FAIRifying in Intensive Care: From Raw Data to HDF5 with Semantic Annotation and Data Quality Checks
The heterogeneity of formats and quality levels of intensive care data represents a significant challenge for both patient treatment and scientific research. The introduction of a data format that provides unified access and a rich structure of metadata could enhance data analysis in this area. Therefore, a data structure based on HDF5 is proposed, which divides data into smaller segments and extends the metadata with semantic annotation and data quality indicators.
Authors
- Martin Dugas (ORCID: https://orcid.org/0000-0001-9740-0788)
- Kei W. Müller (ORCID: https://orcid.org/0009-0004-0744-1623)
- Rosa Klotz (ORCID: https://orcid.org/0000-0003-4123-261X)
- K. Schmitt
- Jonas Biehler (ORCID: https://orcid.org/0000-0003-3032-1924)
- Christian Niklas (ORCID: https://orcid.org/0000-0002-8887-0996)
- Jan Larmann (ORCID: https://orcid.org/0000-0003-3365-4572)
- Markus A. Weigand
Institutions
- Heidelberg University (DE)
- RWTH Aachen University (DE)
Publication Details
- Journal
- Studies in health technology and informatics
- Published
- 2025-05-15
- DOI
- https://doi.org/10.3233/shti250421
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00