Cross-departmental Center A: Research Data Infrastructure

Description

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 A1, the data of the IDEFICS/I.Family cohort are to be processed following the FAIR principles to serve as a prototype for the provision of particularly sensitive primary study data. To achieve this goal, the existing structured metadata will be expanded by a detailed documentation of the data provenance and quality and will be published to make the data better findable for potential external researchers. Procedures for secure data access and monitoring of data use must be developed and tested. Additionally, it is planned to set up a web portal for interactive analyses that may be conducted before applying for data access to assess the usefulness of this data source for the respective study purpose.

In model project A2, GePaRD is to be gradually expanded into a research data center [Forschungsdatenzentrum (FDZ)] to make this important data source available to external researchers. Considering the current legal requirements, workplaces at BIPS for guest researchers using this data will be established. The preparation of the premises will include the establishment of effective control measures and security precautions. Additional technical procedures will be put in place to prevent unauthorized data use.

Funding period

Begin:   January 2023
End:   December 2025

Sponsor

  • AV-WGL

Contact

Prof. Dr. rer. nat. Iris Pigeot

Links

Cross-departmental Center B: Data Science (German)

Cross-departmental Center B: Data Science (English)

Biomarkers4Pediatrics - International Multicohort Pediatric Biomarker Collaboration