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In Information Science , an upper ontology ('''top-level ontology''', or '''foundation ontology''') is an attempt to create an Ontology which describes very general concepts that are the same across all Domains . The aim is to have a large number on ontologies accessible under this upper ontology. It is usually a Hierarchy of entities and associated rules (both Theorem s and Regulation s) that attempts to describe those general entities that do not belong to a specific problem domain. Upper ontologies are commercially valuable, creating competition to define them. Peter Murray-Rust has claimed that this leads to "semantic and ontological warfare due to competing standards", and accordingly any standard foundation ontology is likely to be contested among commercial or political parties, each with their own idea of 'what exists' (in the philosophical sense). No one upper ontology has yet gained widespread acceptance as a De Facto standard. Different organizations are attempting to Define Standards for specific domains. The ' Process Specification Language ' (PSL) created by the National Institute For Standards And Technology (NIST) is one example. There is debate over whether the concept of an upper ontology is Feasible , these arguments are outlined below. Why an upper ontology is not feasible The arguments disregard that under normal social conditions (such as the existence of academic and political freedoms) many ontologies will simultaneously exist and compete for adherents. Permanently adopting any single rigid system is unlikely, and probably undesirable in the public interest. That being said, encouraging private efforts to create a highly successful upper ontology that achieves adherents by virtue of its utility is likely to have a socially beneficial result - better communication. Any effort to encode a useful Upper Or Lower Ontology will be characterized by ontological constraints that philosophers have found historically inescapable. Above all, these constraints cast serious doubt on attempts to build a general-purpose upper ontology.
Because any ontology is, among other things, a social / cultural Artifact , there is no purely objective perspective from which to observe the whole terrain of concepts. Instead of asking, “what hierarchical representation of concepts best captures the universal relationships among general ideas,” it is more productive to ask “what specific purpose do we have in mind for this conceptual map of entities and what practical difference will this ontology make?” This pragmatic philosophical position surrenders all hope of devising the encoded ontology version of “everything that is the case,” ( Wittgenstein , Tractatus Logico-Philosophicus ). According to Barry Smith in ''The Blackwell Guide to the Philosophy of Computing and Information'' (2004), "the project of building one single ontology, even one single top-level ontology, which would be at the same time non-trivial and also readily adopted by a broad population of different information systems communities, has largely been abandoned." (p. 159) How ontologies will be employed in Artificial Intelligence is an open question, but much of what is known about concept acquisition and the social / linguistic interactions of human beings makes it unlikely that a general-purpose ontology is the essential foundation for learning or for achieving an intellect certifiable by the Turing Test . Why an upper ontology is feasible While there is no single agreed metaphysics, the very existence of long standing arguments in the field shows that there are a number of models that do not have fatal flaws. Proponents of an upper ontology argue that while there is not one single true upper ontology, there are in fact several good ones that may be created. The benefits of standardization for communication and sharing suggest that practical system implementors should consider adopting a common upper ontology. Several common arguments against upper ontology can be examined more clearly by separating issues of concept definition (ontology), language (lexicons), and facts (knowledge). The most common conflict among informal ontologies is a difference in language. This difference may be evident even when communities speak the same human language. People have different terms and phrases for the same concept. However, that does not necessarily mean that those people are referring to different concepts. They may simply be using different language. It is essential to separate the language used to refer to concepts from the concepts themselves. Formal ontologies typically use linguistic labels to refer to concepts, but the terms mean no more and no less than what their axioms say they mean. Labels are similar to variable names in software. They should be evocative, but should not be confused with the actual meaning of the name in the context of a formal system. A second argument is that people believe different things, and therefore can't have the same ontology. However, many differences in belief are simply differences in the truth value of a particular assertion, not in the terms themselves that make up a particular logical assertion. Even arguments about the existence of a thing require a certain sharing of a concept, even though its existence in the real world may be disputed. Separating belief from naming and definition also helps to clarify this issue, and show how concepts can be held in common, even in the face of differing belief. In summary, most disagreement about the viability of an upper ontology can be traced to the conflation of ontology, language and knowledge. Some additional concerns can be traced simply to the lack of common knowledge about specialized areas of knowledge. This is inescapable. Lack of knowledge does not however entail the impossibility of common ontology but rather points to the fact that many people, or agents or groups will have areas of their respective internal ontologies that do not overlap. The pragmatic issue is that sharing as much as possible is beneficial, and that a vast amount of ontology can be shared. The several groups building upper ontologies and many users of those ontologies would no doubt be surprised to hear that such efforts have been abandoned. AVAILABLE ONTOLOGIES Cyc A well-known and quite comprehensive ontology available today is Cyc , a proprietary system under development since 1985, consisting of a foundation ontology and several domain-specific ontologies (called ''microtheories''). A subset of that ontology has been released for free under the name OpenCyc , with a larger subset available for non-commercial use under the name ResearchCyc .. ''Read more:'' Cyc Basic Formal Ontology The BFO or Basic Formal Ontology framework developed by Barry Smith and