OBO Foundry

Last updated
OBO Foundry
FocusImprovent of biomedical ontologies
Members
27
Key people
 Suzanna Lewis, Barry Smith, Michael Ashburner
Website obofoundry.org

The Open Biological and Biomedical Ontologies (OBO) Foundry is a group of people dedicated to build and maintain ontologies related to the life sciences. [1] The OBO Foundry establishes a set of principles for ontology development for creating a suite of interoperable reference ontologies in the biomedical domain. Currently, there are more than a hundred ontologies that follow the OBO Foundry principles.

Contents

The OBO Foundry effort makes it easier to integrate biomedical results and carry out analysis in bioinformatics. It does so by offering a structured reference for terms of different research fields and their interconnections (ex: a phenotype in a mouse model and its related phenotype in zebrafish). [2]

Introduction

The Foundry initiative aims at improving the integration of data in the life sciences. One approach to integration is the annotation of data from different sources using controlled vocabularies. Ideally, such controlled vocabularies take the form of ontologies, which support logical reasoning over the data annotated using the terms in the vocabulary.

The formalization of concepts in the biomedical domain is especially known via the work of the Gene Ontology Consortium, a part of the OBO Foundry. This has led to the development of certain proposed principles of good practice in ontology development, which are now being put into practice within the framework of the Open Biomedical Ontologies consortium through its OBO Foundry initiative. OBO ontologies form part of the resources of the National Center for Biomedical Ontology, where they form a central component of the NCBO's BioPortal.

Open Biological and Biomedical Ontologies

The Open Biological and Biomedical Ontologies (OBO; formerly Open Biomedical Ontologies) is an effort to create ontologies (controlled vocabularies) for use across biological and medical domains. A subset of the original OBO ontologies has started the OBO Foundry, which leads the OBO efforts since 2007. [1]

The creation of OBO in 2001 was largely inspired by the efforts of the Gene Ontology project. [3] OBO forms part of the resources of the U.S. National Center for Biomedical Ontology (NCBIO) and a central element of the NCBO's BioPortal. It is an initiative led by the OBO Foundry.

Rules for participation

The OBO Foundry is open to participations of any interested individuals. Ontologies that intend to be officially part of the OBO Foundry have to adhere to the OBO principles and pass a series of reviews done by the members, when "the Foundry coordinators serve as analogs of journal editors". [1] There are ontologies that follow OBO principles but are not officially part of OBO, such as eagle-i's Reagent Application Ontology. [4] and the Animals in Context Ontology. [5]

An integration into OBO of the OntoClean's theory of rigidity has been proposed as a step to standardize candidate ontologies. This integration would make it easier to develop software to automatically check candidates. [6]

Tools

The OBO Foundry community is also dedicated to developing tools to facilitate creating and maintaining ontologies. Most ontology developers in OBO use the Protégé ontology editor and the Web Ontology Language (OWL) for building ontologies. To facilitate command line management of ontologies in a Protégé- and OWL-compatible format, the OBO Foundry has developed the tool ROBOT (ROBOT is an OBO Tool). ROBOT aggregates functions for routine tasks in ontology development, is open source, and can be used either via the command line or as a library for any language on the Java Virtual Machine. [7]

Other tool related to the OBO effort is OBO-Edit, [8] an ontology editor and reasoner funded by the Gene Ontology Consortium. There are also plugins for OBO-Edit which facilitate the development of ontologies, such as the semi-automatic ontology generator DOG4DAG. [9]

The OBO file format

The OBO file format is a biology-oriented language for building ontologies. It is based on the principles of Web Ontology Language (OWL).

