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Updated: May 24, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

REDCap Ontology Annotation Made Easy (ROME) - A REDCap Module for Simplified Metadata Element Annotation.

Christof Meigen1, Sophie A I Klopfenstein2, Andrea Groselj-Strele3

  • 1Medical Faculty, Leipzig University.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

RECap Ontology annotations Made Easy (ROME) integrates semantic annotation into data collection, enhancing data FAIRness and supporting the European Health Data Space. This tool aids researchers in semantic data stewardship during routine data capture.

Keywords:
Data AnnotationFAIR dataMetadata annotationREDCapTerminology as Topic

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A User-friendly and Powerful R Analysis of Large-scale Datasets

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Last Updated: May 24, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

Area of Science:

  • Biomedical Informatics
  • Data Science
  • Health Data Management

Background:

  • Semantic annotation of study metadata is crucial for FAIR data principles and cross-border health data exchange.
  • Current annotation tools often lack integration into existing data capture workflows, hindering adoption.
  • The European Health Data Space (EHDS) initiative necessitates standardized and interoperable health data.

Purpose of the Study:

  • To introduce REDCap Ontology annotations Made Easy (ROME), a novel tool for embedding semantic annotation directly into the REDCap electronic data capture framework.
  • To address the gap between data annotation needs and practical research workflows.
  • To facilitate FAIR data principles and support EHDS objectives through integrated semantic stewardship.

Main Methods:

  • ROME is developed as an external REDCap module, integrating with the REDCap Online Designer.
  • It enables users to import minimal datasets and search ontologies like SNOMED CT.
  • Answer options are mapped, and projects are harmonized using reusable semantic mappings, with data stored in structured JSON.

Main Results:

  • ROME embeds ontology-based annotation directly into the REDCap design workflow, improving usability for researchers and data managers.
  • It facilitates the mapping of REDCap data elements to standardized medical terminologies.
  • Structured JSON storage ensures machine-readability and interoperability of annotated metadata.

Conclusions:

  • ROME represents a practical solution for integrating semantic annotation into routine data capture, aligning with FAIR data principles.
  • The tool supports the development of the European Health Data Space by promoting semantic data stewardship.
  • Future developments aim to enhance ROME's capabilities with dedicated ontology interfaces and community-driven harmonization efforts.