OBO Foundry in 2021: operationalizing open data principles to evaluate ontologies

Abstract

Biological ontologies are used to organize, curate and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies (OBO) Foundry was created to address this by facilitating the development, harmonization, application and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here, we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable, federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data Findable, Accessible, Interoperable, and Reusable (FAIR). Database URL http://obofoundry.org/

Assessing the Need for Semantic Data Integration for Surgical Biobanks—A Knowledge Representation Perspective

“…These entities are sorted into the resource domain, policy domain, and medical domain. In addition, we provide a list of OBO Foundry [ 31 , 32 ] ontologies that provide a semantically rich representation of entities in those domains. This analysis allows for correct modeling of the inter-domain relationships to ensure cross-domain interoperability.…”

“…RDF data can be annotated and used along with domain descriptions provided in the Web Ontology Language (OWL) [ 30 ]. We are using RDF representations and OWL ontologies following the methodology described by Smith and Ceusters [ 24 ] and the best-practice principles of the OBO Foundry [ 31 , 32 ].…”

Chemical reaction network knowledge graphs: the OntoRXN ontology

“…While specific areas of knowledge require specific ontologies, these (and their corresponding KGs) may be bridged by stating equivalencies between their common elements. Regarding scientific data, ontologies have been widely adopted in biology and biomedicine [ 11 – 13 ], but are not yet as common in other fields like Chemistry. Among the existing chemical ontologies, for which a recent review was carried out by Pachl et al [ 14 ], we may highlight ChEBI, for molecules of biological interest [ 15 ], CHMO, for the formalization of methods in experimental chemistry [ 16 ], RXNO, for conceptualizing chemical reactions [ 17 ] or OntoKin [ 18 ], for kinetic studies on mechanisms.…”

A decade of GigaScience: 10 years of the evolving genomic and biomedical standards landscape

“…The Open Biological and Biomedical Ontologies Foundry's establishment of common principles for development, sharing, and reuse of biomedical terms demonstrates the efforts of communities tackling a common problem [ 6 ]. These early efforts, such as anatomy terms by the Foundation Model of Anatomy, phenotypes by Phenotype and Trait Ontology, diseases in the Human Disease Ontology, and chemicals in Chemical Entities of Biological Interest, established broadly used resources.…”