Evidence map›Paper›PMID 35292119›Full record

ArticleJournal of biomedical semantics2022

Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data.

Rajaram Kaliyaperumal, Mark D Wilkinson, Pablo Alarcón Moreno, Nirupama Benis, Ronald Cornet, Bruna Dos Santos Vieira, Michel Dumontier, César Henrique Bernabé, Annika Jacobsen, Clémence M A Le Cornec and 9 more

Abstract read
In one paragraph

Article in Journal of biomedical semantics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
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  11. Article
  12. Article
  13. The use of foundational ontologies in biomedical research.Journal of biomedical semantics · 2023
    Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. One Digital Health for more FAIRness.Methods of information in medicine · 2022
    Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Rajaram Kaliyaperumal *Leiden University Medical Center, Leiden, The Netherlands.
Mark D Wilkinson *Departamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Centro de Biotecnología y Genómica de Plantas (CBGP), Universidad Politécnica de Madrid (UPM), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Pozuelo de Alarcón, Madrid, ES, Spain. mark.wilkinson@upm.es.ORCID 0000-0001-6960-357X
Pablo Alarcón MorenoDepartamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Centro de Biotecnología y Genómica de Plantas (CBGP), Universidad Politécnica de Madrid (UPM), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Pozuelo de Alarcón, Madrid, ES, Spain.
Nirupama BenisDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands.
Ronald CornetDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands.
Bruna Dos Santos VieiraDepartment of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
Michel DumontierInstitute of Data Science, Paul-Henri Spaaklaan 1, Maastricht University, 6229EN, Maastricht, The Netherlands.
César Henrique BernabéLeiden University Medical Center, Leiden, The Netherlands.
Annika JacobsenLeiden University Medical Center, Leiden, The Netherlands.
Clémence M A Le CornecDivision of Paediatric Nephrology, Centre for Paediatrics and Adolescent Medicine, University of Heidelberg, Heidelberg, Germany.
Mario Prieto GodoyDepartamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Centro de Biotecnología y Genómica de Plantas (CBGP), Universidad Politécnica de Madrid (UPM), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Pozuelo de Alarcón, Madrid, ES, Spain.
Núria Queralt-RosinachLeiden University Medical Center, Leiden, The Netherlands.
Leo J Schultze KoolDepartment of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
Morris A SwertzUniversity of Groningen and University Medical Center Groningen, Genomics Coordination Center and Department of Genetics, Antonius Deusinglaan 1, 9713, AV, Groningen, The Netherlands.
Philip van DammeDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands.
K Joeri van der VeldeUniversity of Groningen and University Medical Center Groningen, Genomics Coordination Center and Department of Genetics, Antonius Deusinglaan 1, 9713, AV, Groningen, The Netherlands.
Nawel LaloutCentre for Molecular and Biomolecular Informatics, Radboud University Medical Center, Nijmegen, The Netherlands.
Shuxin ZhangDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands.
Marco RoosLeiden University Medical Center, Leiden, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe European Platform on Rare Disease Registration (EU RD Platform) aims to address the fragmentation of European rare disease (RD) patient data, scattered among hundreds of independent and non-coordinating registries, by establishing standards for integration and interoperability. The first practical output of this effort was a set of 16 Common Data Elements (CDEs) that should be implemented by all RD registries. Interoperability, however, requires decisions beyond data elements - including data models, formats, and semantics. Within the European Joint Programme on Rare Diseases (EJP RD), we aim to further the goals of the EU RD Platform by generating reusable RD semantic model templates that follow the FAIR Data Principles.

resultsThrough a team-based iterative approach, we created semantically grounded models to represent each of the CDEs, using the SemanticScience Integrated Ontology as the core framework for representing the entities and their relationships. Within that framework, we mapped the concepts represented in the CDEs, and their possible values, into domain ontologies such as the Orphanet Rare Disease Ontology, Human Phenotype Ontology and National Cancer Institute Thesaurus. Finally, we created an exemplar, reusable ETL pipeline that we will be deploying over these non-coordinating data repositories to assist them in creating model-compliant FAIR data without requiring site-specific coding nor expertise in Linked Data or FAIR.

conclusionsWithin the EJP RD project, we determined that creating reusable, expert-designed templates reduced or eliminated the requirement for our participating biomedical domain experts and rare disease data hosts to understand OWL semantics. This enabled them to publish highly expressive FAIR data using tools and approaches that were already familiar to them.

Indexed as

Common Data ElementsRare DiseasesHumansRegistriesSemanticsWorkflowCommon data elementsData transformationDisease registriesFAIR dataInteroperabilityLinked dataOntologiesRare diseaseSemantic web

Identifiers

PMID35292119
PMCPMC8922780

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.