• Corpus ID: 233261245

FAIRness of openEHR Archetypes and Templates

@inproceedings{Bnisch2019FAIRnessOO,
  title={FAIRness of openEHR Archetypes and Templates},
  author={Caroline B{\"o}nisch and Anneka Sargeant and Antje Wulff and Marcel Parciak and Christian Robert Bauer and Ulrich Sax},
  booktitle={SWAT4HCLS},
  year={2019}
}
Background: The FAIR Data Publishing Group designed 15 principles to quantify the FAIRness of scientific data. By using the FAIR Principles it is possible to make scientific data findable, accessible, interoperable and reusable. This paper checks the FAIRness of openEHR archetypes and templates as formalisms to preserve semantic interoperability in electronic health records. Objectives: Within the semantic framework of the HiGHmed project, the aim is to exchange harmonized data between various… 

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