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.

This study seeks to partially fill the knowledge gap about national culture in Africa, basing its research on data on ethnolinguistic groups (instead of administrative regions).

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

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.

From 14 to 29 PhD candidates, seven actively involved faculties and, above all, lots of innovative interdisciplinary research, all with data science as the common denominator. The university’s Data Science Research Programme (DSO) has proven so successful that after five years on a start-up grant it…

Sport Data Center

The marine shipping industry is one of the strongest emitters of nitrogen oxides (NOx), a pollutant detrimental to ecology and human health. Over the last 20 years, the pollution produced by power plants, the industry sector, and cars has been decreasing.

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…

What workflow of non-destructive techniques provides accurate, valuable data to improve our understanding of Caribbean archaeological landscapes? How were Amerindian settlements configured?

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…

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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.

Dutch speedskaters have been winning the most medals in speed skating at the Winter Olympics for years. How? Based on their intuition. Scientist Jeroen van der Eb of the Data Mining & Sports group of the Leiden Institute of Advanced Computer Science (LIACS) wants speedskaters to adjust their irons based…

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.…

On 20 February 2019, a special meeting on data science took place in the House of Representatives. The aim of the meeting was to start a dialogue with government organisations about data developments within the government.

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…

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.

By analysing the metabolism using big data techniques, we can identify health risks at an earlier stage. Thomas Hankemeier, professor of Analytical Biosciences at the Leiden Academic Centre for Drug Research, explains how that works.

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…

Leiden University is investing 4 million euros in a new Data Science research programme. This is a joint initiative of all the faculties, headed by Dean Geert de Snoo at the Faculty of Science. The programme will focus on Leiden scientific data.

Data play an important role in any organization. More and more data are available about products, about production processes and about customers. At the annual LIACS Business Event on Wednesday 18 January, the central message was how to find irregularities in Big Data, and how it can help you to track…

Leiden bachelor students analyse data EC soccer Students are now familiar with something sports journalists already knew: summer holidays can be a time of hard labour. Everybody else is lying on the beach, but for you, it is the busiest time of the year. Leiden bachelor students collected the data…

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.

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…

Promotor: Prof.dr. A. Achucarro