Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Sustainable implementation of practice-based research networks in primary care: a qualitative process evaluation of the Bavarian Research Practice Network (BayFoNet).

BMC primary care·2026
Same author

FAIR in practice: minimum metadata schema for bioinformatics analytics by machines.

Journal of biomedical semantics·2026
Same author

[Training conditions in postgraduate family medicine training in Bavaria and the role of the Competence Center: A comparative cross-sectional study].

Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen·2026
Same author

Work-life integration in interprofessional general practice collaboration: a qualitative exploration of different trends among Bavarian general practitioners.

BMJ open·2026
Same author

The medical competency training "climate-sensitive health counseling" - an interdisciplinary approach in planetary health education.

GMS journal for medical education·2026
Same author

[Gender differences in the willingness to transition to interprofessional general practice teams].

Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))·2026

Related Experiment Video

Updated: Feb 17, 2026

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
11:18

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

Published on: January 22, 2011

16.5K

Preparing Data at the Source to Foster Interoperability across Rare Disease Resources.

Marco Roos1, Estrella López Martin2, Mark D Wilkinson3

  • 1BioSemantics group, Human Genetics Department, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands. m.roos@lumc.nl.

Advances in Experimental Medicine and Biology
|December 8, 2017
PubMed
Summary

Integrating rare disease data globally is crucial for research. This study introduces a method using common data elements and biomedical ontologies to overcome challenges in data retrieval and analysis.

Keywords:
Data integrationFAIR approachLinkable dataOntologiesSemantic modelStandardization

More Related Videos

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.4K
Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

10.5K

Related Experiment Videos

Last Updated: Feb 17, 2026

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
11:18

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

Published on: January 22, 2011

16.5K
In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

14.4K
Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

10.5K

Area of Science:

  • Bioinformatics
  • Medical Informatics
  • Rare Disease Research

Background:

  • Combining distributed, heterogeneous global data is vital for rare disease research.
  • Methodological, representational, and automation challenges hinder data integration.
  • Biomedical ontologies are essential for computer-aided information retrieval and analysis.

Purpose of the Study:

  • To present an approach for preparing rare disease data for integration.
  • To apply a global standard for computer-readable data and knowledge.
  • To address domain-relevant requirements like data access control and source independence.

Main Methods:

  • Utilizing common data elements for standardization.
  • Applying ontological codes for semantic interoperability.
  • Ensuring computer-readable data formats for analysis.
  • Developing an approach that respects data access controls and source independence.

Main Results:

  • A standardized method for preparing rare disease data for integration was developed.
  • The approach facilitates the use of common data elements and ontological codes.
  • The method supports controlled data access and source independence.
  • The prepared data can be integrated into computational workflows and data platforms.

Conclusions:

  • The presented approach enables effective integration of heterogeneous rare disease data.
  • Biomedical ontologies and standardized data elements are key to overcoming integration challenges.
  • This facilitates enhanced rare disease research through improved data accessibility and analysis.