Big Data and Research Methods
Higher education in the Netherlands is highly ranked. In the World Economic Forum’s Global Competitiveness Index 2016–2017, it was ranked third after Singapore and Finland.
Moreover, Dutch universities as a group have done very well in global university rankings. All thirteen publicly funded research universities made it to top 200 in THE World University Rankings 2018. Seven were ranked higher than the best-ranked Finnish university and twelve higher than the second bestranked Finnish university.
The board and office of the Finnish Union of University Professors visited the Netherlands to find out what there is to learn from the Dutch university system. They were hosted by Leiden University and Netherlands eScience Center. This article will focus on the eScience Center.
In the past, scientific disciplines worldwide had their own characteristic methods and research tools. In digital society, however, the most important tool in all scientific disciplines is the computer. Since researchers can have access to large amounts of data that must be managed, research projects are getting more and more complex and require new software, new methods and new practices.
The Dutch government seems to have understood what this means to Dutch universities. The “Wetenschapsvisie 2025” of the Dutch government calls for the strengthening of e-infrastructure and eScience in order to maintain the position of Netherlands as an attractive country for scientists and innovative industry. Modern e-infrastructure facilitates highperformance and distributed computing, networking, storage, and visualisation.
The eScience Center is a joint initiative of the Dutch national research council (NWO) and the Dutch organisation for ICT in education and research (SURF). The Center defines itself as “the national hub for the development and application of domain overarching software and methods for the scientific community”. The Center makes collaborative calls. The eScience Center funds and participates in multidisciplinary projects with data-handling, computing and big-data analytics at their core.
In other words, the eScience Center helps Dutch universities develop and apply digitally enhanced scientific tools and methods. The path from data to scientific breakthroughs consists of four steps:
Optimised data handling
1. Data: storage, access, privacy, metadata
2. Processing: annotation, integration
Big data analysis
3. Analysis: modelling, statistics, machine learning
4. Interpretation: visualisation, user interfaces
The Center prefers to develop a limited number of core technological competences where it can have a broad impact on research practices. To create an eScience platform, the Center tries to develop versatile tools and research software that can be generalised. Part of the work is to participate in international coordination within the confines of PLAN-E and EOSC.
The approach is problem-driven. The Center can collaborate with any research discipline. To increase the impact of its work, the Center nevertheless focuses on four broad discipline areas: Environment & Sustainability, Life Sciences & eHealth, Humanities & Social Sciences, and Physics & Beyond. While some of the disciplines within these discipline areas are early adopters of eScience methods, some may use eScience for the first time.
The benefits of Netherlands eScience Center are long term. For funding reasons, however, the Center has thought about ways to show even short-term benefits. Since eScience is the future of research, there are no past economic benefits. One may nevertheless signal research benefits in a quantitative way on the basis of research papers, downloads, or software IDs, or in a qualitative way by narratives. In the future, the Center might lead to spin-offs or consultancy work.
Although the eScience Center develops digital methods, the Center prefers face-to-face meetings with its partners. The staff of the eScience Center thus spend much time on the road visiting Dutch universities and talking directly to researchers and customers.
What lessons can one learn?
The first lesson is about ambition. The Dutch government seems to have understood that a country cannot be competitive in research unless its universities develop new digital research tools and practices that help to address questions that used to be beyond scientists’ reach.
In contrast, the Finnish government has chosen a different path. The Finnish government seems to focus on the digitalisation of education in the false belief that this will help to reduce the number of university lecturers and cut costs. This explains why the digitalisation of education tends to be mentioned — and the digitalisation of research not mentioned — in the new strategies of Finnish universities.
The second lesson relates to the structure of the university sector. It brings benefits to break the silo model of traditional universities. Innovative research increasingly is problem-driven. As a multidisciplinary platform for problem-driven cooperation and as a center that develops generally applicable research tools and practices and participates in multidisciplinary projects, Netherlands eScience Center contributes to a matrix organisation of university research.
University research that the eScience Center participates in is not organised along disciplinary lines. In the long run, this can contribute to new multidisciplinary structures at Dutch universities as well.
Third, one thinks about the number and spatial proximity of universities. The spatial proximity of many research universities in a rather small country seems to increase both cooperation and competition and the spreading of know-how. Cooperation and competition lift all boats and make the Dutch university sector more competitive and innovative as a whole.
The fourth lesson relates to collaboration. Netherlands eScience Center pays attention to being collaborative. It collaborates with researchers, start-ups and established firms. What it tries to avoid is focusing too much on its own research or technology. Shortly put, an eScience center should not be too lured towards its own infrastructure if it is to have an impact.
The fifth lesson is about proximity. Having many eScience specialists under the same roof increases the spreading of knowledge and innovation. So do face-to-face meetings between eScience specialists and scientists. There is no serious collaboration unless the parties meet in the same place.
Of course, university researchers could learn much more from the research projects of the eScience Center. You can use big data to study things ranging from the Big Bang to the human brain and from the weather to the use of case law by judges.