The Data Science Research Programme aims to advance the state of the art in Data Science research and to accelerate the use of Data Science methods at all faculties of Leiden University.

Although science and education have top priority, exploratory projects with companies, governments and NGOs generate ample opportunities in terms of societal challenges, science strategy, valorisation and research collaboration. In the LIACS Applied Data Science Lab, our master's students and graduates…

The master’s programme Statistics & Data Science provides students with a thorough introduction to the general philosophy and methodology of statistical modelling and data analysis. The programme has two specialisations: Data Science and Statistical Science.

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The group Statistical Science is responsible for research and teaching in statistics and data science.

Data sets available for scientific/research purposes.

This page provides an overview of our data management practices.

Are you thinking about studying Statistics and Data Science? Learn more and watch the introduction video.

Social science research helps us understand human behaviour and social structures. These are determined by various factors, which makes the research complex and increases the likelihood of drawing the wrong conclusions. The choice of research method and analysis is therefore extremely important. It…

Leiden University and the Ministry of Infrastructure and Water Management are involved in a collaboration in the form of a research project titled 'Data-Driven Risk Assessment in Infrastructure Networks'.

Wouter Eekhout, our data magician, came in 3d place in the ‪#‎LinksSDGs‬ - Natural language processing and data visualization challenge.

Although the General Data Protection Regulation (GDPR) harmonizes the protection of personal data across the EU as of May 2018, its open norms in combination with cultural differences between countries result in differences in the practical implementation, interpretation and enforcement of personal…

Authority and Control in the Countryside looks at the economic, religious, political and cultural instruments that local and regional powers in the late antique to early medieval Mediterranean and Near East used to manage their rural hinterlands.

Combining results from bibliometric analyses, a global sample of researcher opinions and case-study interviews, a new report reveals that although the benefits of open research data are well known, in practice, confusion remains within the researcher community around when and how to share research…

The master's specialisation Data Science: Computer Science at Leiden University provides students thorough knowledge and understanding of statistical and computational aspects of data analysis, including their application in databases, advances in data mining, networks, pattern recognition, and deep…

This page is under construction.

The CWTS research data management guidelines outline a set of expectations about how CWTS researchers should go about handling data that is collected, processed, (re)used, and shared throughout the lifecycle of a given project.

The Astronomy and Data Science master’s specialisation at Leiden University combines advanced Astronomy courses with relevant courses from the Computer Science programme at Leiden University.

A cross-cut analysis of the ties between university research and fossil industries.

Software and Data of the department Industrial Ecology

This thesis applies data mining in commercial settings in the telecommunications industry.

Computers are becoming so smart that in the future they will perhaps take over the role of judges. In the meantime, experts at Leiden University are examining the question of which standards responsible data science should meet.

Read-Urban was a first project to investigate whether policy recommendations can be made with the aid of linked data collections and data science and to gain experience with the success factors for such a process.

LUMC Technology Focus Area (TFA) Data Analytics is een samenwerkingsverband van verschillende onderzoeksgroepen in het LUMC die nieuwe kwantitatieve en computationele methodologie ontwikkelen voor biomedisch en klinisch onderzoek.

At Leiden University we like to stay in touch with our alumni. We therefore invite you by post, email or phone to lectures, workshops and masterclasses for alumni and inform you about developments in your field and at the University. With your knowledge and experience, you also make a valuable contribution…

Overview of CML software and data

Graduation Ceremony

Archiving Medieval and Post-Medieval Archaeological Fieldwork Data from the Eastern Mediterranean (600-2000)

Explaining treatment response variability between and within patients can support treatment and dosing optimization, to improve treatment of individual patients.

Due to the modern techniques of combinatorial chemistry and high-throughput screening, data on the biological activity of many millions of compounds is known. However, it is still very difficult to transfer this data into knowledge: if we know that compounds A and B bind to a certain protein with high…

In this PhD-thesis several new and existing data science application are described that are particularly focused on applications for tax administrations.

The Collective Experience of Empathic Data Systems (CEEDs) consortium developed novel integrated technologies that support experiencing, analysing and understanding of very large datasets.

This dissertation focuses on developing new mathematical and statistical methods to properly represent time-varying covariates and model them within the context of time-to-event analysis.

Edward Elgar

If researchers make their data FAIR, computers can link large quantities of data and identify patterns, thus greatly accelerating the process of arriving at new insights. In Leiden, the birthplace of ‘FAIR data’, Professor Barend Mons explains the meaning of this term.

Health Data Science Leiden University

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Creating information portals for support of European environmental policy.

‘Tell me something I don’t know,’ said skating coach Jac Orie to Leiden data scientist Arno Knobbe. And he did. Knobbe and his colleagues now assist athletes in all kinds of ways with the help of data mining.