Projects – ODISSEI Social Data Science Team (SoDa)
To get an overview of what citizen science projects are available in the Netherlands, we have created a website with an overview of such projects. The community can contribute their own projects via the gitub page!
Contributors: Peter Lugtig, Annemarie Timmers, Jonathan de Bruin and Leonardo Vida.
OSSC pipeline for Kansenkaart.nl
Using large data sets from Statistics Netherlands, we developed a data pre-processing and analysis pipeline for estimating expectations concerning the inequality of opportunity in The Netherlands using the ODISSEI Secure Supercomputer (OSSC). These estimates will be available on the project website.
Preprocessing GitHub page (currently private)
Analysis GitHub page (currently private)
Contributors: Bastian Ravesteijn, Helen Lam and Erik-Jan van Kesteren.
We have created an R-package to perform geo-enrichment of datasets using openstreetmaps. Enriching geo-coded (latitude/longitude) data sets with features from the physical surroundings enables researchers to take into account spatial surroundings in statistical models.
Contributors: Peter Lugtig, Erik-Jan van Kesteren and Leonardo Vida.
Housing Market data engineering
We are generating datasets from 10TB of online marketing (clicks) data from a large online housing platform. These datasets are then used in research surrounding search behaviour on the housing market in the Netherlands.
Contributors: Joep Steegmans, Jonathan de Bruin
Inference from Volunteer Data
We are creating an analysis pipeline, which will result in a paper outlining how to perform precise statistical inference (correcting for selection bias) using volunteer-generated data.
Contributors: Peter Lugtig, Annemarie Timmers, Erik-Jan van Kesteren, Javier Garcia-Bernardo.
Online Housing Market search strategy
Which search behaviour leads to finding a house quickly on the housing market? We are co-designing and implementing a study on this topic using a large database of online housing search behaviour.
Contributors: Joep Steegmans, Jonathan de Bruin, Erik-Jan van Kesteren
Empathy Diagnostic Dashboard
Research on empathy in anti-social adolescents with the research group on adolescence from the Faculty of Social and Behavioural Sciences from Utrecht University. The project’s goal is to create a tool that can help translate a diagnostic interview into a diagnostic report in which individual scores can be visualized.
Contributors: Minet de Wied, Javier Garcia-Bernardo, Shiva Nadi and Parisa Zahedi.
An initiative to collect an organically growing longitudinal data-infrastructure with information on Dutch companies for academic research. This data will become available for researchers affiliated with universities in The Netherlands through ODISSEI. We are consulting on the technical implementation of the FIRMBACKBONE project.
Contributors: Wolter Hassink, Peter Gerbrands
Synthetic register Data for Open Science
We are exploring the use of existing software packages to generate synthetic datasets for the Statistics Netherlands microdata architecture. These synthetic datasets can then be used as example datasets when sharing analyses (but not original data!) with researchers.
Contributors: Jan Kabatek and Erik-Jan van Kesteren
CBS Network Data Processing
We are aiding the implementation of the Statistics Netherlands population network data files in order to make them available to network researchers. These network data files can be used to develop network analysis models.
Contributors: Tom Emery and Javier Garcia-Bernardo.
Brainstorm: synthetic data
Brainstorming with researchers about working with Statistics Netherlands data and generating synthetic data that can serve as input in an agent-based model.
Contributors: Sanne Hettinga, Corentin Kuster, and Erik-Jan van Kesteren.
Grant application partners
Code Profiling Help
We are available to talk and teach about making statistical analysis code more efficient.
Contributors: Thijs Lindner and Erik-Jan van Kesteren.
Collaborate with us!
You can always drop us a line if you are interested to collaborate on a project.