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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.ncbcs.org/biositemaps/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. Biositemaps represent a mechanism for computational biologists and bio-informaticians to openly broadcast and retrieve meta-data about biomedical data, tools and services (i.e., biomedical resources) over the Internet. All Institutions with an interest in biomedical research can publish a biositemap.rdf file on their Internet site. The technology, developed by the Biositemaps Working Group of the NIH Roadmap National Centers of Biomedical Computing (NCBC), addresses (i) locating, (ii) querying, (iii) composing or combining, and (iv) mining biomedical resources. Each site which intends to contribute to the inventory instantiates a file on its Internet site biositemap.rdf which conforms to a defined RDF schema and uses concepts from the Biomedical Resource Ontology to describe the resources. Each biositemap.rdf file is simply a list of controlled metadata about resources (software tools, databases, material resources) that your organization uses or believes are important to biomedical research. The key enabling technologies are the Information Model (IM) which is the list of metadata fields about each resource (resource_name, description, contact_person, resource_type,...) and the Biomedical Resource Ontology (BRO) which is a controlled terminology for the resource_typeand which is used to improve the sensitivity and specificity of web searches. Biositemaps blend the features of Sitemaps (enabling efficient web-content exploration) and RSS Feeds (a mechanism for wide and effective news dissemination). As a hybrid between Sitemaps and RSS feeds, the Biositemap infrastructure facilitates a decentralized, portable, extensible and computationally tractable generation and consumption of meta-data about existent, revised and new resources for biomedical computation. Web browsers, crawlers and robots can discover, accumulate, process, integrate and deliver Biositemaps content to (human or machine) users in a variety of graphical, tabular, computational formats. Biositemaps content allows such web browsers to pool resource-associated metadata from disparate and diverse sites and present it to the user in an integrated fashion. The Biositemaps protocol provides clues, information and directives for all Biositemap web harvesters that point to the existence and content of such biomedical resources at different sites.

Proper citation: Biositemaps (RRID:SCR_001976) 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://purl.bioontology.org/ontology/GAZ

THIS RESOURCE IS NO LONGER IN SERVICE, documented on April 23, 2014. Description not available.

Proper citation: Gazetteer (RRID:SCR_000473) Copy   

•   Source: SciCrunch Registry

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

Ontology of Cerrado wood plant dynamics to represent the set of concepts about the dynamics, that is, changes over time of the wood vegetation structure, of Cerrado. Ccon describes the main parameters used to measure the changes, such as mortality rate and recruitment rate.

Proper citation: Cerrado concepts and plant community dynamics (RRID:SCR_007174) Copy   

•   Source: SciCrunch Registry

http://fireball.drexelmed.edu/birnlex/OWLdocs/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on April 26, 2011. Lexicon that provides entities for data and database annotation for the BIRN project, covering anatomy, disease, data collection, project management and experimental design. These sources may include complex image databases, such as data from structural and functional magnetic resonance imaging (MRI) on human subjects involved in studies on Alzheimer''s disease or schizophrenia. The BIRNLex is a specialized vocabulary utilized by BIRN scientists in the context of their research, including common terms for neuroanatomy, molecular species, subject information, behavioral and cognitive processes, experimental practice and design, and the associated elements of primary data provenance required for large-scale data integration across disparate experimental studies.The BIRNLex offers well defined terms from several domains of importance to neuroimaging across scales.

Proper citation: BIRNLex (RRID:SCR_007326) Copy   

•   Source: SciCrunch Registry

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

A controlled vocabulary of terms used in Computational Neurosciences to describe models of the nervous system. This first release of CNO is an alpha version and should be further aligned with other ontologies accessible on Bioportal and should be made compliant with the OBO foundry recommendations.

Proper citation: Computational Neuroscience Ontology (RRID:SCR_007289) Copy   

•   Source: SciCrunch Registry

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

Ontology for Solanaceae crop phenotypes and traits, developed in collaboration with the research community, especially for breeder traits of agronomic importance.

Proper citation: Solanaceae Phenotype Ontology (RRID:SCR_007832) Copy   

•   Source: SciCrunch Registry

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

A uniform core set of data elements (whose formal semantics are captured in OWL) for use in a Computer-Based Patient Record (CPR)

Proper citation: Computer-Based Patient Record Ontology (RRID:SCR_007540) Copy   

•   Source: SciCrunch Registry

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

Ontology for the healthcare common procedure coding system.

