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…

Comparing individual health data with group data allows doctors to give personalised advice and patients to learn from one another's experiences. Wessel Kraaij, Professor of Applied Data Analytics, shows how personal data can have a valuable predictive function. Inaugural lecture 24 February.

Data reuse and big data: a taxonomy for personal data reuse.

By comparing individual health data with population data, doctors can provide personalized health advice and patients can learn from each other's experiences. Wessel Kraaij, professor of Applied Data Analytics shows how personal data can have predictive value.

What consequences does Brexit have for the protection of personal data?

At Psychology Lab on Wheels, we take your privacy and the security of your personal data very seriously. We want to assure you that all the information collected during this study will be handled in accordance with the General Data Protection Regulation (GDPR).

As a PhD candidate, you probably work with personal data. That’s not just names and telephone numbers – it can also include things like cookies. To keep (personal) data as secure as possible, the university has established an information security policy.

On 7 February 2019, Helena Ursic-Vrabec defended her thesis 'Uncontrollable: Data subject rights and the data- driven economy'. The doctoral research was supervised by Prof. dr. S. van der Hof.

Sarah Giest and Annemarie Samuels, both Assistant Professors at Leiden University, researched the quality and coverage of the data being collected for policiymakers to be used, specifically pertaining to minority groups.

The research of this PhD project can be subdivided into two main disease areas: migraine and stroke. For both we will be investigating how artificial intelligence (AI) and machine learning (ML) techniques can be used to study these afflictions, their (early) detection, and their potential treatment.

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…

On 12 September 2019, Michiel Rhoen defended his thesis 'Big Data, Big Risks, Big Power Shifts: Evaluating the General Data Protection Regulation as an instrument of risk control and power redistribution in the context of big data'. The doctoral research was supervised by Prof. G.J. Zwenne and Prof.…

Modern computer-aided simulation tools used by various industries produce gigabytes of data. But currently, they take days and even up to weeks of computation effort. To make the best use of all these data, the DAMIOSO project focuses on developing algorithms and tools for managing, mining, and optimizing…

Data Sets Department of Economics

The extensive use of electronic communication channels and other devices has opened new possibilities for collecting data on human behavior. This information is sometimes openly accessible, but largely part of administrative registration systems that are not open to the broader public. The data provides…

How can teachers be motivated by their students’ data in making stepwise changes to their teaching practices?

The ability to collect and interpret huge quantities of data has become indispensable to society and academia. Leiden University is a knowledge and expertise centre for data science that places the emphasis on interdisciplinary collaboration and innovation.

The SAPPAO project aims to optimise the accuracy and reliability of predicting scheduled flight times. The full name of the project is 'A Systems Approach towards Data Mining and Prediction in Airlines Operations'.

The change from a closed institution to an open living environment for patients with late stages of dementia will give the patients more freedom in their day-to-day life. The effect of this change on the patients’ mobility, activity and interaction with others will be assessed with sensor technology…

The Data-Driven Drug Discovery Network (D4N) is an initiative by researchers from Leiden University and collaborators to join efforts in applying and developing novel techniques from data science to drug discovery and related topics from bioinformatics.

Open Science means not only sharing final research results but also the underlying data. A main way to do that is by making research data FAIR: Findable, Accessible, Interoperable and Reusable.

Today, everybody and everything produces data. People produce large amounts of data in social networks and in commercial transactions. Medical, corporate, and government databases continue to grow. Sensors continue to get cheaper and are increasingly connected, creating an Internet of Things, and generating…

Promotor: J.N. Kok, Co-Promotor: A.J. Knobbe

LACDR adheres to strict data management rules, with the aim to make our data findable, accessible, interoperable and re-usable. For this reason all LACDR PhD candidates are required to prepare a data management plan and to implement data management rules accordingly. All PhD candidates follow a data…

The majority of scientists, from archaeologists through to zoologists, collect enormous volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics and computer science, we can develop algorithms for analyzing…

Netherlands Statistics (CBS), Leiden University and the University of Amsterdam have started a collaboration in the form of a research project titled 'Enriching official economic statistics using data-driven modelling techniques'.

The majority of scientists, from archaeologists through to zoologists, collect huge volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics, we can develop algorithms for analysing and identifying patterns…

The project 'Data use, online consumer needs, business strategies and regulatory response' aims to explore and examine the factors that impact upon the efficacy of information disclosure duties pertaining to customer data use in online business.

Promotores: J.C. van Houwelingen, S.A. van de Geer

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…

Health research, medical practice and consequently the whole population is increasingly affected by digitization, data science and AI.

Before your student residence permit can be issued, you must have your biometric data recorded.

The Explainatory Data Analysis group develops algorithms and theory that enable domain experts to explain data by finding interpretable patterns and models.

Why should you publish your data? ... and how?

Our group is part of the Metabolomics and Analytics Centre where we accompany the data from its acquisition all the way to the publication of identified associations and biomarkers for a range of human diseases. The generated data of the metabolic measurements are assessed using an in-house quality…

Collecting data in sports increased in importance the last few years.

Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.

Sport Data Center

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.

The Data Management Protocol is an elaboration of the Leiden University Data Management Regulations for research that takes place within the Leiden Institute of History. It is intended for researchers who are starting a research project and / or researchers who are going to submit a proposal to external…

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…

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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.

Promotor: J.N. Kok, Co-promotor: W.A. Kosters

De minor Data Science & Artificial Intelligence geeft een toegankelijke introductie tot de theorie en praktijk van datawetenschap en kunstmatige intelligentie. Studenten leren de basis van data-analyse en patroonherkenning in grote gegevensverzamelingen, hoe computers leren en ook het interpreteren…

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