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https://wiki.nci.nih.gov/display/LexEVS/LexGrid

LexGrid (Lexical Grid) provides support for a distributed network of lexical resources such as terminologies and ontologies via standards-based tools, storage formats, and access/update mechanisms. The Lexical Grid Vision is for a distributed network of terminological resources. It is the foundation of the National Center for Biomedical Ontology BioPortal interface and web-services, and can parse OBO format, as well as other formats such as OWL. Currently, there are many terminologies and ontologies in existence. Just about every terminology has its own format, its own set of tools, and its own update mechanisms. The only thing that most of these pieces have in common with each other is their incompatibility. This makes it very hard to use these resources to their full potential. We have designed the Lexical Grid as a way to bridge terminologies and ontologies with a common set of tools, formats and update mechanisms. The Lexical Grid is: * accessible through a set of common APIs * joined through shared indices * online accessible * downloadable * loosely coupled * locally extendable * globally revised * available in web-space on web-time * cross-linked The realization of this vision requires three interlocking components, which are: * Standards - access methods and formats need to be published and openly available * Tools - standards based tools must be readily available * Content - commonly used terminologies have to be available for access and download Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: LexGrid (RRID:SCR_006627) Copy   

•   Source: SciCrunch Registry

http://www.rightfield.org.uk/

An open-source tool for adding ontology term selection to Excel spreadsheets. It is used by a "Template Creator" to create semantically aware Excel spreadsheet templates. The Excel templates are then reused by Scientists to collect and annotate their data; without any need to understand, or even be aware of, RightField or the ontologies used. For each annotation field, RightField can specify a range of allowed terms from a chosen ontology (subclasses, individuals or combinations). The resulting spreadsheet presents these terms to the users as a simple drop-down list. This reduces the adoption barrier for using community ontologies as the annotation is made by the scientist that generated the data rather than a third party, and the annotation is collected at the time of data collection. RightField is a standalone Java application which uses Apache-POI for interacting with Microsoft documents. It enables users to import Excel spreadsheets, or generate new ones from scratch. Ontologies can either be imported from their local file systems, or from the BioPortal ontology repository. Individual cells, or whole columns or rows can be marked with the required ranges of ontology terms and an individual spreadsheet can be annotated with terms from multiple ontologies.

Proper citation: RightField (RRID:SCR_002649) Copy   

•   Source: SciCrunch Registry

http://www.geneontology.org/

Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.

Proper citation: Gene Ontology (RRID:SCR_002811) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/LIPRO

An ontology that describes the LIPIDMAPS nomenclature classification explicitly using description logics (OWL-DL). Lipid classes are organized hierarchically with the super-classes restricted by generic necessary conditions. More specific necessary conditions are used to define membership requirements for sub classes of lipid according to appropriate functional groups. Lipid research is increasingly integrated within systems level biology such as lipidomics where lipid classification is required before appropriate annotation of chemical functions can be applied.

Proper citation: Lipid Ontology (RRID:SCR_003349) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/APO

A structured controlled vocabulary for the phenotypes of Ascomycete fungi.

Proper citation: Ascomycete Phenotype Ontology (RRID:SCR_003254) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/MMO

An ontology designed to represent the variety of methods used to make qualitative and quantitative clinical and phenotype measurements both in the clinic and with model organisms.

Proper citation: Measurement Method Ontology (RRID:SCR_003373) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/bcgo-ontology/

An application ontology built for the Beta Cell Genomics database aiming to support database annotation, complicated semantic queries, and automated cell type classification. The ontology is developed using Basic Formal Ontology (BFO) as upper ontology, Ontology for Biomedical Investigations (OBI) as ontology framework and integrated subsets of multiple OBO Foundry (candidate) ontologies. Current the BCGO contains 2383 classes including terms referencing to 24 various OBO Foundry ontologies including CL, CLO, UBERON, GO, PRO, UO, etc.

Proper citation: Beta Cell Genomics Ontology (RRID:SCR_003259) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/IDOMAL

An application ontology to cover all aspects of malaria (clinical, epidemiological, biological, etc) as well as the intervention attempts to control it, extending the infectious disease ontology (IDO).

Proper citation: Malaria Ontology (RRID:SCR_003369) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/DDANAT

A structured controlled vocabulary of the anatomy of the slime-mould Dictyostelium discoideum.

Proper citation: Dictyostelium Discoideum Anatomy Ontology (RRID:SCR_003309) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/bco/

Ontology developed as an application ontology as part of the Biocode Commons project whose goal is to support the interoperability of biodiversity data, including data on museum collections, environmental and metagenomic samples, and ecological surveys. It includes consideration of the distinctions between individuals, organisms, voucher specimens, lots, and samples the relations between these entities, and processes governing the creation and use of samples. Within scope as well are properties including collector, location, time, storage environment, containers, institution, and collection identifiers.

