Generally the data from remote sensing surveys - the scanning of the earth by satellite or aircraft in order to obtain information about it - is screened manually in archaeology. However, constant monitoring of the earth's surface causes a huge influx of data of high complexity and high quality. To…

This project’s aim is to critically assess current homicide data sources in order to develop a proposal for long-term EU-level monitoring of DRH.

The aim of this project is to develop accurate but interpretable ensemble learning methods for high-dimensional multi-domain data.

Promotor: Prof.dr. B.R. Katzy, Co-promotor: R. Ortt

Governments have increasing amounts of data at their disposal. How can big data be used in policymaking? And are governments ready to deal with all this data? That is what Sarah Giest, Assistant Professor at the Institute of Public Administration, is interested in.

The deeper understanding of an organism's pathology is important for developing treatments. Over centuries of systematic research, clinical researchers have demonstrated that the more information they acquire about the cellular properties and their organisation in the tissue, the better they can understand…

This project aims to develop advanced data analysis methods for monitoring and increasing our understanding on biodiversity dynamics in nature reserves such as the Oostvaardersplassen.

Latest technological developments in data mining and profiling.

Promotor: A.P.IJzerman Co-promotor: A. Bender

Sport Data Center

The RISIS project aims at creating a distributed research infrastructure to support and advance science and innovation studies. This will give the field a strong scientific push forward, and at the same time, provide a radically improved evidence base for research and innovation policies, for research…

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…

Parkinson's disease is the second most common neurodegenerative disease in the world. One of its symptoms is the loss of dopaminergic neurons in the substantia nigra pars compacta.

This article provides an in‐depth assessment of lone actor terrorists’ attack planning and preparation.

With the rise of information and communication technologies, large amounts of data are being generated and stored in databases. In order to get a better grip on these large amounts of data, serious efforts are being made to discover patterns and relations in the data with the help of new techniques.…

Quantifying physical activity (using accelerometers) and combining the frequency and intensity of activities with health data (brain MRI, traditional clinical parameters and metabolomics) is of utmost importance to monitor mobility and health among older individuals and study health promotion during…

The coronacrisis is emerging as the ultimate test for political leaders. How do national political leaders get ahead or behind ‘the curve’ of fast-changing dynamics. Martin Lodge (London School of Economics and Political Science) and Arjen Boin (Leiden University Institute of Political Science) look…

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 goal is to establish an intuitive search and querying service that allows researchers to quickly retrieve the most valuable digital resources, in order to allow them to integrate and synthesise the results into a coherent narrative of the past. The current focus of the project is to implement…

To deliver a Virtual Sensor tool optimised to exploit the synergy between Sentinels 2 and 3 to allow the consistent retrieval of land surface parameters (Albedo, LAI, and LST); To extend the existing capabilities of land EO data assimilation tools to add capacity to handle data in the thermal domain…

Athletes always strive for the top. How can data scientists assist them in improving their performance? During the seminar Data Science and Sports, the possibilities and challenges of collaboration between these two worlds were discussed.

The emergence of complex diseases resulting from abnormal cell-cell signaling and the spread of infectious diseases caused by pathogens are significant threats to humanity. Unraveling the dynamic mechanisms underlying cell-cell signaling and infectious disease spreading is crucial for effective disease…

D1.3 describes a set of five case studies relevant in the context of the EuDEco project. Case studies are considered relevant if they are initiatives focusing on the promotion of big data and data reuse or pilots facilitating data reuse in one form or the other. The case studies were expected to allow…

Biologists today have to be able to work with big data. Data analysis skills should be taught from the start of the degree programme, or - even better - in secondary school. This is the message of Vera van Noort, new Professor of Computational Biology. Inaugural lecture 22 January.

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.

Wessel Kraaij has been appointed Professor of Applied Data Analytics with effect from 1 March 2016. Kraaij will use new methods to analyse big data sets. He intends to use data from various data-intensive research fields to test these methods in practice.