his associates consists in a series of sub-ontologies at different levels of granularity. The ontologies are divided into two varieties: SNAP (or snapshot) ontologies, comprehending continuant entities such as three-dimensional enduring objects, and '''SPAN''' ontologies, comprehending processes conceived as extended through (or as spanning) time. BFO thus incorporates both three-dimensionalist and four-dimensionalist perspectives on reality within a single framework. Interrelations are defined between the two types of ontologies in a way which gives BFO the facility to deal with both static/spatial and dynamic/temporal features of reality. [http://ontology.buffalo.edu/smith/articles/SNAP_SPAN.pdf] Each SNAP ontology is an inventory of all entities existing at a time. Each SPAN ontology is an inventory (processory) of all the processes unfolding through a given interval of time. Both types of ontology serve as basis for a series of sub-ontologies, each of which can be conceived as a window on a certain portion of reality at a given level of granularity. DOLCE and DnS Developed by Nicola Guarino and his associates at the Laboratory for Applied Ontology ( LOA ), the Descriptive Ontology for Linguistic and Cognitive Engineering ( DOLCE ) is the first module of the WONDERWEB foundational ontologies library. As implied by its acronym, DOLCE has a clear ''cognitive bias'', in that it aims at capturing the ontological categories underlying natural language and human commonsense. DOLCE, however, does not commit to a strictly referentialist metaphysics related to the intrinsic nature of the world. Rather, the categories it introduces are thought of as cognitive artifacts, which are ultimately depending on human perception, cultural imprints and social conventions. In this sense, they intend to be just ''descriptive'' (vs ''prescriptive'') notions, that assist in making already formed conceptualizations explicit. DOLCE is an ontology of particulars, in the sense that its domain of discourse is restricted to them. Of course, universals are used to organize and characterize the particulars, but they are not themselves subject to being organized and characterized (e.g., by means of metaproperties). DnS (Descriptions and Situations), developed by Aldo Gangemi (LOA, Rome), is a ''constructivist'' ontology that pushes DOLCE’s descriptive stance even further. DnS does not put restrictions on the type of entities and relations that one may want to postulate, either as a domain specification, or as an upper ontology, and it allows for context-sensitive ‘''redescriptions''’ of the types and relations postulated by other given ontologies (or ‘ground’ vocabularies). The current OWL encoding of DnS assumes DOLCE as a ground top-level vocabulary. DnS and related modules also exploit ‘Codeps’ (Content Ontology Design Patterns), a newly created tool which provides a framework to annotate ‘focused’ fragments of a reference ontology (i.e., the parts of an ontology containing the types and relations that underly ‘expert reasoning’ in given fields or communities). Both DOLCE and DnS are particularly devoted to the treatment of social enties, such as e.g. organizations, collectives, plans, norms, and information objects. The DOLCE-2.1-Lite-Plus version, including a number of DnS-based modules, has been and is being applied to several ontology projects. General Formal Ontology The , is a realistic ontology integrating processes and objects. It tries to include many aspects of recent philosophy, which is reflected both in its taxonomic tree and its axiomatisations. GFO allows for different axiomatisations for parts of its taxonomic tree (such as the existence of atomar time-intervals vs. dense time). Furthermore, the distinction between endurants (objects) and perdurants (processes) is made explicit within GFO by the introduction of a special category, a Persistant . A persistant is a special universal with the intension of "remaining identical". A further difference to other upper ontologies is the used model of time. In GFO, time intervals are taken as primitive, and time-points (called boundaries) as derived. This is convenient in modelling instantanuous change. WordNet WordNet , a freely available database originally designed as a Semantic Network based on Psycholinguistic principles, was expanded by addition of definitions and is now also viewed as a Dictionary . It qualifies as an upper ontology by including the most general concepts as well as more specialized concepts, related to each other not only by the subsumption relations, but by other semantic relations as well, such as part-of and cause. However, unlike Cyc, it has not been formally axiomatized so as to make the logical relations between the concepts precise. It has been widely used in Natural Language Processing research. ''Read more:'' WordNet GJXDM/NIEM Global Justice XML Data Model and National Information Exchange Model is a collection of approximately 2,500 Data Element s that are used to communicate between federal agencies. These systems use an Activity-Document-Organization-Person structure to define most abstract data elements. Because of the consistent use of Representation Term s for properties these data elements are frequently used by state and federal agencies for Data Mapping . Suggested Upper Merged Ontology The Suggested Upper Merged Ontology (SUMO) is another comprehensive ontology project. It includes an upper ontology, created by the IEEE working group P1600.1 (predominantly by Ian Niles and Adam Pease ). It is extended with many domain ontologies and a complete set of links to WordNet . It is freely available. This would reserve certain terms and their meanings for all 'P1600.1 standard' systems. Some would take this to entail that a general Ontology (in the philosophical sense) defines 'what exists'. Some also feel that use of the adjective 'upper', in particular, implies a hierarchy one must accept rather than a foundation one can choose, and seems to suggest a cultural impact. Upper ontology creators however believe that an upper ontology simply defines a set of terms that people or software systems may choose to hold in common. The potential for Cultural Bias in SUMO has been tested by its translation into multiple non-English languages such as Chinese and Hindi , and its use within cultures that speak those languages, resulting in the conclusion by its creators and users that no significant linguistic or cultural biases are evident. ''Read more:'' Suggested Upper Merged Ontology Biomedical ontology Examples of ''domain ontologies'' can be found at the Open Biomedical Ontology site. They act as an umbrella organisation for many ontologies specific to biological topics (such as cellular organelles). Other SEE ALSO |
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