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Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data.
Kaliyaperumal, Rajaram; Wilkinson, Mark D; Moreno, Pablo Alarcón; Benis, Nirupama; Cornet, Ronald; Dos Santos Vieira, Bruna; Dumontier, Michel; Bernabé, César Henrique; Jacobsen, Annika; Le Cornec, Clémence M A; Godoy, Mario Prieto; Queralt-Rosinach, Núria; Schultze Kool, Leo J; Swertz, Morris A; van Damme, Philip; van der Velde, K Joeri; Lalout, Nawel; Zhang, Shuxin; Roos, Marco.
Afiliación
  • Kaliyaperumal R; Leiden University Medical Center, Leiden, The Netherlands.
  • Wilkinson MD; 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
  • Moreno PA; 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
  • Benis N; Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands.
  • Cornet R; Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands.
  • Dos Santos Vieira B; Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Dumontier M; Centre for Molecular and Biomolecular Informatics, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Bernabé CH; Institute of Data Science, Paul-Henri Spaaklaan 1, Maastricht University, 6229EN, Maastricht, The Netherlands.
  • Jacobsen A; Leiden University Medical Center, Leiden, The Netherlands.
  • Le Cornec CMA; Leiden University Medical Center, Leiden, The Netherlands.
  • Godoy MP; Division of Paediatric Nephrology, Centre for Paediatrics and Adolescent Medicine, University of Heidelberg, Heidelberg, Germany.
  • Queralt-Rosinach N; 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
  • Schultze Kool LJ; Leiden University Medical Center, Leiden, The Netherlands.
  • Swertz MA; Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
  • van Damme P; University of Groningen and University Medical Center Groningen, Genomics Coordination Center and Department of Genetics, Antonius Deusinglaan 1, 9713, AV, Groningen, The Netherlands.
  • van der Velde KJ; Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands.
  • Lalout N; University of Groningen and University Medical Center Groningen, Genomics Coordination Center and Department of Genetics, Antonius Deusinglaan 1, 9713, AV, Groningen, The Netherlands.
  • Zhang S; Centre for Molecular and Biomolecular Informatics, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Roos M; Duchenne Parent Project, Veenendaal, The Netherlands.
J Biomed Semantics ; 13(1): 9, 2022 03 15.
Article en En | MEDLINE | ID: mdl-35292119
ABSTRACT

BACKGROUND:

The 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.

RESULTS:

Through 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.

CONCLUSIONS:

Within 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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedades Raras / Elementos de Datos Comunes Tipo de estudio: Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: J Biomed Semantics Año: 2022 Tipo del documento: Article País de afiliación: Países Bajos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedades Raras / Elementos de Datos Comunes Tipo de estudio: Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: J Biomed Semantics Año: 2022 Tipo del documento: Article País de afiliación: Países Bajos