAIR AI validation and quality control

Lead applicant: Dr. J.P.A. van Soest, Maastricht University 

Discipline area: Life Sciences

Addressing the challenges in implementing AI models in clinical settings, we propose to establish the FAIVOR platform, a software solution for transparently validating AI models while accounting for differences between training and patient populations. These validation results can help to give insights into the trust and robustness of AI models and can inform researchers to learn from previous failures and successes in development of new AI models.

Software Sustainability Call 2023 winners 

HP2SIM: Democratizing multi-physics simulations with high-productivity high-performance finite element software

Lead applicant: Prof. dr. ir. H.E. Bal, Vrije Universiteit Amsterdam 

Gridap, a finite element multi-physics library in Julia, enables access to complex simulations for researchers in various fields, including weather research, photonics, nuclear fusion and offshore engineering. We aim to enhance Gridap, bringing together domain experts, applied mathematicians and HPC experts to collaboratively address partial differential equations, demonstrate capability and engage a broader community for further development. 

JASP-MOD: A module workflow for JASP

Lead applicant: Prof. dr. E.M. Wagenmakers, Universiteit van Amsterdam 


JASP is a widely-used, free open-source statistics programme featuring an intuitive interface. Our project aims to enhance sustainability by making module development more accessible through tutorials and support, and by establishing an online module library, ensuring the JASP ecosystem is user-friendly, manageable and ready for expansion. 


The above text has been refined using ChatGPT. The AI-output has been verified for correctness, accuracy and completeness, adopted where needed, and approved by the authors.