As a community effort, standard common mappings have been created for lossless roundtrip transformations between Open Biomedical Ontologies (OBO) format and OWL. [10] [11] The research contains methodical examination of each of the constructs of OBO and a layer cake for OBO, similar to the Semantic Web stack. [12]

OBO Foundry Ontologies

The initial set of OBO Foundry ontologies was composed by mature ontologies (such as the Gene Ontology, GO, and the Foundational Model of Anatomy, FMAO), by mergers of previously existing ontologies (ex: the Cell Ontology, [13] CL, formed from different dedicated ontologies, [14] [15] and related parts on GO and FMAO) and by development of new ontologies based on its principles. [16]

The original set of ontologies also included the Zebrafish Anatomical Ontology [17] (a part of the Zebrafish Information Network), the CheBI ontology, the Disease Ontology, the Plant Ontology, the Sequence Ontology, the Ontology for Biomedical Investigations and the Protein Ontology. [16]

The number of ontologies in OBO has grown to the order of hundreds, and they are gathered in the list of OBO Foundry ontologies.

OBO Foundry and Wikidata

A number of different OBO Foundry ontologies have also been integrated to the Wikidata knowledge graph. [18] [19] This has led to the integration of OBO structured ontologies to data from other, non-OBO databases . For example, the integration of the Human Disease Ontology [20] to Wikidata has enabled its link to the description of cell-lines from the resource Cellosaurus. [21] One of the goals of the integration of OBO Foundry to Wikidata has been to lower the barriers for non-ontologists to contribute to and use ontologies. Wikidata is arguably easier to understand and use than the traditional ontology models (which require a high degree of specific expertise). [22]

Principles

Summary of OBO Foundry Principles [23] for development of an OBO-compatible life sciences ontology:

Openness

The ontologies are openly available and have to be released under either the license CC-BY 3.0 or under the public domain (CC0). [24] The openness of the ontologies has enabled, for example, the import of terms from the Gene Ontology (one of the ontologies that follow OBO Principles) to the Wikidata project. [25]

Common format

The ontologies have to be available in a common formal language. In practice, that means that ontologies that are part of the OBO foundry need to describe items unsing the formats OWL/OWL2 or OBO using a RDF/XML syntax to maximize interoperability. [26]

Orthogonality

Mapping from OBO IDs to OBO Unified Resource Identifiers (URIs), unique for each item. Screenshot from 2020-05-08 06-52-55.png
Mapping from OBO IDs to OBO Unified Resource Identifiers (URIs), unique for each item.

Terms should be unique in the OBO space, meaning that each item has a unique ontology prefix (such as CHEBI, GO, PRO) and a local numeric identifier within the ontology. [27] The choice of a numerical ID was made in order to improve maintenance and evolution of the resources. [28] In order to participate in OBO Foundry, ontologies have to be orthogonal and the concepts it models must be unique within OBO, so each concept has a single Uniform Resource Identifier (URI). New ontologies have, then, to reuse work done in other efforts. [28]

Despite the ideal of uniqueness of terms and interoperability, in practice, this is difficult to enforce, leading to the occurrence of term duplication. Furthermore, some ontologies do not reuse terms or even reuse terms inappropriately. [29]

Versioning

Ontologies evolve in time, refining concepts and descriptions according to advances in the knowledge of their specific domains. [30] In order to ensure that new versions are updated, but tools that use older version of the ontologies are still function, OBO enforces a system of versioning systems, with each ontology version receiving a unique identifier, either in the format of a date or a numbering system, and metadata dags. [31]

Scope

The ontologies should have a clearly specified scope (the domain it intends to cover). [32]

Have textual definitions

The ontologies should have textual definitions for each item, in a human-readable way. That means that beside the alphanumeric identification for each item, they should be described in natural language by logical affirmations following the Aristotelian logic in a way that is unique within the ontology. [33]

Standardized relations and the Relation Ontology (RO)

The ontologies should use relations between items from the Relations Ontology (RO). This ensures that different ontologies can integrated seamlessly, which is specially important for logical inference. [34]

The Relation Ontology (RO) is an ontology designed to represent the relationships between different biomedical concepts. [35] It describes rigorously relations like "part_of", "located_in" and "preceded_by" that are reused by many OBO Foundry ontologies.