Proper citation: Biological Collections Ontology (RRID:SCR_003262) Copy   

•   Source: SciCrunch Registry

http://www.bioontology.org/wiki/index.php/CARO:Main_Page

An ontology developed to facilitate interoperability between existing anatomy ontologies for different species, and to provide a template for building new anatomy ontologies.

Proper citation: Common Anatomy Reference Ontology (RRID:SCR_003296) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CMO

An ontology designed to be used to standardize morphological and physiological measurement records generated from clinical and model organism research and health programs.

Proper citation: Clinical Measurement Ontology (RRID:SCR_003291) Copy   

•   Source: SciCrunch Registry

https://github.com/rsc-ontologies/rsc-cmo

An ontology that describes methods used to collect data in chemical experiments, such as mass spectrometry and electron microscopy; preparing and separating material for further analysis, such as sample ionization, chromatography, and electrophoresis; and synthesizing materials, such as epitaxy and continuous vapor deposition. It also describes the instruments used in these experiments, such as mass spectrometers and chromatography columns. It is intended to be complementary to the Ontology for Biomedical Investigations (OBI).

Proper citation: Chemical Methods Ontology (RRID:SCR_003286) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/FB-CV

A structured controlled vocabulary used for various aspects of annotation by FlyBase. This ontology is maintained by FlyBase for various aspects of annotation not covered, or not yet covered, by other OBO ontologies. If and when community ontologies are available for the domains here covered FlyBase will use them.

Proper citation: FlyBase Controlled Vocabulary (RRID:SCR_003318) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/FYPO

A formal ontology of phenotypes observed in fission yeast that is being developed to support the comprehensive and detailed representation of phenotypes in PomBase, the online fission yeast resource. Its scope is similar to that of the Ascomycete Phenotype Ontology (APO), but FYPO includes more detailed pre-composed terms as well as computable definitions.

Proper citation: Fission Yeast Phenotype Ontology (RRID:SCR_003315) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/popcomm-ontology/

An ontology that models material entities, qualities, and processes related to collections of interacting organisms such as populations and communities. It is taxon neutral, and can be used for any species, including humans. The classes in the PCO are useful for describing evolutionary processes, organismal interactions, and ecological experiments. Practical applications of the PCO include community health care, plant pathology, behavioral studies, sociology, and ecology. The PCO is compliant with the Basic Formal Ontology (BFO) and is designed to be compatible with other OBO Foundry ontologies, such as the Gene Ontology (GO), which covers biological processes, and the Phenotypic Quality Ontology (PATO).

Proper citation: Population and Community Ontology (RRID:SCR_003462) Copy   

•   Source: SciCrunch Registry

http://archive.gramene.org/plant_ontology/ontology_browse.html#eo

A structured controlled vocabulary for the representation of plant environmental conditions.

Proper citation: Plant Environmental Conditions (RRID:SCR_003460) Copy   

•   Source: SciCrunch Registry

http://sig.biostr.washington.edu/projects/fm/

A domain ontology that represents a coherent body of explicit declarative knowledge about human anatomy. It is concerned with the representation of classes or types and relationships necessary for the symbolic representation of the phenotypic structure of the human body in a form that is understandable to humans and is also navigable, parseable and interpretable by machine-based systems. Its ontological framework can be applied and extended to all other species. The description of how the OWL version was generated is in Pushing the Envelope: Challenges in a Frame-Based Representation of Human Anatomy by N. F. Noy, J. L. Mejino, C. Rosse, M. A. Musen: http://bmir.stanford.edu/publications/view.php/pushing_the_envelope_challenges_in_a_frame_based_representation_of_human_anatomy The Foundational Model of Anatomy ontology has four interrelated components: # Anatomy taxonomy (At), # Anatomical Structural Abstraction (ASA), # Anatomical Transformation Abstraction (ATA), # Metaknowledge (Mk), The ontology contains approximately 75,000 classes and over 120,000 terms; over 2.1 million relationship instances from over 168 relationship types link the FMA's classes into a coherent symbolic model.

Proper citation: FMA (RRID:SCR_003379) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/pharmgkb-owl/

An OWL representation of the data in PharmGKB, Comparative Toxicogenomics Database (CTD) and DrugBank and linked to related ontologies: ChEBI ontology, the Human Disease Ontology (DO), the Anatomical Therapeutic Chemical Classification System (ATC) and the Medical Subject Headings Thesaurus (MESH). The combined knowledge base can be exploited using the ELK reasoner.

Proper citation: PharmGKB Ontology (RRID:SCR_003529) Copy   

•   Source: SciCrunch Registry

http://www.oae-ontology.org

Biomedical ontology in the domain of adverse events that aims to standardize adverse event annotation, integrate various adverse event data, and support computer-assisted reasoning. AEO is a community-based ontology. Its development follows the OBO Foundry principles.

Proper citation: Ontology of Adverse Events (RRID:SCR_003428) Copy   

•   Source: SciCrunch Registry