Proper citation: Healthcare Common Procedure Coding System (RRID:SCR_007598) Copy   

•   Source: SciCrunch Registry

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

An evidence taxonomy for pharmacologic studies that, when combined with a set of inclusion criteria, enable drug experts to specify what their confidence in a drug mechanism assertion would be if it were supported by a specific set of evidence.

Proper citation: Drug Interaction Knowledge Base Ontology (RRID:SCR_007591) Copy   

•   Source: SciCrunch Registry

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

An ontology that describes the Congenital Heart Defects data.

Proper citation: Congenital Heart Defects Ontology (RRID:SCR_007584) Copy   

•   Source: SciCrunch Registry

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

Growth, trait and development ontology for soybean

Proper citation: Soy Ontology (RRID:SCR_007847) Copy   

•   Source: SciCrunch Registry

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

Memorial Sloan-Kettering Cancer Center''s ontology of surgical secondary events (adverse events).

Proper citation: Surgical Secondary Events (RRID:SCR_007894) Copy   

•   Source: SciCrunch Registry

http://bmir.stanford.edu/

Mark Musen''s laboratory studies components for building knowledge-based systems, controlled terminologies and ontologies, and technology for the Semantic Web. For more than two decades, Musen''s group has worked to elucidate reusable building blocks of intelligent systems, and to develop scalable computational architectures for systems with significant applications in biomedicine. Informatics is the study of information: its structure, its communication, and its use. As society becomes increasingly information intensive, the need to understand, create, and apply new methods for modeling, managing, and acquiring information has never been greater especially in biomedicine. BMIR is home to world class scientists and trainees developing cutting-edge ways to acquire, represent, process, and manage knowledge and data related to health, health care, and the biomedical sciences. Our faculty, students, and staff are committed to ensuring the biomedical community is properly equipped for the information age, and believe our efforts will provide the structure for the burgeoning revolution of health care and the biomedical sciences.

Proper citation: Stanford Center for Biomedical Informatics Research (RRID:SCR_005698) Copy   

•   Source: SciCrunch Registry

http://www.clo-ontology.org/

A community-driven ontology that is developed to standardize and integrate cell line information and support computer-assisted reasoning. Its focus is on permanent cell lines from culture collections. Upper ontology structures that frame the skeleton of CLO include Basic Formal Ontology and Relation Ontology. Cell lines contained in CLO are associated with terms from other ontologies such as Cell Type Ontology, NCBI Taxonomy, and Ontology for Biomedical Investigation. A common design pattern for the cell line is used to model cell lines and their attributes, the Jurkat cell line provides ane xample. Currently CLO contains over 36,000 cell line entries obtained from ATCC, HyperCLDB, Coriell, and bymanual curation. The cell lines are derived from 194 cell types, 656 anatomical entries, and 217 organisms. The OWL-based CLO is machine-readable and can be used in various applications. The CLO development has become a community effort with international collaborations. The development consortium includes experts from all over the world: the USA, Europe, and Japan.

Proper citation: Cell Line Ontology (RRID:SCR_005840) Copy   

•   Source: SciCrunch Registry

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

Ontology of clinical terms Version 3 (CTV3) (Read Codes) (Q199): National Health Service National Coding and Classification Centre

Proper citation: Read Codes Clinical Terms Version 3 (RRID:SCR_006055) Copy   

•   Source: SciCrunch Registry

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

Ontology specifically for Randomized Controlled Trials in order to facilitate the production of systematic reviews and metaanalysis.

Proper citation: Randomized Controlled Trials Ontology (RRID:SCR_005992) Copy   

•   Source: SciCrunch Registry

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

An application ontology for the domain of gene transcription regulation. The ontology integrates fragments of GO and MI with data from GOA, IntAct, UniProt, NCBI, KEGG and orthology relations.

Proper citation: Regulation of Transcription Ontology (RRID:SCR_006238) Copy   

•   Source: SciCrunch Registry

http://obi-ontology.org/

An ontology for the description of biological and clinical investigations built with international, collaborative effort. The ontology represents the design of an investigation, the protocols and instrumentation used, the material used, the data generated and the type analysis performed on it. This includes a set of universal terms that are applicable across various biological and technological domains, and domain-specific terms relevant only to a given domain. Currently OBI is being built under the Basic Formal Ontology (BFO). This project was formerly titled the Functional Genomics Investigation Ontology (FuGO) project.

Proper citation: Ontology for Biomedical Investigations (RRID:SCR_006266) Copy   

•   Source: SciCrunch Registry