Documentation

OBO ontologies need to be thoroughly documented. Frequently this is done via GitHub repositories for each specific ontologies (see List of OBO Foundry ontologies). [36]

Plurality of users

The ontologies should be useful for multiple different people, and ontology developers should document the evidence of use. This criterion is important for the review process. Examples of use include linking to terms by other ontologies, use in semantic web projects, use in annotations or other research applications. [37]

Openness to collaborations

The ontologies should be developed in a way that allows collaborations with other OBO Foundry members. [38]

Locus of authority

The ontologies should have one person responsible for the ontology who mediates interaction with the community. [39]

Naming conventions

Naming conventions for OBO ontologies aim at making primary labels unambiguous and unique inside the ontology (and preferably, inside OBO). Labels and synonyms should be written in English, avoiding the use of underscores and camel case. [40] OBO lacks a mechanism for multilingual support, in contrast to Wikidata, which allows labels in different systems. The naming system in OBO is based on a series of surveys at cataloguing naming conventions of current ontologies, as well as discover issues relating to these conventions. [41]

Maintenance

The ontologies should be updated with regards to changes in scientific consensus. The OBO Foundry defines scientific consensus as "multiple publications by independent labs over a year come to the same conclusion, and there is no or limited (<10%) dissenting opinions published in the same time frame." [42]

See also

Related Research Articles

In information science, an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject.

The Gene Ontology (GO) is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species. More specifically, the project aims to: 1) maintain and develop its controlled vocabulary of gene and gene product attributes; 2) annotate genes and gene products, and assimilate and disseminate annotation data; and 3) provide tools for easy access to all aspects of the data provided by the project, and to enable functional interpretation of experimental data using the GO, for example via enrichment analysis. GO is part of a larger classification effort, the Open Biomedical Ontologies, being one of the Initial Candidate Members of the OBO Foundry.

A semantic web service, like conventional web services, is the server end of a client–server system for machine-to-machine interaction via the World Wide Web. Semantic services are a component of the semantic web because they use markup which makes data machine-readable in a detailed and sophisticated way.

<span class="mw-page-title-main">Carole Goble</span> British computer scientist

Carole Anne Goble, is a British academic who is Professor of Computer Science at the University of Manchester. She is principal investigator (PI) of the myGrid, BioCatalogue and myExperiment projects and co-leads the Information Management Group (IMG) with Norman Paton.

<span class="mw-page-title-main">Robert Stevens (scientist)</span>

Robert David Stevens is a professor of bio-health informatics. and former Head of Department of Computer Science at The University of Manchester

Plant ontology (PO) is a collection of ontologies developed by the Plant Ontology Consortium. These ontologies describe anatomical structures and growth and developmental stages across Viridiplantae. The PO is intended for multiple applications, including genetics, genomics, phenomics, and development, taxonomy and systematics, semantic applications and education.

The Ontology for Biomedical Investigations (OBI) is an open-access, integrated ontology for the description of biological and clinical investigations. OBI provides a model for the design of an investigation, the protocols and instrumentation used, the materials used, the data generated and the type of analysis performed on it. The project is being developed as part of the OBO Foundry and as such adheres to all the principles therein such as orthogonal coverage and the use of a common formal language. In OBI the common formal language used is the Web Ontology Language (OWL). As of March 2008, a pre-release version of the ontology was made available at the project's SVN repository.

Basic Formal Ontology (BFO) is a top-level ontology developed by Barry Smith and his associates for the purposes of promoting interoperability among domain ontologies built in its terms through a process of downward population. A guide to building BFO-conformant domain ontologies was published by MIT Press in 2015.

