Machine Learning is becoming a more and more substantial technology for industry.

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).

Data management is crucial for the success of research projects.

Real-life processes are characterized by dynamics involving time. Examples are walking, sleeping, disease progress in medical treatment, and events in a workflow.

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.

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

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.

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

Data Science (DS) and Artificial Intelligence (AI) are omni-present and have the potential to be incorporated in various fields. However, in order to live up to this expectation, a good understanding of the techniques, their implications and limitations is required. In this minor you develop insights…

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

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…

Sport Data Center

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…

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…

Data sets available for scientific/research purposes.

This page provides an overview of our data management practices.

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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…

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…

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…

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 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.

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

Exploring the value of data-driven approaches in education: collecting, analysing, and interpreting data from educational environments to improve teaching and learning outcomes.

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.

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

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…

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

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

DIGIFOOD is a transnational research project that investigates how data governance can support equitable and sustainable digital food systems. Around the world, digital technologies are transforming agriculture. Sensors in soil, satellites in space, and mobile phones in farmers’ hands are generating…

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.

VODAN Africa started as a platform to enable access to critical data needed from Africa to fight the novel COVID-19. The initiative was inspired by the experience from the Liberia Ebola Virus outbreak in 2014: early detection requires contact tracing. Inclusion of the most vulnerable is critical to…

Promotor: Prof.dr. L.J. Slikkerveer

This project is a collaboration between Sanquin, LUMC and LIACS. It focuses on the development of meta-modelling methods and tools for the exchange, analysis, and publication of anonymised patient data. Measures are being constructed to evaluate both the level of privacy and the extent to which an anonymized…

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

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

A lively discussion on impact and society

A lively discussion on impact and society.

Developing new medicines is one of modern science's most significant hurdles, a process marked by high costs, long timelines, and frequent failures of promising candidates.

Edward Elgar