Upper-level Ontology
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An Upper-level Ontology is an ontology that covers high-level concepts (and their interrelationships).
- AKA: Top-level Ontology, Foundational Ontology.
- Context:
- It can be produced by a General Knowledge Engineering Task.
- It can capture the most general and reusable concepts and definitions.
- It can clarify the meaning of more specific concepts.
- It can be reused.
- It can (typically) include a Thing Concept such as an Entity Concept and a Relation Concept.
- ...
- Example(s):
- a BFO Ontology.
- a BORO Ontology.
- a CIDOC Conceptual Reference Model.
- a DOLCE Ontology.
- a EuroWordNet Top Ontology (Vossen 1998).
- a IEEE Standard Upper Ontology.
- a Mikrokosmos Ontology.
- a PROTON Ontology.
- a Suggested Upper Merged Ontology (SUMO).
- a Unified Foundational Ontology (UFO).
- a Upper Cyc Ontology [1].
- a WordNet Top Ontology (Fellbaum 1998).
- …
- Counter-Example(s):
- a Domain Specific Ontology, such as: GO Genontology or Dublin Core.
- See: Knowledge Representation, Common-Sense Knowledge, Semantic Interoperability, Metaphor.
References
2023
- (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/Upper_ontology Retrieved:2023-6-9.
- In information science, an upper ontology (also known as a top-level ontology, upper model, or foundation ontology) is an ontology (in the sense used in information science) which consists of very general terms (such as "object", "property", "relation") that are common across all domains. An important function of an upper ontology is to support broad semantic interoperability among a large number of domain-specific ontologies by providing a common starting point for the formulation of definitions. Terms in the domain ontology are ranked under the terms in the upper ontology, e.g., the upper ontology classes are superclasses or supersets of all the classes in the domain ontologies.
A number of upper ontologies have been proposed, each with its own proponents.
Library classification systems predate 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.
- In information science, an upper ontology (also known as a top-level ontology, upper model, or foundation ontology) is an ontology (in the sense used in information science) which consists of very general terms (such as "object", "property", "relation") that are common across all domains. An important function of an upper ontology is to support broad semantic interoperability among a large number of domain-specific ontologies by providing a common starting point for the formulation of definitions. Terms in the domain ontology are ranked under the terms in the upper ontology, e.g., the upper ontology classes are superclasses or supersets of all the classes in the domain ontologies.
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Upper_ontology Retrieved:2015-2-8.
- 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. ...
2011
- (Pease, 2011) ⇒ Adam Pease. (2011). “Ontology: A Practical Guide." Articulate Software Press. ISBN:1889455105
2007
- (Obitko, 2007) ⇒ Marek Obitko. (2007). “Translations between Ontologies in Multi-Agent Systems", Ph.D. dissertation, Faculty of Electrical Engineering, Czech Technical University in Prague. http://www.obitko.com/tutorials/ontologies-semantic-web/modularization-of-ontologies.html
- The purpose of authoring ontologies is also reusing of knowledge. Once ontology is created for a domain, it should be (at least to some degree) reusable for other applications in the same domain. To simplify both ontology development and reuse, modular design is beneficial. The modular design uses inheritance of ontologies - upper ontologies describe general knowledge, and application ontologies describe knowledge for a particular application, as illustrated in the figure below.
- Depending on the scope of the ontology, ontology may be classified as follows (see also figure above):
- upper, generic, top-level ontology - describing general knowledge, such as what is time and what is space
- domain ontology - describing a domain, such as medical domain or electrical engineering domain, or narrower domains, such as personal computers domain
- task - ontology suitable for a specific task, such as assembling parts together
- application - ontology developed for a specific application, such as assembling personal computers
- Depending on the scope of the ontology, ontology may be classified as follows (see also figure above):
2001
- (Niles & Pease, 2001) ⇒ Ian Niles, and Adam Pease. (2001). “Towards a Standard Upper Ontology.” In: Proceedings of the International Conference on Formal Ontology in Information Systems - Volume 2001. doi:10.1145/505168.505170
- QUOTE: The Suggested Upper Merged Ontology (SUMO) is an upper level ontology that has been proposed as a starter document for The Standard Upper Ontology Working Group, an IEEE-sanctioned working group of collaborators from the fields of engineering, philosophy, and information science. The SUMO provides definitions for general-purpose terms and acts as a foundation for more specific domain ontologies. In this paper we outline the strategy used to create the current version of the SUMO, discuss some of the challenges that we faced in constructing the ontology, and describe in detail its most general concepts and the relations between them.
2000
- http://www-sop.inria.fr/acacia/personnel/phmartin/RDF/phOntology.html
- Metadata retrieval and reuse is enhanced when metadata providers follow common or interconnected ontologies. Below, we propose a top-level ontology to ease and guide metadata representation and organization. It reuses the classes and properties declared in [RDFMS] and [RDFSchema] and adds about 80 new classes and 120 new relations (properties). Some classes come from the Frame Ontology of Ontolingua [FrameOntol] (not all the classes and relations of this ontology have been reused since many are not relevant to RDF, e.g. n-ary relations with n > 2). Most classes and properties were selected and adapted from works of John Sowa [Sowa84] and completed with classes and relations from various other top-level ontologies (e.g. to a small extent, the CYC top-level ontology and the Generalized Upper Model). Whereas the set of proposed relations can be seen as relatively complete for the representation of most natural language sentences, we have mainly limited the introduction of classes to those required for the signatures of the relations (i.e. to constrain their ranges and domains). The whole file of this top-level ontology is accessible in RDF format and in a more readable format (that is also parsable)
To complete that work on classes, we have also worked on the WordNet lexical database [WN]. First, we have inserted the WordNet top-level classes into our top-level ontology (cf. section 1.2). Second, we have translated this database (plus the top-level ontology) into a 24Mb RDF file (click here for a 4.2Mb gzipped version). A version of this file in also given in the more readable format (click here for a 3.7Mb gzipped version). Third, to search this ontology of 84,000 categories and navigate along the various kinds of relations between them, we have implemented a CGI script and an HTML+Javascript interface to use it. The results are given in RDF or simpler formats.
Following our conventions, we have only used singular nouns for class names and have not introduced inverse relations (e.g. subClass and agentOf have not be introduced since subClassOf and agent are have been declared).
- Metadata retrieval and reuse is enhanced when metadata providers follow common or interconnected ontologies. Below, we propose a top-level ontology to ease and guide metadata representation and organization. It reuses the classes and properties declared in [RDFMS] and [RDFSchema] and adds about 80 new classes and 120 new relations (properties). Some classes come from the Frame Ontology of Ontolingua [FrameOntol] (not all the classes and relations of this ontology have been reused since many are not relevant to RDF, e.g. n-ary relations with n > 2). Most classes and properties were selected and adapted from works of John Sowa [Sowa84] and completed with classes and relations from various other top-level ontologies (e.g. to a small extent, the CYC top-level ontology and the Generalized Upper Model). Whereas the set of proposed relations can be seen as relatively complete for the representation of most natural language sentences, we have mainly limited the introduction of classes to those required for the signatures of the relations (i.e. to constrain their ranges and domains). The whole file of this top-level ontology is accessible in RDF format and in a more readable format (that is also parsable)