The Ontology for Biomedical Investigations.

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

Data standards for Omics data: the basis of data sharing and reuse.

To facilitate sharing of Omics data, many groups of scientists have been working to establish the relevant data standards. The main components of data sharing standards are experiment description standards, data exchange standards, terminology standards, and experiment execution standards. Here we provide a survey of existing and emerging standards that are intended to assist the free and open exchange of large-format data.

Survey-based naming conventions for use in OBO Foundry ontology development.

BACKGROUND: A wide variety of ontologies relevant to the biological and medical domains are available through the OBO Foundry portal, and their number is growing rapidly. Integration of these ontologies, while requiring considerable effort, is extremely desirable. However, heterogeneities in format and style pose serious obstacles to such integration. In particular, inconsistencies in naming conventions can impair the readability and navigability of ontology class hierarchies, and hinder their alignment and integration. While other sources of diversity are tremendously complex and challenging, agreeing a set of common naming conventions is an achievable goal, particularly if those conventions are based on lessons drawn from pooled practical experience and surveys of community opinion. RESULTS: We summarize a review of existing naming conventions and highlight certain disadvantages with respect to general applicability in the biological domain. We also present the results of a survey carried out to establish which naming conventions are currently employed by OBO Foundry ontologies and to determine what their special requirements regarding the naming of entities might be. Lastly, we propose an initial set of typographic, syntactic and semantic conventions for labelling classes in OBO Foundry ontologies. CONCLUSION: Adherence to common naming conventions is more than just a matter of aesthetics. Such conventions provide guidance to ontology creators, help developers avoid flaws and inaccuracies when editing, and especially when interlinking, ontologies. Common naming conventions will also assist consumers of ontologies to more readily understand what meanings were intended by the authors of ontologies used in annotating bodies of data.

Debunking minimum information myths: one hat need not fit all.

A recent meeting report published in this journal suggests that the work of the various bodies attempting to improve the quality of articles describing the results of biomedical experimental work has been misunderstood or, at best, misinterpreted. This response is an attempt to set the record straight and ensure that other groups are not discouraged from using these standards or from joining in their further development in either existing or novel areas of research.

Towards interoperable reporting standards for omics data: hopes and hurdles.

BACKGROUND: As the size and complexity of scientific datasets and the corresponding information stores grow, standards for collecting, describing, formatting, submitting and exchanging information are playing an increasingly active role. Several initiatives occupy strategic positions in the international scenario, both within and across domains. However, the job of harmonising reporting standards is still very much a work in progress; both software interoperability and the data integration remain challenging as things stand. RESULTS: The status quo with respect to standardization initiatives is summarized here, with particular emphasis on the motivation for, and the challenges of, ongoing synergistic activities amongst the academic community focused on the creation of truly interoperable standards. CONCLUSIONS: Groups generating standards should engage with ongoing cross-domain activities to simplify the integration of heterogeneous data sets to the greatest possible extent.

The Functional Genomics Experiment model (FuGE): an extensible framework for standards in functional genomics.

The Functional Genomics Experiment data model (FuGE) has been developed to facilitate convergence of data standards for high-throughput, comprehensive analyses in biology. FuGE models the components of an experimental activity that are common across different technologies, including protocols, samples and data. FuGE provides a foundation for describing entire laboratory workflows and for the development of new data formats. The Microarray Gene Expression Data society and the Proteomics Standards Initiative have committed to using FuGE as the basis for defining their respective standards, and other standards groups, including the Metabolomics Standards Initiative, are evaluating FuGE in their development efforts. Adoption of FuGE by multiple standards bodies will enable uniform reporting of common parts of functional genomics workflows, simplify data-integration efforts and ease the burden on researchers seeking to fulfill multiple minimum reporting requirements. Such advances are important for transparent data management and mining in functional genomics and systems biology.

The minimum information about a proteomics experiment (MIAPE).

Both the generation and the analysis of proteomics data are now widespread, and high-throughput approaches are commonplace. Protocols continue to increase in complexity as methods and technologies evolve and diversify. To encourage the standardized collection, integration, storage and dissemination of proteomics data, the Human Proteome Organization's Proteomics Standards Initiative develops guidance modules for reporting the use of techniques such as gel electrophoresis and mass spectrometry. This paper describes the processes and principles underpinning the development of these modules; discusses the ramifications for various interest groups such as experimentalists, funders, publishers and the private sector; addresses the issue of overlap with other reporting guidelines; and highlights the criticality of appropriate tools and resources in enabling 'MIAPE-compliant' reporting.

Standards for reporting bioscience data: a forward look.

Groups representing a number of domains in the life sciences have been developing specifications and resources for the description and transmission of data, including those produced by (high-throughput) omics technologies. Although these developments are individually valuable, there is now a need for coordination to avoid the problem of a multiplicity of competing candidate standards. Three ongoing collaborative projects (FuGE, OBI and MIBBI) offer the promise of support for truly integrated, cross-domain informatics solutions. This article briefly summarizes the status quo with respect to biological and biomedical data standards, and offers an assessment of coming developments.

Progress in standards for reporting omics data.

A number of research groups are generating standard mechanisms and prescriptions for reporting various kinds of biological and biomedical experiments. The motives for this generation include concern about the longevity of data sets (and the robustness of conclusions built upon them), the desire to integrate data from diverse scientific disciplines, and the facility to productively mine accrued data. The pharmaceutical industry continues to play a significant role in the genesis and development of such standards, in conjunction with technology vendors and academia. This review describes the context and nature of the new candidate standards and discusses their relevance to drug discovery and development.

Entering the implementation era: a report on the HUPO-PSI Fall workshop 25-27 September 2006, Washington DC, USA.

Since its conception in April 2002, the Human Proteome Organisation Proteomics Standards Initiative has contributed to the development of community standards for proteomics in a collaborative and very dynamic manner, resulting in the publication and increasing adoption of a number of interchange formats and controlled vocabularies. Repositories supporting these formats are being established or are already operational. In parallel with this, minimum reporting requirement have been developed and are now maturing to the point where they have been submitted for journal publication after prolonged exposure to community-input via the PSI website.

Minimum reporting requirements for proteomics: a MIAPE primer.

Amongst other functions, the Human Proteome Organization's Proteomics Standards Initiative (HUPO PSI) facilitates the generation by the proteomics community of guidelines that specify the appropriate level of detail to provide when describing the various components of a proteomics experiment. These guidelines are codified as the MIAPE (Minimum Information About a Proteomics Experiment) specification, the first modules of which are now finalized. This primer describes the structure and scope of MIAPE, places it in context amongst reporting specifications for other domains, briefly discusses related informatics resources and closes by considering the ramifications for the proteomics community.

The work of the Human Proteome Organisation's Proteomics Standards Initiative (HUPO PSI).

This article describes the origins, working practices and various development projects of the HUman Proteome Organisation's Proteomics Standards Initiative (HUPO PSI), specifically, our work on reporting requirements, data exchange formats and controlled vocabulary terms. We also offer our view of the two functional genomics projects in which the PSI plays a role (FuGE and FuGO), discussing their impact on our process and laying out the benefits we see as accruing, both to the PSI and to biomedical science as a whole as a result of their widespread acceptance.