This link has been bookmarked by 24 people . It was first bookmarked on 17 May 2007, by Marcel van Mackelenbergh.
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26 Jul 09
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27 Feb 09
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it is also a term that has widely divergent use and understanding within the community
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There is an M.C. Escher-like recursion of the lizard eating its tail when one observes ontologists creating an ontology to describe the ontological domain.
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domain X perspective X schema.
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Human and domain diversities makes this viewpoint patently false.
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We live in the real world, where multiple options will always have their advocates and their applications
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The sooner we can embrace content in any of these formats and convert it to a canonical form,
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semantic mediation
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But that observation need not also embrace chaos.
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the development of an organism through its embryological phases mirrors its evolutionary history
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this naturalness should emerge from the shared understandings and perceptions of the domain’s participants.
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The phylogeny example shows that understanding changes over time as knowledge is gained. We now accept DNA over the recapitulation theory.
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change is a constant
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expressiveness is the extent and ease by which an ontology can describe domain semantics. Structure they define as the degree of organization or hierarchical extent of the ontology. They further define granularity as the level of detail in the ontology.
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. . . formal ontologies (e.g., BFO, DOLCE, SUMO), biomedical ontologies (e.g., Gene Ontology, SNOMED CT, UMLS, ICD), thesauri (e.g., MeSH, National Agricultural Library Thesaurus), folksonomies (e.g., Social bookmarking tags), general ontologies (WordNet, OpenCyc) and specific ontologies (e.g., Process Specification Language). The list also includes markup languages (e.g., NeuroML), representation formalisms (e.g., Entity-Relation model, OWL, WSDL-S) and various ISO standards (e.g., ISO 11179). This [Ontolog] sample clearly illustrates the diversity of artifacts collected under “ontology”.
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More formal ontologies have greater expressiveness
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Not all content providers can or want to employ ontology engineers to enable formal inferencing of their content. Yet, on the other hand, their content in its various forms does have some meaningful structure, some organization. The trick is to extract this structure for more meaningful use such as data exchange or data merging.
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also, the nature of adoption shows much about how ontological structure is an artifact, not driver, for use
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Both tags and hierarchical structure are arbitrary, but some researchers now believe over large enough participant sets that structural consensus and value does emerge
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The Web Ontology Language (OWL) is a language for defining and instantiating Web ontologies. An OWL ontology may include descriptions of classes, along with their related properties and instances. OWL is designed for use by applications that need to process the content of information instead of just presenting information to humans. It facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics. The three language versions are in order of increasing expressiveness
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As a rule of thumb, items that are less “formal” can be converted to a more formal expression, but the most formal forms can generally not be expressed in less formal forms.
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This is not to say that the various dialects of OWL should be neglected. In bounded environments, they can provide superior reasoning power and are warranted if they can be sufficiently mandated or enforced. But the RDF and RDF-S systems represent the most tractable “meeting place” or “middle ground,” IMHO.
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SUMO is one of the formal ontologies that has been mapped to the WordNet lexicon, which adds to its semantic richness. SUMO is written in the SUO-KIF language. SUMO is free and owned by the IEEE. The ontologies that extend SUMO are available under GNU General Public License.
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At this level, the structure is quite abstract. But one can easily browse the SUMO structure. A nifty tool to do so is the KSMSA (Knowledge Support for Modeling and Simulation) ontology browser.
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the entities, are also fairly abstract. That is because the intention of a standard “upper-level” ontology is to cover all relevant knowledge aspects of each entity’s domain. This approach results in a subject and topic coverage that feels less “concrete” than the coverage in, say, an encyclopedia, directory or card catalog.
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According to Park and Durusau, upper ontologies are diverse, middle ontologies are even more diverse, and lower ontologies are more diverse still.
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increases as we approach real user interaction levels
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diversity of approach is a further key factor.
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ontology integration or federation.
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A fundamental distinction within mechanisms to combine ontologies is whether it is a unified or centralized approach (often imposed or required by some party) or whether it is a schema mapping or binding approach. We can term this distinction centralized v. federated.
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the ultimately critical domain specifics required for actual implementation
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24 Jan 09
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22 Jan 09
Fernando Sánchez Zamoraamplio artículo sobre ontologías y su relación con otras formas de arquitectura de la información. interesantes figuras explicativas
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12 Nov 08
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22 Oct 08
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28 Aug 08
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27 Aug 08
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25 Aug 08
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27 Jun 08
Joachim ReitanA case for pluralism in the semantic universe.
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05 Nov 07
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07 Oct 07
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09 Aug 07
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22 May 07
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18 May 07
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