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Ontolog Forum

Revision as of 06:17, 9 January 2016 by imported>KennethBaclawski (Fix PurpleMediaWiki references)
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Draft of Ontolog Summit 2007 Artifacts Summary

The current version of this summary is at OntologySummit2007_Survey/ArtifactSummary

There is a spreadsheet for the evaluated artifacts at http://spreadsheets2.google.com/ccc?key=p9rmhfgnHSlkyaat5UOrsKg

  • Basic Formal Ontology (BFO)
  • CMC Controlled Vocabularies
    • used in automatic indexing to describe content, then used to generate navigation between related content. We would like to add more advanced semantic relationships so we can 'type' the relationships Karen Loasby
    • References none public
  • CMC model
    • CMC content model is built in Protege, hence the increased likelihood of being called an ontology. Main issues are around over-complexity given the business needs and creation of multiple overlapping models that are inconsistent with each other. Karen Loasby
    • References none public
  • Common Semantic Model (COSMO)
    • Expressiveness OWL + SWRL
    • Structure FORMAL Both structured (5) (rules-based) plus natural language
    • Granularity low
    • Intended Use Semantic integration/interoperability, and natural language understanding
    • Automated Reasoning Yes
    • Prescriptive/descriptive No, promiscuous, loose/descriptive
    • Assessed by: Pat Cassidy, Leo Obrst, Michael Grüninger, Arturo Sanchez, Joe Kopena
  • Construction Specifications Institute (CSI)
    • Specifying by performance requirements was developed in California in the 70s because the state needed A LOT of schools to be built quickly and cheaply. The government defined what they required by a school, local architects and contractors were hired and schools were built in every shape, size, color you can imagine. We need performance requirements for the semantic web. DeborahMacPherson
    • References http://www.csinet.org/s_csi/sec_forums.asp
  • Controlled Health Thesaurus
    • Originally developed to tag CDC web pages to improve search and retrieval. CDC changed web search strategies and the thesaurus is being used by some in CDC to tag internal documents. The structure was changed from a MeSH model to an IS-A taxonomy with the intent to grow to an ontology. Funding was cut. CDC is putting efforts into building 'value sets'. The thesaurus has the potential to be the glue to link the value sets as well as assist with discovery and decision support - if it were funded. Kathy Lesh
    • References http://www.cdc.gov/PhinVSBrowser/StrutsController.do
  • Current Procedural Terminology (CPT)
  • del.icio.us folksonomy
    • Often - for defining interfaces for portals or collaboration spaces - it is said that we need to enable folksonomies rather than create controlled vocabularies like 'ontologies' Lisa Colvin
    • Expressiveness One relation
    • Structure informal
    • Granularity course
    • Intended Use bookmarking
    • Automated Reasoning automated search by various criteria
    • Prescriptive/descriptive neither prescriptive nor descriptive
    • References del.icio.us
    • Assessed by: Tom Gruber ThomasVanderWal
  • DOLCE - D & S
  • DOLCE
  • Dublin Core
    • Metadata elements for describing documents. It is widely used to describe digital materials such as video, sound, image, text, and composite media like web pages. Ken Baclawski
    • Expressiveness low
    • Structure informal
    • Granularity very coarse
    • Intended Use bibliographic entries
    • Automated Reasoning no
    • Prescriptive/descriptive prescriptive
    • References http://dublincore.org/
    • Assessed by: Tom Gruber ThomasVanderWal
  • ebXML Core Components
    • Core Component sue a simple ontology to establish names for business objects. TimMcGrath
  • ebXML Registry Profile for Web Ontology
  • Emergency Data Exchange Language (EDXL) Distribution Element
  • Engineering Math
  • Enterprise Topic Classification Scheme
  • Environmental Data Coding Specification
    • Expressiveness 3
    • Structure 4
    • Granularity Coarse Granularity
    • Intended Use Neutral Translation
    • Automated Reasoning Some Complex Reasoning
    • Prescriptive/descriptive Prescriptive
    • Assessed by: Charles Turnitsa, Doug Holmes
  • ER Model
    • References Data Model Patterns: Conventions of Thought by David Hay
  • FLOWS
  • Friend-of-a-Friend (FOAF)
  • Gene Ontology (GO)
    • The GO project has developed three structured controlled vocabularies (ontologies) that describe gene products in terms of their associated biological processes, cellular components and molecular functions in a species-independent manner. There are three separate aspects to this effort: first, the development and maintenance of the ontologies themselves; second, the annotation of gene products, which entails making associations between the ontologies and the genes and gene products in the collaborating databases; and third, development of tools that facilitate the creation, maintenance and use of ontologies. Ken Baclawski
    • References http://archive.geneontology.org/latest-termdb/go_daily-termdb.rdf-xml.gz http://www.geneontology.org/GO.downloads.ontology.shtml
  • Generalized Upper Model (GUM)
