Cross-departmental Center B: Data Science


High quality research data are essential for epidemiological research. Generally, it is not possible to fully exploit the potential of the research data generated in individual research projects given their typically narrow focus and limited duration. These data frequently offer the opportunity to investigate further questions that may not have been foreseen at the time of project inception or could not have been answered within the context of the individual project. In order to fully exploit this potential in terms of efficient use of resources, there have been increasing demands to publish research data and share them with external researchers (data sharing). To this end, research data should be provided in accordance with the so-called FAIR Guiding Principles: According to these principles, research data should be findable, accessible, interoperable, and reusable by third parties. This means that data-generating institutions such as BIPS will face the necessity to significantly increase the efforts for data processing and documentation in order to enable meaningful third-party use in compliance with all legal and ethical requirements. At the same time, data sharing offers the opportunity to address own research by additionally analyzing external data sources and to develop novel research questions by combining various external data sources with own data.

The Cross-departmental Center for Research Data Infrastructure and Data Science in Epidemiology is directly linked to the scientific director and accommodates staff from all departments, with a major focus on Department of Biometry and Data Management. The cross-departmental center targets two areas: (A) research data infrastructure and management and (B) the methodological competence in the field of data science. In each area, we will focus on two model projects to address the particular requirements of primary and secondary data.

In model project B1, we will establish a research group that will conduct a pooling study to determine reference values for clinically relevant biomarkers in children. This will build on a previously published special issue in the International Journal of Obesity "Filling the gap: international reference values for health care in children" (edited by Ahrens W, Moreno LA, Pigeot I). The research group will identify suitable biomarker studies worldwide, assess their data quality and establish collaborations with them. The data from the participating studies will subsequently be calibrated and harmonized, virtually pooled and analyzed using federated data analyses.

In Model project B2, we will conduct a pharmacoepidemiological study on new cancer therapeutics under the leadership of BIPS together with international partners using harmonized large European registry and secondary data sources. We will use approaches to standardize data sources with so-called common data models and then analyze the data locally with standardized scripts, which has been shown to be the most feasible way to conduct international pharmacoepidemiolocial studies in compliance with data protection regulations. The established methods and collaborations can also be used for other projects and will secure the international competitiveness of the BIPS in pharmacoepidemiological research.

Funding period

Begin:   January 2023
End:   December 2025


  • AV-WGL


Prof. Dr. rer. nat. Iris Pigeot


Cross-departmental Center A: Research Data Infrastructure

Biomarkers4Pediatrics is a recently established initiative that brings together international population-based studies in children and adolescent populations with biomarkers and anthropometric and physiological measurements collected.

Selected project-related publications

    Presentations at scientific meetings/conferences (invited)

  • Ahrens W. Determinants of eating behaviour in European children, adolescents and their parents: Overview & key findings. 9th Cyprus Public Health Workshop, 3 October 2023, Limassol, Cyprus.
  • Presentations at scientific meetings/conferences

  • Swenne A, Intemann T, Pigeot I. Federated generalized additive models for location, scale and shape in DataSHIELD. Monthly Meeting of the DataSHIELD Statistical Development Theme, 7 March 2024, online presentation.
  • Swenne A, Intemann T, Pigeot I. Federated generalized additive models for location, scale and shape in DataSHIELD. 70th Biometric Colloquium, 28 February-1 March 2024, Lübeck.