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

Ten Simple Rules for FAIR Sharing of Experimental and Clinical Data with the Modeling Community

Abstract (Expand)

Science continues to become more interdisciplinary and to involve increasingly complex data sets. Many projects in the biomedical and health-related sciences follow or aim to follow the principles of …rinciples of FAIR data sharing, which has been demonstrated to foster collaboration, to lead to better research outcomes, and to help ensure reproducibility of results. Data generated in the course of biomedical and health research present specific challenges for FAIR sharing in the sense that they are heterogeneous and highly sensitive to context and the needs of protection and privacy. Data sharing must respect these features without impeding timely dissemination of results, so that they can contribute to time-critical advances in medical therapy and treatment. Modeling and simulation of biomedical processes have become established tools, and a global community has been developing algorithms, methodologies, and standards for applying biomedical simulation models in clinical research. However, it can be difficult for clinician scientists to follow the specific rules and recommendations for FAIR data sharing within this domain. We seek to clarify the standard workflow for sharing experimental and clinical data with the simulation modeling community. By following these recommendations, data sharing will be improved, collaborations will become more effective, and the FAIR publication and subsequent reuse of data will become possible at the level of quality necessary to support biomedical and health-related sciences.

Authors: Matthias König, Jan Grzegorzewski, Martin Golebiewski, Henning Hermjakob, Mike Hucka, Brett Olivier, Sarah Keating, David Nickerson, Falk Schreiber, Rahuman Sheriff, Dagmar Waltemath

Date Published: 19th Nov 2021

Publication Type: Journal

FAIRDOMHub: a repository and collaboration environment for sharing systems biology research

Abstract

Not specified

Authors: Katherine Wolstencroft, Olga Krebs, Jacky L. Snoep, Natalie J. Stanford, Finn Bacall, Martin Golebiewski, Rostyk Kuzyakiv, Quyen Nguyen, Stuart Owen, Stian Soiland-Reyes, Jakub Straszewski, David D. van Niekerk, Alan R. Williams, Lars Malmström, Bernd Rinn, Wolfgang Müller, Carole Goble

Date Published: 3rd Jan 2017

Publication Type: Journal

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