  • Geospatial ML Ontology
    • Expressiveness 4
    • Structure 4
    • Granularity Fine Granularity
    • Intended Use Integration of Data Sets/Models
    • Automated Reasoning Can support Complex Reasoning
    • Prescriptive/descriptive Descriptive
    • Assessed by: Charles Turnitsa, Doug Holmes
  • ICD-9
    • The International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) is based on the World Health Organization's Ninth Revision, International Classification of Diseases (ICD-9). ICD-9-CM is the official system of assigning codes to diagnoses and procedures associated with hospital utilization in the United States. The ICD-9 is used to code and classify mortality data from death certificates. The ICD-9-CM consists of: a tabular list containing a numerical list of the disease code numbers in tabular form; an alphabetical index to the disease entries; and a classification system for surgical, diagnostic, and therapeutic procedures (alphabetic index and tabular list). Ed Dodds
    • References http://www.cdc.gov/nchs/about/otheract/icd9/abticd9.htm
  • International Classification of Diseases Version 10 (ICD-10)
    • The ICD has become the international standard diagnostic classification for all general epidemiological and many health management purposes. These include the analysis of the general health situation of population groups and monitoring of the incidence and prevalence of diseases and other health problems in relation to other variables such as the characteristics and circumstances of the individuals affected. It is used to classify diseases and other health problems recorded on many types of health and vital records including death certificates and hospital records. In addition to enabling the storage and retrieval of diagnostic information for clinical and epidemiological purposes, these records also provide the basis for the compilation of national mortality and morbidity statistics by WHO Member States. Ken Baclawski
    • References http://www.who.int/classifications/icd/en/
  • iPlayer model
    • CMC content model is built in Protege, hence the increased likelihood of being called an ontology. Main issues are around over-complexity given the business needs and creation of multiple overlapping models that are inconsistent with each other. Karen Loasby
    • References none public
  • ISO 10303 (STEP)
  • ISO 15926-2
    • Entity relationship models have roughly the same expressivity as Description Logics. Entity Relationship models are ontologies, but many practitioners are not aware that what they are really doing is ontology, and as a result many of them are not very good ontologies. But a bad ontology is still an ontology. This sort of ontology is easily the most widespread, and has the biggest impact on business and commerce since SQL databases run the worlds economy. Matthew West
    • References http://www.tc184-sc4.org/wg3ndocs/wg3n1328/lifecycle_integration_schema.html
  • ISO 15926-2
  • ISO Country Names
  • ISO/IEC 11179 - Metadata registries
  • ISO/IEC 15944-4 FDIS
    • Expressiveness Logically defined in Prolog
    • Structure Highly structured
    • Granularity relatively coarse
    • Intended Use Several intended uses included education
    • Prescriptive/descriptive prescriptive
    • Governance normative standard
    • Assessed by: BillMcCarthy
  • ISO/IEEE 11073-10101
    • Cited as a medical device interoperability standard (ISO/IEEE 11073), the nomenclature section is touted by the developers as the key to semantic interoperability. The standard has not been widely implemented and is not in any format that is computable. Kathy Lesh
  • ISO Languages
  • Joint Warfare Simulation Object Library
    • Provides a strong taxonomical structure (based on a heirarchy divided up into broad conceptual areas of agent, physical, and event entities). Lacks a method for formally capturing 'meaning' of entities, and is very limited in scope in that it only addresses elements of specific interest to the domain of Joint Warfare simulation, and only from a U.S.-centric perspective. Atomic concepts required for such a simulation are missing, as are other perspectives relative to the domain. Charles Turnitsa
    • References Conwell, C.L. Joint Warfare Simulation Object Library, U.S. Navy Research and Development Technical Document TD2808, Washington, DC, June 1995
  • Medical Subject Headings (MeSH)
    • The MeSH thesaurus is used by NLM for indexing articles from 4,800 of the world's leading biomedical journals for the MEDLINE/PubMED database. It is also used for the NLM-produced database that includes cataloging of books, documents, and audiovisuals acquired by the Library. Each bibliographic reference is associated with a set of MeSH terms that describe the content of the item. Similarly, search queries use MeSH vocabulary to find items on a desired topic. Ken Baclawski
    • References http://www.nlm.nih.gov/mesh/termscon.html
  • Multi-Entity Bayesian Network (MEBN)
  • National Agricultural Library Thesaurus (NALT)
  • National Institute for Health and Clinical Excellence (NICE) Taxonomy Scheme
  • OpenCYC
  • OWL-S
  • PIPs model