<span class="mw-page-title-main">Ontology engineering</span> Field that studies the methods and methodologies for building ontologies

In computer science, information science and systems engineering, ontology engineering is a field which studies the methods and methodologies for building ontologies, which encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities. In a broader sense, this field also includes a knowledge construction of the domain using formal ontology representations such as OWL/RDF. A large-scale representation of abstract concepts such as actions, time, physical objects and beliefs would be an example of ontological engineering. Ontology engineering is one of the areas of applied ontology, and can be seen as an application of philosophical ontology. Core ideas and objectives of ontology engineering are also central in conceptual modeling.

The Disease Ontology (DO) is a formal ontology of human disease. The Disease Ontology project is hosted at the Institute for Genome Sciences at the University of Maryland School of Medicine.

<span class="mw-page-title-main">Lawrence Hunter</span>

Lawrence E. Hunter is a Professor and Director of the Center for Computational Pharmacology and of the Computational Bioscience Program at the University of Colorado School of Medicine and Professor of Computer Science at the University of Colorado Boulder. He is an internationally known scholar, focused on computational biology, knowledge-driven extraction of information from the primary biomedical literature, the semantic integration of knowledge resources in molecular biology, and the use of knowledge in the analysis of high-throughput data, as well as for his foundational work in computational biology, which led to the genesis of the major professional organization in the field and two international conferences.

The Sequence Ontology (SO) is an ontology suitable for describing biological sequences. It is designed to make the naming of DNA sequence features and variants consistent and therefore machine-readable and searchable.

Suzanna (Suzi) E. Lewis was a scientist and Principal investigator at the Berkeley Bioinformatics Open-source Project based at Lawrence Berkeley National Laboratory until her retirement in 2019. Lewis led the development of open standards and software for genome annotation and ontologies.

Semantic Automated Discovery and Integration (SADI) is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. SADI services utilize Semantic Web technologies at every level of the Web services "stack". Services are described in OWL-DL, where the property restrictions in OWL classes are used to define the properties expected of the input and output data. Invocation of SADI Services is achieved through HTTP POST of RDF data representing OWL Individuals ('instances') of the defined input OWL Class, and the resulting output data will be OWL Individuals of the defined output OWL Class.

DisGeNET is a discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET is one of the largest and comprehensive repositories of human gene-disease associations (GDAs) currently available. It also offers a set of bioinformatic tools to facilitate the analysis of these data by different user profiles. It is maintained by the Integrative Biomedical Informatics (IBI) Group, of the (GRIB)-IMIM/UPF, based at the Barcelona Biomedical Research Park (PRBB), Barcelona, Spain.

The Monarch Initiative is a large scale bioinformatics web resource focused on leveraging existing biomedical knowledge to connect genotypes with phenotypes in an effort to aid research that combats genetic diseases. Monarch does this by integrating multi-species genotype, phenotype, genetic variant and disease knowledge from various existing biomedical data resources into a centralized and structured database. While this integration process has been traditionally done manually by basic researchers and clinicians on a case-by-case basis, The Monarch Initiative provides an aggregated and structured collection of data and tools that make biomedical knowledge exploration more efficient and effective.

Biocuration is the field of life sciences dedicated to organizing biomedical data, information and knowledge into structured formats, such as spreadsheets, tables and knowledge graphs. The biocuration of biomedical knowledge is made possible by the cooperative work of biocurators, software developers and bioinformaticians and is at the base of the work of biological databases.

The Cell Ontology is an ontology that aims at capturing the diversity of cell types in animals. It is part of the Open Biomedical and Biological Ontologies (OBO) Foundry. The Cell Ontology identifiers and organizational structure are used to annotate data at the level of cell types, for example in single-cell RNA-seq studies. It is one important resource in the construction of the Human Cell Atlas.

<span class="mw-page-title-main">Susanna-Assunta Sansone</span> British-Italian data scientist

Susanna-Assunta Sansone is a British-Italian data scientist who is professor of data readiness at the University of Oxford where she leads the data readiness group and serves as associate director of the Oxford e-Research Centre. Her research investigates techniques for improving the interoperability, reproducibility and integrity of data.

