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 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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Format: | artículo biblioteca |
Language: | English |
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BioMed Central
2022-03-22
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Subjects: | FAIR data, Rare disease, Interoperability, Linked data, Data transformation, Semantic web, Ontologies, Common data elements, Disease registries, |
Online Access: | http://hdl.handle.net/20.500.12792/6184 http://hdl.handle.net/10261/289592 |
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dig-inia-es-10261-2895922023-02-16T14:54:29Z 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. Alarcón Moreno, Pablo Benis, Nirupama Cornet, Ronald dos Santos Vieira, Bruna Michel Dumontier, Michel Bernabé, César Henrique Jacobsen, Annika Le Cornec, Clémence M. A. Prieto Godoy, Mario Queralt-Rosinach, Núria Schultze Kool, Leo J. Swertz, Morris A. van Damme, Philip van der Velde, K. Joer Lalout, Nawel Zhang, Shuxin Roos, Marco FAIR data Rare disease Interoperability Linked data Data transformation Semantic web Ontologies Common data elements Disease registries 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. 2023-02-16T12:21:49Z 2023-02-16T12:21:49Z 2022-03-22 artículo Journal of Biomed Semant 13 (9) (2022) 2041-1480 http://hdl.handle.net/20.500.12792/6184 http://hdl.handle.net/10261/289592 10.1186/s13326-022-00264-6 en open BioMed Central |
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FAIR data Rare disease Interoperability Linked data Data transformation Semantic web Ontologies Common data elements Disease registries FAIR data Rare disease Interoperability Linked data Data transformation Semantic web Ontologies Common data elements Disease registries |
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FAIR data Rare disease Interoperability Linked data Data transformation Semantic web Ontologies Common data elements Disease registries FAIR data Rare disease Interoperability Linked data Data transformation Semantic web Ontologies Common data elements Disease registries Kaliyaperumal, Rajaram Wilkinson, Mark D. Alarcón Moreno, Pablo Benis, Nirupama Cornet, Ronald dos Santos Vieira, Bruna Michel Dumontier, Michel Bernabé, César Henrique Jacobsen, Annika Le Cornec, Clémence M. A. Prieto Godoy, Mario Queralt-Rosinach, Núria Schultze Kool, Leo J. Swertz, Morris A. van Damme, Philip van der Velde, K. Joer 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 |
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 |
artículo |
topic_facet |
FAIR data Rare disease Interoperability Linked data Data transformation Semantic web Ontologies Common data elements Disease registries |
author |
Kaliyaperumal, Rajaram Wilkinson, Mark D. Alarcón Moreno, Pablo Benis, Nirupama Cornet, Ronald dos Santos Vieira, Bruna Michel Dumontier, Michel Bernabé, César Henrique Jacobsen, Annika Le Cornec, Clémence M. A. Prieto Godoy, Mario Queralt-Rosinach, Núria Schultze Kool, Leo J. Swertz, Morris A. van Damme, Philip van der Velde, K. Joer Lalout, Nawel Zhang, Shuxin Roos, Marco |
author_facet |
Kaliyaperumal, Rajaram Wilkinson, Mark D. Alarcón Moreno, Pablo Benis, Nirupama Cornet, Ronald dos Santos Vieira, Bruna Michel Dumontier, Michel Bernabé, César Henrique Jacobsen, Annika Le Cornec, Clémence M. A. Prieto Godoy, Mario Queralt-Rosinach, Núria Schultze Kool, Leo J. Swertz, Morris A. van Damme, Philip van der Velde, K. Joer Lalout, Nawel Zhang, Shuxin Roos, Marco |
author_sort |
Kaliyaperumal, Rajaram |
title |
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_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_sort |
semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data |
publisher |
BioMed Central |
publishDate |
2022-03-22 |
url |
http://hdl.handle.net/20.500.12792/6184 http://hdl.handle.net/10261/289592 |
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