The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration

By Barry Smith, Michael Ashburner, Cornelius Rosse, J. Bard, W. Bug, Werner Ceusters, Louis J. Goldberg, Karen Eilbeck, A. Ireland, C. Mungall and 8 more. Nature Biotechnology, 2007

2,805 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/74a776fc32153f2306086d8b69bb29fdd8fcad13

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Molecular Biology

Citations in the corpus

ClassyFire: automated chemical classification with a comprehensive, computable taxonomy (2016, background): “The chemical taxonomy and its hierarchical structure provided using the Open Biological and Biomedical Ontologies (OBO) format [33], which may help with its integration with respect to semantic technology approaches.”
Clinical diagnostics in human genetics with semantic similarity searches in ontologies. (2009, positive): “After the success of Gene Ontology,(11) ontologies have been developed for many fields in biomedical science.(12) We developed the HPO in order to provide a standardized vocabulary of phenotypic abnormalities encountered in human disease.”
Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies (2017, methodology): “[5] Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, Goldberg LJ, Eilbeck K, Ireland A, Mungall CJ, Leontis N, Rocca-Serra P, Ruttenberg A, Sansone SA, Scheuermann RH, Shah N, Whetzel PL, Lewis S.”
Deep learning for noise-tolerant RDFS reasoning (2019, methodology): “We investigated some use cases using ontologies from the Open Biological and Biomedical Ontology (OBO) Foundry [93], specifically using the Human Disease Ontology [94].”
The Plant Ontology as a Tool for Comparative Plant Anatomy and Genomic Analyses (2012, methodology): “There are currently >100 ontology projects using BFO as common upper-level framework, including the ontologies within the OBO Foundry (Grenon et al. 2004, Arp and Smith 2008).”
BioPortal: ontologies and integrated data resources at the click of a mouse (2009, methodology): “Users can ﬁlter ontologies by group, such as all OBO Foundry ontologies (4) or caBIG ontologies (e.g. http:// bioportal.bioontology.org/?ﬁlter=OBOFoundry).”
Uberon, an integrative multi-species anatomy ontology (2012, background): “We believe that Uberon meets the current need for an integrative cross-species anatomy ontology amongst the OBO Foundry suite [66].”
Standardized description of scientific evidence using the Evidence Ontology (ECO) (2014, background): “Issues affecting ECO and general improvements A number of criticisms of ECO (revision 19) were noted at an OBO Foundry (6) workshop held in 2009 (http:// www.obofoundry.org/wiki/index.php/OBO_Foundry_Wo rkshop_2009) including (i) inconsistent mixing of ‘is_a’ relations based on experimental methodol”
Finding Our Way through Phenotypes (2015, background): “The prospects of computable phenotype data have slowly improved over the past several years, with several domain-specific initiatives yielding results [21,30,32,94,95] and a larger framework of data integration resources [96–100].”
A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog (2018, background): “perform more powerful and precise ancestry-related queries [20].”
Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement (2013, background): “…the development of phenotyping strategies will almost certainly mirror innovations in genotyping technology that have occurred over the last 20 years, characterized by increasing automation and throughput (Rafalski and Tingey 1993; Perlin et al. 1995; Sheffield et al. 1995; Weber and Broman 2001).”
WikiPathways: Pathway Editing for the People (2008, background): “This trend is most apparent with the growing number of open-access journals (see the Directory of Open Access Journals at http:// www.doaj.org/), public databases [2], and data exchange formats [3] and ontologies [4].”
The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data (2013, methodology): “Since its initial publication in 2008, the project has grown in terms of coverage, complexity, usage and cross-linking with other projects, especially from the Open Biological and Biomedical Ontologies (OBO) Foundry (7).”
PubChemRDF: towards the semantic annotation of PubChem compound and substance databases (2015, methodology): “The ontologies ChEBI, CHEMINF, SIO, and UO are interfaced by the NIH Roadmap National Center for Bio-medical Ontology (NCBO) through its BioPortal [38], and comply with an evolving set of shared principles established by the Open Biomedical Ontologies (OBO) foundry [39].”
Surgical data science – from concepts toward clinical translation (2020, background): “Most notable is the family of ontologies gathered under the OpenBiological and Biomedical Ontologies (OBO) Foundry (Smith et al., 2007), which cover a wide array of topics from the biomedical domain and share the Basic Formal Ontology (BFO) (Grenon and Smith, 2004) as a common top-level ontology.”
Ontological realism: A methodology for coordinated evolution of scientific ontologies (2010, neutral): “…a trafﬁc law, which has been executed with some success and, we believe, some measurable beneﬁt by the GO and its sister ontologies within the OBO Foundry (Smith et al., 2007), is the law according to which all terms within an ontology should be nouns and noun-phrases that are singular in number .”
Concept annotation in the CRAFT corpus (2012, background): “These ontologies are largely constructed in a community-driven approach, and their developers commit to a common set of attributes including openness, shared syntax, clear versioning, demarcated content, and clear definition [7].”