References

  1. 1 2 3 Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, et al. (November 2007). "The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration". Nature Biotechnology. 25 (11): 1251–5. doi:10.1038/nbt1346. PMC   2814061 . PMID   17989687.
  2. ↑ Mungall, Christopher J; Gkoutos, Georgios V; Smith, Cynthia L; Haendel, Melissa A; Lewis, Suzanna E; Ashburner, Michael (2010). "Integrating phenotype ontologies across multiple species". Genome Biology. 11 (1): R2. doi: 10.1186/gb-2010-11-1-r2 . ISSN   1465-6906. PMC   2847714 . PMID   20064205.
  3. ↑ Shimoyama, Mary; Dwinell, Melinda; Jacob, Howard (2009-08-05). "Multiple Ontologies for Integrating Complex Phenotype Datasets". Nature Precedings. doi: 10.1038/npre.2009.3554 . ISSN   1756-0357.
  4. ↑ Brush MH, Vasilevsky N, Torniai C, Johnson T, Shaffer C, Haendel M (2011). "Developing a reagent application ontology within the OBO foundry framework". CEUR Workshop Proceedings. 833: 234–236.
  5. ↑ Santamaria SL (2012). Development the Animals in Context ontology (PDF). Proceedings of the International Conference on Biomedical Ontology. Graz.
  6. ↑ Seyed, Patrice, and Stuart C. Shapiro. (2011). Applying Rigidity to Standardizing OBO Foundry Candidate Ontologies (PDF). Proceedings of the International Conference on Biomedical Ontology (CEUR 993).{{cite conference}}: CS1 maint: multiple names: authors list (link)
  7. ↑ Jackson RC, Balhoff JP, Douglass E, Harris NL, Mungall CJ, Overton JA (July 2019). "ROBOT: A Tool for Automating Ontology Workflows". BMC Bioinformatics. 20 (1): 407. doi: 10.1186/s12859-019-3002-3 . PMC   6664714 . PMID   31357927.
  8. ↑ Day-Richter J, Harris MA, Haendel M, Lewis S (August 2007). "OBO-Edit--an ontology editor for biologists". Bioinformatics. 23 (16): 2198–200. doi: 10.1093/bioinformatics/btm112 . PMID   17545183.
  9. ↑ Wächter T, Schroeder M (June 2010). "Semi-automated ontology generation within OBO-Edit". Bioinformatics. 26 (12): i88-96. doi: 10.1093/bioinformatics/btq188 . PMC   2881373 . PMID   20529942.
  10. 1 2 Tirmizi, Syed; Aitken, Stuart; Moreira, Dilvan A; Mungall, Chris; Sequeda, Juan; Shah, Nigam H; Miranker, Daniel P (2011). "Mapping between the OBO and OWL ontology languages". Journal of Biomedical Semantics. 2 (Suppl 1): S3. doi: 10.1186/2041-1480-2-s1-s3 . ISSN   2041-1480. PMC   3105495 . PMID   21388572.
  11. ↑ Golbreich, Christine; Horridge, Matthew; Horrocks, Ian; Motik, Boris; Shearer, Rob (2007), "OBO and OWL: Leveraging Semantic Web Technologies for the Life Sciences", The Semantic Web, Lecture Notes in Computer Science, Springer Berlin Heidelberg, vol. 4825, pp. 169–182, Bibcode:2007LNCS.4825..169G, doi: 10.1007/978-3-540-76298-0_13 , ISBN   978-3-540-76297-3
  12. ↑ Antezana, E.; Egana, M.; De Baets, B.; Kuiper, M.; Mironov, V. (2008). "ONTO-PERL: An API for supporting the development and analysis of bio-ontologies". Bioinformatics. 24 (6): 885–887. doi: 10.1093/bioinformatics/btn042 . PMID   18245124.
