Cargando…

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

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 f...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922780/
https://www.ncbi.nlm.nih.gov/pubmed/35292119
http://dx.doi.org/10.1186/s13326-022-00264-6
_version_ 1784669563338620928
author 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
author_facet 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
author_sort Kaliyaperumal, Rajaram
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8922780
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-89227802022-03-22 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 J Biomed Semantics Research 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. BioMed Central 2022-03-15 /pmc/articles/PMC8922780/ /pubmed/35292119 http://dx.doi.org/10.1186/s13326-022-00264-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
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
Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data
title Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data
title_full Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data
title_fullStr Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data
title_full_unstemmed Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data
title_short Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data
title_sort semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922780/
https://www.ncbi.nlm.nih.gov/pubmed/35292119
http://dx.doi.org/10.1186/s13326-022-00264-6
work_keys_str_mv AT kaliyaperumalrajaram semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT wilkinsonmarkd semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT morenopabloalarcon semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT benisnirupama semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT cornetronald semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT dossantosvieirabruna semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT dumontiermichel semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT bernabecesarhenrique semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT jacobsenannika semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT lecornecclemencema semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT godoymarioprieto semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT queraltrosinachnuria semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT schultzekoolleoj semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT swertzmorrisa semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT vandammephilip semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT vanderveldekjoeri semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT laloutnawel semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT zhangshuxin semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata
AT roosmarco semanticmodellingofcommondataelementsforrarediseaseregistriesandaprototypeworkflowfortheirdeploymentoverregistrydata