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NFDI4Health Local Data Hubs Implementing a Tailored Metadata Schema for Health Data

Abstract (Expand)

Introduction: NFDI4Health is a consortium funded by the German Research Foundation to make structured health data findable and accessible internationally according to the FAIR principles. Its goal is …s. Its goal is bringing data users and Data Holding Organizations (DHOs) together. It mainly considers DHOs conducting epidemiological and public health studies or clinical trials. Methods: Local data hubs (LDH) are provided for such DHOs to connect decentralized local research data management within their organizations with the option of publishing shareable metadata via centralized NFDI4Health services such as the German central Health Study Hub. The LDH platform is based on FAIRDOM SEEK and provides a complete and flexible, locally controlled data and information management platform for health research data. A tailored NFDI4Health metadata schema for studies and their corresponding resources has been developed which is fully supported by the LDH software, e.g. for metadata transfer to other NFDI4Health services. Results: The SEEK platform has been technically enhanced to support extended metadata structures tailored to the needs of the user communities in addition to the existing metadata structuring of SEEK. Conclusion: With the LDH and the MDS, the NFDI4Health provides all DHOs with a standardized and free and open source research data management platform for the FAIR exchange of structured health data.

Authors: Xiaoming Hu, Haitham Abaza, Rene Hänsel, Masoud Abedi, Martin Golebiewski, Wolfgang Müller, Frank Meineke

Date Published: 30th Aug 2024

Publication Type: InProceedings

Making Epidemiological and Clinical Studies FAIR Using the Example of COVID-19

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Abstract FAIRification of personal health data is of utmost importance to improve health research and political as well as medical decision-making, which ultimately contributes to a better health of …utes to a better health of the general population. Despite the many advances in information technology, several obstacles such as interoperability problems remain and relevant research on the health topic of interest is likely to be missed out due to time-consuming search and access processes. A recent example is the COVID-19 pandemic, where a better understanding of the virus’ transmission dynamics as well as preventive and therapeutic options would have improved public health and medical decision-making. Consequently, the NFDI4Health Task Force COVID-19 was established to foster the FAIRification of German COVID-19 studies. This paper describes the various steps that have been taken to create low barrier workflows for scientists in finding and accessing German COVID-19 research. It provides an overview on the building blocks for FAIR health research within the Task Force COVID-19 and how this initial work was subsequently expanded by the German consortium National Research Data Infrastructure for Personal Health Data (NFDI4Health) to cover a wider range of studies and research areas in epidemiological, public health and clinical research. Lessons learned from the Task Force helped to improve the respective tasks of NFDI4Health.

Authors: Iris Pigeot, Wolfgang Ahrens, Johannes Darms, Juliane Fluck, Martin Golebiewski, Horst K. Hahn, Xiaoming Hu, Timm Intemann, Elisa Kasbohm, Toralf Kirsten, Sebastian Klammt, Sophie Anne Ines Klopfenstein, Bianca Lassen-Schmidt, Manuela Peters, Ulrich Sax, Dagmar Waltemath, Carsten Oliver Schmidt

Date Published: 1st Jul 2024

Publication Type: Journal

Standardization landscape, needs and gaps for the virtual human twin (VHT)

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This document created within the European Coordination and Support Action (CSA) of the EDITH (Ecosystem Digital Twins in Healthcare) project describes the current landscape of formatting and description … standards, terminologies and metadata guidelines for virtual human twins (VHTs). It refers to corresponding biomedical data, simulation models and workflows, as well as their metadata relevant for the definition, implementation, and simulation of Digital Twins in Healthcare (DTHs). It comprises both, ISO and community standards and lists the relevant standards and terminologies describing the modelling process, the integration of domain-specific medical research data with routine data from electronic health records, the documentation of data provenance, the validation process for biomedical, physiological, bio-signaling and other healthcare data and models. The document also reveals needs and gaps in the current standards landscape to drive the further development of such standards. Therefore, remarks and comments on how to improve existing standards or on areas for which standards are still missing are very welcome.

