This project develops a scientific method to extract clinically relevant new information from patient forum websites that discuss patient experiences concerning e.g. medication, nutrition, co-morbidities, genetic factors etc.

ChEMBL is a large-scale drug discovery database containing bioactivity information primarily extracted from scientific literature.

This thesis deals with the use of sound in interactions in the context of participatory systems and data sonification. We investigate an interactive environment where participants perceive information of the data through sound elements.

Archiving Medieval and Post-Medieval Archaeological Fieldwork Data from the Eastern Mediterranean (600-2000)

Als gevolg van de grote technologische vooruitgang in de gezondheidszorg worden in toenemende mate gegevens verzameld tijdens de uitvoering van klinische onderzoeken.

This project aims to explore and examine the factors that impact upon the efficacy of information disclosure duties pertaining to customer data use in online business.

Tomography is a powerful technique to non-destructively determine the interior structure of an object.Usually, a series of projection images (e.g.\ X-ray images) is acquired from a range of different positions.

How to access the end-of-supply risk of spare pares using big data analytics

Due to the modern techniques of combinatorial chemistry and high-throughput screening, data on the biological activity of many millions of compounds is known. However, it is still very difficult to transfer this data into knowledge: if we know that compounds A and B bind to a certain protein with high…

On 23 April, Andreas Häuselmann defended the thesis 'EU privacy and data protection law applied to AI: unveiling the legal problems for individuals'. The doctoral research was supervised by Gerrit-Jan Zwenne and Bart Custers.

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.

This monograph focuses on clustering of objects in high-dimensional data, given the restriction that the objects do not cluster on all the attributes, not even on a single subset of attributes, but often on different subsets of attributes in the data.

This thesis focuses on data found in the field of computational drug discovery. New insight can be obtained by applying machine learning in various ways and in a variety of domains. Two studies delved into the application of proteochemometrics (PCM), a machine learning technique that can be used to…

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…

The Digital Archaeology research group manages two computer laboratories with different purposes: the teaching lab (F1.01) and the research lab (A1.13a).

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

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

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

To what extent is it possible to utilise traditional and new media data to examine and understand the nature and scope of homicide in Indonesia?

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…

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

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…

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

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.

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 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…

Sport Data Center

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

While bioinformatics methods deal with the analysis of sequence information (be it proteins or DNA), the field of cheminformatics is concerned with the analysis of small-molecule datasets.

This project aims to improve understanding of, and responses to, the phenomenon of lone actors through analysis of comprehensive data on cases from across Europe.

Data science offers exciting new instruments for governments to reach out to citizens, for example by using data-driven information channels, providing real-time simulations, or personalizing services based on citizen data. At the same time, the possibilities and use of data science methods can have…

On 9 October, Corné Smit defended his doctoral thesis, 'Minority governments in the Netherlands and Denmark '. The PhD research was supervised by Luc Verheij and Geerten Boogaard.

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…

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).

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.

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…

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…

Latest technological developments in data mining and profiling.

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.