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

Abstract

The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or 'ontologies'. Unfortunately, the very success of this approach has led to a proliferation of ontologies, which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium is pursuing a strategy to overcome this problem. Existing OBO ontologies, including the Gene Ontology, are undergoing coordinated reform, and new ontologies are being created on the basis of an evolving set of shared principles governing ontology development. The result is an expanding family of ontologies designed to be interoperable and logically well formed and to incorporate accurate representations of biological reality. We describe this OBO Foundry initiative and provide guidelines for those who might wish to become involved.In the search for what is biologically and clinically significant in the swarms of data being generated by today's high-throughput technologies, a common strategy involves the creation and analysis of 'annotations' linking primary data to expressions in controlled, structured vocabularies, thereby making the data available to search and to algorithmic processing 1 . The most successful such endeavor, measured both by numbers of users and by reach across species and granularities, is the Gene Ontology (GO) 2 . There exist over 11 million annotations relating gene products described in the UniProt, Ensembl and other databases to terms in the GO3, of which half a million have been manually verified by specialist curators in different modelorganism communities on the basis of the analysis of experimental results reported in 52,000 scientific journal articles (http://www.ebi.ac.uk/GOA/). Data related to some 180,000 genes have been manually annotated in this way, an endeavor now being refined and systematized within the Reference Genome Project (US National Institutes of Health National Human Genome Research Institute grant 2P41HG002273-07), which will provide comprehensive GO annotations for both the human genome and a representative set of model-organism genomes in support of research on the primary molecular systems affecting human health. From retrospective mapping to prospective standardizationThe domain of molecular biology is marked by the availability of large amounts of well defined data that can be used without restriction as inputs to algorithmic processing. In the clinical domain, by contrast, only limited amounts of data are available for research purposes, and these still consist overwhelmingly of natural language text. Even where more systematic clinical data are available, the use of local coding schemes means that these data do not cumulate in ways useful to research 4 . One approach to solving this problem is the Unified Medical Language System (UMLS) 5 , a compendium of some 100 source vocabularies combined through a process of...

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“…There are over 11 million annotations relating gene products described in research databases to terms in the GO. Research information regarding approximately 180,000 genes has been tagged using G0 [41].…”

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“…In the practice of ontology engineering, it does have an impact and, based on a literature review and survey [5], the different types of purposes can be summarised as follows: A. Ontology-based data access through linking data to ontologies [6,5]; B. Data(base) integration, most notably the strand of applications initiated by the Gene Ontology Consortium and a successor, the OBO Foundry [7,8]; C. Structured controlled vocabulary to link database records and navigate across databases on the Internet, also known as 'linked data'; D. Using it as part of scientific discourse and advancing research at a faster pace [4,9], including experimental ontologies in a scientific discipline and usage in computing and engineering to build prototype software; E. As full-fledged discipline "Ontology (Science)" [10], where an ontology is a formal, logic-based, representation of a scientific theory; F. Coordination and integration of Web Services; G. Tutorial ontologies to learn modelling in the ontology development environment (e.g., the wine and pizza ontologies). A real caveat with choosing explicitly for a specific goal is that a few years after initial development of the ontology, it may get its own life and be used for other purposes than the original scope.…”

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“…The problem with existing inter-ontology mappings is that they are usually not very comprehensive. For instance, the mapping between PO and GO provided by the OBO Foundry [19] consists of only 137 relationships between the sub-ontologies Biological Process and Plant Structure. A notable exception to this lack of coverage are the inter-ontology mappings in GO itself, where the sub-ontologies Molecular Function and Biological Process are richly inter-linked.…”