Michele Pasin / Quotes

Computational ontologies and knowledge bases

We take a computational ontology to be a directed acyclic graph where nodes represent concepts and the links between concepts represent the taxonomic “isa” relation (e.g. in the graph where ‘Wine → Red Wine → Brunello di Montalcino, everything that “is a” instance of Brunello di Montalcino “is a” instance of Red Wine, and everything that “is a” instance of Red Wine “is a” instance of Wine (we are less strict as to whether this subsumption relation must hold in all contexts of discourse—see Sect. 6.2). A knowledge base is an ontology that has been populated with individuals; mathematically, knowledge bases contain another kind of link denoting the “instance of” taxonomic relation, and a new kind of node denoting individuals (with the restriction that no individual can have any children). Thus we may populate our toy ontology with an individual, ‘Campogiovanni Brunello’, which is an instance of the concept Brunello di Montalcino. A computational ontology will also contain declarations for a number of non-taxonomic relations, which can either hold between individuals and constants (properties) or between two (or more) individuals (relations). Instances of these non-taxonomic relations may also be encoded in the process of ontology population. For example, a knowledge base might record the property ‘alcohol_content (Campo- giovanni Brunello, 7%)’ and the relation ‘pairs_with (Campogiovanni Brunello, Parmigiano Reggiano)’. Finally, a computational ontology may also contain a number of inference rules and axioms that can be used to reason about objects in the domain (e.g. infer the presence of certain relations on the basis of others, enforce consistency and default properties, and so forth).

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#computational-ontology #ontology #graph #nodes #concept

Graph database vs relational database

The marketing manager is hypothesis-testing: she might use this data for a while and then realize that adding geographic information would be useful too since…

Harnessing The Power Of Data Discovery: Pt. 2 | Yarcdata #graph-database #schema #nodes #database #graph #things

Contextual knowledge in the humanities

Humanities ontologies require dynamic concept formalizations instead of static ones, especially for contested, open-textured or ambiguous concepts. The…

Semantic Web For The Humanities #context #concept #ontology #definition

Ontological pluralism

Ludwig Wittgenstein's notion of language-games argues that there is no over-arching, single, fundamental ontology, but only a patchwork of overlapping…

Pluralism (philosophy) - Wikipedia, The Free Encyclopedia #ontology #concept #number #notion #wittgenstein

Ontology is an exercise in detection not creation

Requirements have no effect on meaning. Concepts are unaffected by whether or not you choose to include them in an application. If a given concept is that of…

Ontology And The Art Of Not Designing | In Context #meaning #art #ontology #things #concept

Ontology segmentation

Ontology segmentation or the creation of ontology views is an important issue. Since many ontologies constantly grow in size and are therefore more and more…

Ubiseditor 3.0: Collaborative Ontology Development On The Web #ontology-views #ontology #concept #users

Blank node identifiers

Since a complex graph might contain more than one blank node, there also needs to be a way to differentiate between these different blank nodes in a triples…

Rdf Primer #nodes #identifiers #subjects #form #results