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Unifying Data and Domain Knowledge Using Virtual Views    Kalyana Krishnan  Overview 
Unifying Data and Domain Knowledge Using Virtual Views    Kalyana Krishnan  Overview 

... properties are drawn into a transitive tree and implication rules into an implication graph.  When the queries are issued against the virtual view, a query rewriter rewrites the queries  to retrieve appropriate information from the relational tables as well as the ontology.  ...
mdean-rdfdbm
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...  Get the data into Semantic Web format quickly and then apply Semantic Web tools  Much less labor to achieve similar results  How “nice” can we make the first stage output? ...
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... Enables object in “data space” to be associated formally with object in “science concept space” “Shared understanding” enables software tools to find “meaning” in resources ...
My own background - Department of Computer Science
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... record extensive world knowledge in predicate, but which its designer Douglas Lenat also claimed as a possible knowledge form for language processing. We must begin with one of my earlier questions about the conflation of ontologies (construed as hierarchical classifications of things or entities) a ...
Ontologies and Databases: myths and challenges
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... representation of complex properties and relations that may exist in the data; they should allow for an abstract representation of information which resembles the way they are actually perceived and used in the real world, thus shortening (with respect to the more traditional data models) the semant ...
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Ontology - UNC School of Information and Library Science
Ontology - UNC School of Information and Library Science

... modeling with entities/relationships) Most ontologies focus on a specific area to conceptualize (e.g. subject thesauri) Must be updated to keep up with dynamic world No set discipline or methodology! ...
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Upper ontology

In information science, an upper ontology (also known as a top-level ontology or foundation ontology) is an ontology (in the sense used in information science) which describes very general concepts that are the same across all knowledge domains. An important function of an upper ontology is to support very broad semantic interoperability between a large number of ontologies which are accessible ranking ""under"" this upper ontology. As the rank metaphor suggests, it is usually a hierarchy of entities and associated rules (both theorems and regulations) that attempts to describe those general entities that do not belong to a specific problem domain.The seemingly conflicting use of metaphors implying a solid rigorous bottom-up ""foundation"" or a top-down imposition of somewhat arbitrary, and possibly political, decisions is no accident – the field is characterized by the usual mix of controversy, politics, competing approaches and academic rivalry. Some upper ontologies have led to commercial products, causing a financial incentive to promote one ontology over the competing systems.Debates notwithstanding, it can be said that a very important part of each upper ontology can be considered as the computational implementation of natural philosophy, which itself is a more empirical method for investigating the topics within the philosophical discipline of physical ontology.Library classification systems predate these upper ontology systems. Though library classifications organize and categorize knowledge using general concepts that are the same across all knowledge domains, neither system is a replacement for the other.
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