  13. ↑ Diehl, Alexander D.; Meehan, Terrence F.; Bradford, Yvonne M.; Brush, Matthew H.; Dahdul, Wasila M.; Dougall, David S.; He, Yongqun; Osumi-Sutherland, David; Ruttenberg, Alan; Sarntivijai, Sirarat; Van Slyke, Ceri E. (2016-07-04). "The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability". Journal of Biomedical Semantics. 7 (1): 44. doi: 10.1186/s13326-016-0088-7 . ISSN   2041-1480. PMC   4932724 . PMID   27377652.
  14. ↑ Bard, Jonathan; Rhee, Seung Y.; Ashburner, Michael (2005-01-14). "An ontology for cell types". Genome Biology. 6 (2): R21. doi: 10.1186/gb-2005-6-2-r21 . ISSN   1474-760X. PMC   551541 . PMID   15693950.
  15. ↑ Kelso, J. (2003-05-12). "eVOC: A Controlled Vocabulary for Unifying Gene Expression Data". Genome Research. 13 (6): 1222–1230. doi:10.1101/gr.985203. ISSN   1088-9051. PMC   403650 . PMID   12799354.
  16. 1 2 Smith, Barry; Ashburner, Michael; Rosse, Cornelius; Bard, Jonathan; Bug, William; Ceusters, Werner; Goldberg, Louis J; Eilbeck, Karen; Ireland, Amelia; Mungall, Christopher J; Leontis, Neocles (November 2007). "The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration". Nature Biotechnology. 25 (11): 1251–1255. doi:10.1038/nbt1346. ISSN   1087-0156. PMC   2814061 . PMID   17989687.
  17. ↑ Van Slyke, Ceri E.; Bradford, Yvonne M.; Westerfield, Monte; Haendel, Melissa A. (2014-02-25). "The zebrafish anatomy and stage ontologies: representing the anatomy and development of Danio rerio". Journal of Biomedical Semantics. 5 (1): 12. doi: 10.1186/2041-1480-5-12 . ISSN   2041-1480. PMC   3944782 . PMID   24568621.
  18. ↑ Waagmeester, Andra; Stupp, Gregory; Burgstaller-Muehlbacher, Sebastian; Good, Benjamin M; Griffith, Malachi; Griffith, Obi L; Hanspers, Kristina; Hermjakob, Henning; Hudson, Toby S; Hybiske, Kevin; Keating, Sarah M (2020-03-17). Rodgers, Peter; Mungall, Chris (eds.). "Wikidata as a knowledge graph for the life sciences". eLife. 9: e52614. doi: 10.7554/eLife.52614 . ISSN   2050-084X. PMC   7077981 . PMID   32180547.
  19. ↑ Turki, Houcemeddine; Shafee, Thomas; Hadj Taieb, Mohamed Ali; Ben Aouicha, Mohamed; Vrandečić, Denny; Das, Diptanshu; Hamdi, Helmi (2019-11-01). "Wikidata: A large-scale collaborative ontological medical database". Journal of Biomedical Informatics. 99: 103292. doi: 10.1016/j.jbi.2019.103292 . ISSN   1532-0464. PMID   31557529.
  20. ↑ Schriml, Lynn M.; Mitraka, Elvira; Munro, James; Tauber, Becky; Schor, Mike; Nickle, Lance; Felix, Victor; Jeng, Linda; Bearer, Cynthia; Lichenstein, Richard; Bisordi, Katharine (2019-01-08). "Human Disease Ontology 2018 update: classification, content and workflow expansion". Nucleic Acids Research. 47 (D1): D955–D962. doi:10.1093/nar/gky1032. ISSN   0305-1048. PMC   6323977 . PMID   30407550.
  21. ↑ "HeLa". www.wikidata.org. Retrieved 2020-05-04.
