Research institutes

Institute of Data Science

Vast amounts of data being generated across all segments of society. If taken advantage of, these data offer an unprecedented opportunity to accelerate scientific discovery, to improve healthcare and wellbeing, and to strengthen our communities. Data Science is an interdisciplinary field concerning the scientific methods, systems and workflows to obtain insights from data.

Data Science has the potential to affect all aspects of human activity. We embrace this development and are preparing a new generation of data scientists, scholars and entrepreneurs who work in a collaborative manner to tackle the world’s most pressing problems.


Research at IDS focuses on: 

  • accelerating scientific discovery through powerful platforms for scalable, collaborative and reproducible discovery science
  • improving clinical care and wellbeing by developing a learning health system to understand the health of diverse populations and to maximise the wellness and health outcomes for individuals.
  • empowering communities so that they can learn what works, what doesn’t, and how to enact change to improve the quality of life for themselves and their neighbours

IDS aims to tackle impactful research problems through multidisciplinary teams involving students, researchers, partners, and stakeholders inside and out of the university. We aim to train the next generation of data scientists to be even more collaborative and interdisciplinary.


  • Thomas Cleij appointed as new Dean of the Faculty of Science and Engineering

    Thursday, February 28, 2019

    The Executive Board of Maastricht University (UM) has appointed Prof. dr. Thomas Cleij as the new dean of the Faculty of Science & Engineering.

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  • Data Driven Society event

    UM and Dutch Embassy host Berlin Science Week event

    Monday, November 5, 2018

    Maastricht University (UM) is the only Dutch university to have organised an event together with the Dutch Embassy during the famous Berlin Science Week.

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  • Postdoc part of ESOF Panel on AI

    Wednesday, July 18, 2018

    Amrapali Zaveri, postdoc at IDS,  was part of a panel on “Increasing Scientific Productivity through Artificial Intelligence” of the EuroScience Open Forum conference.


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Social media

    • Photo by Institute of Data Science at University of Maastricht

      Did you already have a chance to check out the programme of the upcoming Symposium on FAIR Personal, Open and Distributed Data on the Web? We offer a line-up of 9 talks follewed by working sessions with expert guided discussions on several themes.

      Have a look at the UM Event Page and join us Friday 24 May from 13.00 until 17.30 hrs in the Jo-Ritzen Room (OXF55).

      The event is organised by the Institute of Data Science in collaboration with IDLab form the Universiteit Gent and industry partner ONTOFORCE.

      The symposium is open to all and free of charge.
      #UMDataScience #DataScience #FAIR

      Symposium on FAIR Personal, Open and Distributed Data on the Web - events - Maastricht University
      1 day 9 hours ago
    • Last Wednesday, Lianne Ippel gave the second workshop in Survey Construction as part of the research workshop series at the University College Maastricht! In two hours first year bachelor liberal arts students dived into all the in's and out's of questionnaire design and how to conduct a survey for their own research projects.
      #UMDataScience #DataScience #Survey

      1 day 20 hours ago
    • Photo by Institute of Data Science at University of Maastricht

      The open acces journal Data Science ( invites submissions for a special issue on FAIR Data, Systems and Analysis, that will be published on October 15th, 2019 and will be edited by Michel Dumontier and Paul Groth

      Submissions are due by June 1st, 2019!

      All submitted papers to the special issue will be made openly available on the journal website as pre-prints before the reviewing starts, so reviewers and everybody else will be free to not only read but also share submitted papers.
      Submissions should comply with the guidelines for authors as outlined at For submitting please go to

      Please consult for more detailed information about the journal.

      The aim of this special issue is to highlight unique contributions towards the development and assessment of FAIR data, systems, and analysis. Topics of submissions include, but are not limited to:
      - systems to automatically create FAIR data and services
      - methods to automatically capture detailed provenance and other metadata
      - development and maintenance of FAIR knowledge graphs
      - FAIR support tools, repositories and resources
      - methods, tools and systems for computing and using FAIR assessments
      - computable licenses and terms of use
      - novel analytics for FAIR data
      - distributed systems to share and mine sensitive data in a privacy preserving manner
      - legal and ethical contributions related to FAIR data and systems
      - contributions to assess the economic value and benefits of FAIR

      The FAIR principles ( outline key attributes to make digital resources more Findable, Accessible, Interoperable, and Reusable. Globally endorsed and widely adopted, there is now a pressing need to enable the establishment of an Internet of FAIR Data and Services, to demonstrate how these can be used to generate new insights, and to assess the overall value proposition for FAIR across different sectors (health, finance, law, etc). Realizing the value of the FAIR principles will require a combination of scientific, technical, social, legal, and ethical advances for the production, sharing, discovery, assessment, and reuse of data.

      #UMDataScience #DataScience

      About Data Science | Data Science
      2 days 11 hours ago