The Sickle Cell Disease Ontology: recent development and expansion of the universal sickle cell knowledge representation

Abstract

The Sickle Cell Disease (SCD) Ontology (SCDO, https://scdontology.h3abionet.org/) provides a comprehensive knowledge base of SCD management, systems and standardized human and machine-readable resources that unambiguously describe terminology and concepts about SCD for researchers, patients and clinicians. The SCDO was launched in 2016 and is continuously updated in quantity, as well as in quality, to effectively support the curation of SCD research, patient databasing and clinical informatics applications. SCD knowledge from the scientific literature is used to update existing SCDO terms and create new terms where necessary. Here, we report major updates to the SCDO, from December 2019 until April 2021, for promoting interoperability and facilitating SCD data harmonization, sharing and integration across different studies and for retrospective multi-site research collaborations. SCDO developers continue to collaborate with the SCD community, clinicians and researchers to improve specific ontology areas and expand standardized descriptions to conditions influencing SCD phenotypic expressions and clinical manifestations of the sickling process, e.g. thalassemias. Database URL: https://scdontology.h3abionet.org/

Datenstandards für Seltene Erkrankungen

“…Weitere Terminologien und Ontologien mit Krankheitsklassifikationen sind: "National Cancer Institute Thesaurus" (NCIt), "SNOMED CT", "Human Disease Ontology", "ICD-10", "MedGen", spezialisierte Nosologien wie die "Sickle Cell Disease Ontology" und dergleichen mehr [23][24][25][26]. Jede Ressource dient einem bestimmten Zweck und weist unterschiedliche Schwerpunkte sowie Stärken und Schwächen auf.…”

A Novel Tightly Coupled Information System for Research Data Management

“…We reviewed different software that manage ontologies as per the criteria defined in Section 3.1 and we settled on WebProtégé [42] since it has been widely used for ontology management [43][44][45]. We configured and hosted it on our VPN [12].…”

“…These are some quality control checks that can be put in place to improve data quality. We note that standardizing data variables, i.e., ontology alignment, improved data quality and made it easy to fetch data that has a variable name from the entire database Mazandu et al [43].…”

HURON: A Quantitative Framework for Assessing Human Readability in Ontologies

“…Ontologies play a key role in knowledge engineering by providing a common conceptualization of a domain. Ontologies have been successfully applied in different domains, but especially in biology and biomedicine, with different purposes [1][2][3][4][5].…”

“…INTRODUCTIONOntologies play a key role in knowledge engineering by providing a common conceptualization of a domain. Ontologies have been successfully applied in different domains, but especially in biology and biomedicine, with different purposes [1][2][3][4][5].At the time of writing, repositories like BioPortal [6] had more than 1,000 ontologies and both the Open Biological and Biomedical Ontology (OBO) Foundry [7] and the Ontology Lookup Service (OLS) [8] had more than 250 ontologies. The number of ontologies in these repositories is continuously increasing, which demonstrates their relevance and impact.In contrast to other artifacts used in data management systems, such as relational databases, developed specifically for particular applications, ontologies should be created in a standardized way to facilitate their reuse.…”