  22. ↑ Jacobsen, Annika; Waagmeester, Andra; Kaliyaperumal, Rajaram; Stupp, Gregory S.; M. Schriml, Lynn; Thompson, Mark; I. Su, Andrew; Roos, Marco (2018-12-04). "Wikidata as an intuitive resource towards semantic data modeling in data FAIRification". Figshare. doi:10.6084/m9.figshare.7415282.v2.
  23. ↑ "Overview". obofoundry.org. Retrieved 2020-02-06.
  24. ↑ "Open (principle 1)". obofoundry.org. Retrieved 2020-02-06.
  25. ↑ Burgstaller-Muehlbacher S, Waagmeester A, Mitraka E, Turner J, Putman T, Leong J, et al. (2016-01-01). "Wikidata as a semantic framework for the Gene Wiki initiative". Database. 2016: baw015. doi:10.1093/database/baw015. PMC   4795929 . PMID   26989148.
  26. ↑ "Common Format (principle 2)". obofoundry.org. Retrieved 2020-02-06.
  27. ↑ "URI/Identifier Space (principle 3)". obofoundry.org. Retrieved 2020-02-06.
  28. 1 2 Courtot M, Mungall C, Brinkman RR, Ruttenberg A (2010). Building the OBO Foundry-One Policy at a Time. CEURS Proceedings: International Conference on Biomedical Ontologies.
  29. ↑ Ghazvinian A, Noy NF, Musen MA (May 2011). "How orthogonal are the OBO Foundry ontologies?". Journal of Biomedical Semantics. 2 (Suppl 2): S2. doi: 10.1186/2041-1480-2-s2-s2 . PMC   3102891 . PMID   21624157.
  30. ↑ Groß, Anika; Pruski, Cédric; Rahm, Erhard (2016). "Evolution of biomedical ontologies and mappings: Overview of recent approaches". Computational and Structural Biotechnology Journal. 14: 333–340. doi: 10.1016/j.csbj.2016.08.002 . ISSN   2001-0370. PMC   5018063 . PMID   27642503.
  31. ↑ "Versioning (principle 4)". obofoundry.org. Retrieved 2020-02-06.
  32. ↑ "Scope (principle 5)". obofoundry.org. Retrieved 2020-02-06.
  33. ↑ "Textual Definitions (principle 6)". obofoundry.org. Retrieved 2020-02-06.
  34. ↑ "Relations (principle 7)". obofoundry.org. Retrieved 2020-02-06.
  35. ↑ Smith, Barry; Ceusters, Werner; Klagges, Bert; Köhler, Jacob; Kumar, Anand; Lomax, Jane; Mungall, Chris; Neuhaus, Fabian; Rector, Alan L; Rosse, Cornelius (2005). "Relations in biomedical ontologies". Genome Biology. 6 (5): R46. doi: 10.1186/gb-2005-6-5-r46 . PMC   1175958 . PMID   15892874.
  36. ↑ "Documentation (principle 8)". obofoundry.org. Retrieved 2020-02-06.
  37. ↑ "Documented Plurality of Users (principle 9)". obofoundry.org. Retrieved 2020-02-06.
  38. ↑ "Commitment To Collaboration (principle 10)". obofoundry.org. Retrieved 2020-02-06.
  39. ↑ "Locus of Authority (principle 11)". obofoundry.org. Retrieved 2020-02-06.
  40. ↑ "Naming Conventions (principle 12)". obofoundry.org. Retrieved 2020-02-06.
  41. ↑ Schober, Daniel; Smith, Barry; Lewis, Suzanna E; Kusnierczyk, Waclaw; Lomax, Jane; Mungall, Chris; Taylor, Chris F; Rocca-Serra, Philippe; Sansone, Susanna-Assunta (2009). "Survey-based naming conventions for use in OBO Foundry ontology development". BMC Bioinformatics. 10 (1): 125. doi: 10.1186/1471-2105-10-125 . ISSN   1471-2105. PMC   2684543 . PMID   19397794.
  42. ↑ "Maintenance (principle 16)". obofoundry.org. Retrieved 2020-02-06.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.