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Taxonomy is the science of defining and naming groups of biological organisms based on shared characteristics. It uses a hierarchy of increasingly inclusive categories with Latin names. The smallest units of taxonomy, species and genus, are used to assign a formal, taxonomic name to each species in a system. This classification system, referred to as binomial nomenclature, was formalized by Carolus Linnaeus in the 18th century.
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Exploring Metadata Catalogs in Health Care Data Ecosystems: Taxonomy Development Study.

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This study introduces a taxonomy of 20 dimensions and 101 characteristics for designing effective health metadata catalogs (HMDCs) to enhance data sharing in European health care. The findings offer practical guidance for developing FAIR (findable, accessible, interoperable, reusable) health data ecosystems.

Keywords:
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Area of Science:

  • Health Informatics
  • Information Systems Engineering
  • Data Governance

Background:

  • European health care is investing in data ecosystems to leverage increasing health data.
  • Health Metadata Catalogs (HMDCs) are crucial for data allocation, sharing, and use, aiming for FAIR principles.
  • Actionable design knowledge for HMDCs is scarce, hindering development and innovation.

Purpose of the Study:

  • To explore structural design elements of HMDCs.
  • To classify HMDCs using empirical dimensions and characteristics.
  • To provide actionable design knowledge for HMDC development and theory.

Main Methods:

  • A taxonomy-building methodology based on information systems guidelines.
  • Combined inductive and deductive research methods.
  • Systematic literature review (38 articles) and multicase study (17 HMDCs), refined by expert focus groups.

Main Results:

  • An empirically grounded taxonomy of 20 dimensions and 101 characteristics for structuring and classifying FAIR HMDCs.
  • Key design considerations include metadata assets and data security/governance.
  • The taxonomy's relevance is demonstrated through 4 expert-cocreated use cases.

Conclusions:

  • The study provides fundamental, actionable design knowledge for building HMDCs in European health care.
  • Offers guidance for practitioners, scientists, and policymakers in health data ecosystems.
  • Addresses the research gap in actionable HMDC design knowledge.