Towards an Interoperability Landscape for a National Research Data Infrastructure for Personal Health Data.

Abstract (Expand)

The German initiative "National Research Data Infrastructure for Personal Health Data" (NFDI4Health) focuses on research data management in health research. It aims to foster and develop … harmonized informatics standards for public health, epidemiological studies, and clinical trials, facilitating access to relevant data and metadata standards. This publication lists syntactic and semantic data standards of potential use for NFDI4Health and beyond, based on interdisciplinary meetings and workshops, mappings of study questionnaires and the NFDI4Health metadata schema, and literature search. Included are 7 syntactic, 32 semantic and 9 combined syntactic and semantic standards. In addition, 101 ISO Standards from ISO/TC 215 Health Informatics and ISO/TC 276 Biotechnology could be identified as being potentially relevant. The work emphasizes the utilization of standards for epidemiological and health research data ensuring interoperability as well as the compatibility to NFDI4Health, its use cases, and to (inter-)national efforts within these sectors. The goal is to foster collaborative and inter-sectoral work in health research and initiate a debate around the potential of using common standards.

Authors: C. N. Vorisek, S. A. I. Klopfenstein, M. Lobe, C. O. Schmidt, P. J. Mayer, M. Golebiewski, S. Thun

Date Published: 13th Jul 2024

Publication Type: Journal

Bringing Communities Together: Mapping the Investigation-Study-Assay-Model (ISA) to Fast Healthcare Interoperability Resources (FHIR).

Abstract (Expand)

Adhering to FAIR principles (findability, accessibility, interoperability, reusability) ensures sustainability and reliable exchange of data and metadata. Research communities need common infrastructures … and information models to collect, store, manage and work with data and metadata. The German initiative NFDI4Health created a metadata schema and an infrastructure integrating existing platforms based on different information models and standards. To ensure system compatibility and enhance data integration possibilities, we mapped the Investigation-Study-Assay (ISA) model to Fast Healthcare Interoperability Resources (FHIR). We present the mapping in FHIR logical models, a resulting FHIR resources' network and challenges that we encountered. Challenges mainly related to ISA's genericness, and to different structures and datatypes used in ISA and FHIR. Mapping ISA to FHIR is feasible but requires further analyses of example data and adaptations to better specify target FHIR elements, and enable possible automatized conversions from ISA to FHIR.

Authors: S. A. I. Klopfenstein, J. Sass, C. N. Vorisek, F. Jorczik, C. O. Schmidt, M. Lobe, M. Golebiewski, H. Abaza, S. Thun

Date Published: 25th Jan 2024

Publication Type: Journal

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

Abstract (Expand)

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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