    • CMC content model is built in Protege, hence the increased likelihood of being called an ontology. Main issues are around over-complexity given the business needs and creation of multiple overlapping models that are inconsistent with each other. Karen Loasby
    • References none public
  • Pizza Ontology
  • PreAct (development tool)
  • Process Specification Language (PSL)
    • PSL is a formal ontology axiomatized in Common Logic. It is applied to support semantic integration among process-related software applications, and it is also applied to support automated reasoning (such as verification of the consistency of business processes and web service discovery) Michael Grüninger
    • Expressiveness FOL
    • Structure formal
    • Granularity medium
    • Intended Use KB semantic integration/interoperablity,manufacturing process interoperability
    • Automated Reasoning yes
    • References http://www.mel.nist.gov/psl/
    • Assessed by: Pat Cassidy, Leo Obrst, Michael Grüninger, Arturo Sanchez, Joe Kopena
  • Reference Data Library (RDL)
    • Until now we have focussed on the taxonomy. Once that is in a good shape, we will add so-called Object Information Models by means of ISO 15926-7 templates. Hans Teijgeler
    • References http://www.posccaesar.com/ select 'POSC Caesar Core RDL based on IS-model'
  • Relation Ontology (RO)
  • Semantic MediaWiki
  • Sequence Ontology (SO)
    • The Sequence Ontology Project (SO) is a joint effort by genome annotation centres, including: WormBase, the Berkeley Drosophila Genome Project, FlyBase, the Mouse Genome Informatics group, and the Sanger Institute. They are a part of the Gene Ontology Project and their aim is to develop an ontology suitable for describing biological sequences. Ken Baclawski
    • References http://song.cvs.sourceforge.net/song
  • Service Modeling Language (SML)
    • Term is found in the Terminology section of the public specification. Term is widely used by the target community (system architects) to describe other things. Carl Mattocks
    • References http://www.serviceml.org/
  • SNOMED-CT
    • Although SNOMED CT is built using description logics, I do not consider it a 'true' ontology. It has too many compound (precoordinated) concepts. It does not have natural language text definitions. It is inconsistently modeled. SNOMED CT is trying to be too many things to too many people/groups. Kathy Lesh
    • References http://www.snomed.org/snomedct/index.html
  • SUMO
  • SWSF
  • Tag Ontology
    • Expressiveness TBD but probably OWL
    • Structure unstructured
    • Granularity coarse
    • Intended Use 8 use cases have been specified
    • Automated Reasoning Intended for automated reasoning about tag sources
    • Prescriptive/descriptive descriptive
    • Assessed by: Tom Gruber ThomasVanderWal
  • Unified Medical Language System (UMLS) Metathesaurus
    • The Metathesaurus is a very large, multi-purpose, and multi-lingual vocabulary database that contains information about biomedical and health related concepts, their various names, and the relationships among them. Designed for use by system developers, the Metathesaurus is built from the electronic versions of various thesauri, classifications, code sets, and lists of controlled terms used in patient care, health services billing, public health statistics, indexing and cataloging biomedical literature, and/or basic, clinical, and health services research. These are referred to as the 'source vocabularies' of the Metathesaurus. Ken Baclawski
    • References http://www.nlm.nih.gov/research/umls/access.html
  • Unified Medical Language System (UMLS) Semantic Network
  • Universal Decimal Classification; Colon Classification
    • Faceted classification is nearer to the concept of ontologies. Faceted classification scheme is designed to express the basic structure of the thought content of a document in standard way, instead of just enumerating a group of subject classes. Nabonita Guha
  • Web Service Modeling Language (WSML)
    • Term is an invention of the public specification (subject matter is clearly ontological). Essentially is a compound term that requires full understanding of each component term. The use of the 'dash' seems to break rules for making ontological statements. Carl Mattocks
    • References http://www.w3.org/Submission/WSML/
  • Wordnet
    • Expressiveness none by itself
    • Structure low structure
    • Granularity moderately coarse
    • Intended Use computational linguistics
    • Automated Reasoning no
    • References http://wordnet.princeton.edu/
    • Assessed by: Tom Gruber ThomasVanderWal
  • World Bank Core Metadata Strategy
    • What people sometimes refer to as 'faceted' structures when properly formed is actually a metadata scheme, each facet of which may have its own distinct behavior and structures. There is a need to bring together the people who talk about 'metadata' and the people who talk about 'faceted search'. They using different terms but meaning the same thing. There are discrepancies in business rules applied to each one, though. Denise Bedford
  • World Bank currency names
  • World Bank MetaThesaurus
    • Leveraged in topic classification, used to support search (equivalent terms for synonym expansion), other relationships for suggesting other search terms. Denise Bedford
    • References http://www.multites.com/wb/
  • WSDL-S
  • WSMO