Author: Gerhard Mayer, Martin Golebiewski

Date Published: 17th Jan 2024

Publication Type: Tech report

The NFDI4Health Metadata Schema (V3_3)

Abstract (Expand)

Originally developed by the NFDI4Health Task Force COVID-19, the Metadata Schema of the NFDI4Health contains a list of properties that describe a resource to be registered in the German Central Health … Study Hub. Currently, two main types of resources are distinguished: a) study descriptions (i.e., metadata set describing a study) and b) study documents. However, due to the generic character of the Metadata Schema, other types of resources may also be described and registered. The metadata properties are divided into mandatory and recommended ones. Along with bibliographic information such as title and description of the resource, the related persons and organizations contributing to the development of the resource can also be specified. The results of studies published in journal articles or other text publications can be linked too. For studies, information about study design and accessibility of the collected data should be additionally provided. The Metadata Schema consists mainly of properties adapted from established standards and models such as DataCite Metadata Schema 4.4, data models of the ClinicalTrials.gov, German Clinical Trials Register, International Clinical Trials Registry, HL7® FHIR, MIABIS, Maelstrom Research cataloguing toolkit and DDI Controlled Vocabularies. This is an updated version V3_3 of the Metadata Schema, which improves the modules of the previous version via refined display names, description and additional information texts, and short input helps and examples. The new version also introduces a new url item in the data sharing section for linking to data request applications. The undertaken changes are described within the document.

Authors: Haitham Abaza, A. Shutsko, Martin Golebiewski, Sophie Klopfenstein, C. O. Schmidt, Carina Vorisek, C. Brünings-Kuppe, V. Clemens, J. Darms, S. Hanß, T. Intemann, F. Jannasch, E. Kasbohm, Birte Lindstädt, Matthias Löbe, E. Orban, I. Perrar, M. Peters, U. Sax, M. Schulze, C. Schupp, F. Schwarz, C. Schwedhelm, S. Strathmann, Dagmar Waltemath, H. Wünsche, A. Zeleke

Date Published: 5th Dec 2023

Publication Type: Misc

Data Publication for Personalised Health Data

Abstract (Expand)

Health data collected in clinical trials and epidemiological as well as public health studies cannot be freely published, but are valuable datasets whose subsequent use is of high importance for health … research. The National Research Data Infrastructure for Personal Health Data (NFDI4Health) aims to promote the publication of such health data without compromising privacy. Based on existing international standards, NFDI4Health has established a generic information model for the description and preservation of high-level metadata describing health-related studies, covering both clinical and epidemiological studies. As an infrastructure for publishing such preservation metadata as well as more detailed representation information of study data (e.g. questionaries and data dictionaries), NFDI4Health has developed the German Central Health Study Hub. Content is either harvested from existing distributed sources or entered directly via a user interface. This metadata makes health studies more discoverable, and researchers can use the published metadata to evaluate the content of data collections, learn about access conditions and how and where to request data access. The goal of NFDI4Health is to establish interoperable and internationally accepted standards and processes for the publication of health data sets to make health data FAIR.

Authors: Juliane Fluck, Martin Golebiewski, Johannes Darms

Date Published: 7th Sep 2023

Publication Type: Proceedings

NFDI4Health Local Data Hubs for Finding and Accessing Health Data

Abstract (Expand)

To support federated data structuring and sharing for sensitive health data from clinical trial, epidemiological and public health studies in the context of the German National Research Data Infrastructure … for Personal Health Data (NFDI4Health), we have developed Local Data Hubs (LDHs) based on the FAIRDOM-SEEK platform. Those LDHs connect to the German Central Health Study Hub (CSH) to make the health data searchable and findable. This decentralised approach supports researchers to make health studies with their data FAIR (Findable, Accessible, Interoperable and Reusable), and at the same time fully preserves data protection for sensitive data.

Authors: Frank Meineke, Martin Golebiewski, Xiaoming Hu, Toralf Kirsten, Matthias Löbe, Sebastian Klammt, Ulrich Sax, Wolfgang Müller

Date Published: 7th Sep 2023

Publication Type: Proceedings

Provenance Core Data Set: A Minimal Information Model for Data Provenance in Biomedical Research

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The exchange, dissemination, and reuse of biological specimens and data have become essentialfor life sciences research. This requires standards that enable cross-organizational documentation, traceability, … and tracking of data and its corresponding metadata. Thus, data provenance, or the lineage of data, is an important aspect of data management in any information system integrating data from different sources [1]. It provides crucial information about the origin, transformation, and accountability of data, which is essential for ensuring trustworthiness, transparency, and quality of healthcare data [2]. For biological material and derived data, a novel ISO standard was recently introduced that specifies a general concept for a provenance information model for biological material and data and requirements for provenance data interoperability and serialization [3,4]. However, a specific standard for health data provenance is currently missing. In recent years, there has been a growing need for developing a minimal core data set for representing provenance information in health information systems. This paper presents a Provenance Core Data Set (PCDS), a generalized data model that aims to provide a set of attributes for describing data provenance in health information systems and beyond. 

Authors: Ulrich Sax, Christian Henke, Christian Dräger, Theresa Bender, Alessandra Kuntz, Martin Golebiewski, Hannes Ulrich, Mattias Löbe

Date Published: 7th Sep 2023

Publication Type: Journal

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