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 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…

This page provides an overview of our data management practices.

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.

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…

Promotor: J.N. Kok, Co-promotor: F.J. Verbeek

It is the end of your archaeological research project, and you may be wondering where to deposit your data. After the excavation, all of the finds are drawn, scanned, digitised, and the database is completed. Perhaps you have also accumulated a lot of data through further scientific analysis of the…

Whilst the world is opening up, the teaching will continue in a hybrid form next academic year. During the past year, when all of us were bound to our home offices and computer screens, new forms of education had to be developed – some of which proved to be efficient in preparing the students for their…

The world is becoming increasingly digitised, and the information one has easy access to is often rather overwhelming. In particular, the accumulative nature of the archaeological practice has resulted in huge quantities of data being produced. But how to prevent these from becoming dust-collectors…

Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…

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.

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.

Tremendous amounts of data are generated in scientific research each day. Most of this data has more potential than we are using now, says Katy Wolstencroft, assistant professor in bioinformatics and computer science. We just need to integrate and manage it better.

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

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…

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.

Nowadays data-driven working is very important within Rijkswaterstaat. A Variety of employees is involved in analyzing the data collected on daily basis by Rijkswaterstaat. The goal is to ensure that we construct an infrastructure in the Netherlands which will be safe, accessible and liveable in the…

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…

Edward Elgar

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

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.

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

Didactics, Career development

VVI Research Meetings 2022-2023

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 Technology and Operation Management (TOM) group focuses on the operational challenges of adopting new cutting-edge technologies in areas such as artificial intelligence, precision medicine, and high-tech instrumentation.

Data Sets Department of Economics

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'.

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 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…

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.

This book discusses theories of crisis management and the radical right, to shed light on how responses to crisis influence radical right parties in their presence, discourse, and evolution. The book offers a comparative perspective by examining case studies with various traditions of radical right…

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.

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…

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…

Paul Hudson, Associate Professor of Physical Geography at Leiden University College, examines human impacts on lowland rivers in his new book.

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 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 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…

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

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.

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

The management teams lead the department and consist of a General Manager, an Outreach Manager, an Instrumentation Manager, an ICT/Housing Manager, a HR/Finances Manager and an Education Manager.

Promotor: Prof.dr. B.R. Katzy, Prof.dr. H.J. van den Herik, Prof.dr. G.H. Baltes (University of Applied Sciences Konstanz)