The TOVE project ("Toronto Virtual Enterprise") is a project to develop an ontological framework for enterprise integration (EI) based on and suited for enterprise modeling. [1] In the beginning of the 1990s it was initiated by Mark S. Fox and others at the University of Toronto. [2]
The original goal of the project was fourfold: [3]
Eventually the ongoing project aims to develop a set of integrated ontologies for the modelling of both commercial and public enterprises.
The model according to Ted Williams (2000) is "multi-level, spanning conceptual, generic and applications layers. The generic and applications layers all also stratified and composed of micro theories spanning, for example, activities, time, resources, constraints, etc. At the generic level. Critical to the TOVE effort is enabling the easy instantiation of the model for a particular enterprise TOVE models will be automatically created as a by product of the enterprise design function". [4] At the turn of the millennium TOVE has been used to model a computer manufacturer and an aerospace engineering firm.
The TOVE enterprise models is presented by Fox et al. (1995) as second generation knowledge engineering approach. A first generation knowledge engineering approach "is extracting rules from experts, while second generation is ontology engineering: They develop comprehensive ontologies for all the aspects of an organization they find necessary (necessity is decided based on competency requirements to the model, i.e., what are the questions the model will have to answer, either by ordinary look-up or by deduction). The background of TOVE is clearly knowledge engineering and to some degree Computer Integrated Manufacturing". [1]
Cyc is a long-term artificial intelligence project that aims to assemble a comprehensive ontology and knowledge base that spans the basic concepts and rules about how the world works. Hoping to capture common sense knowledge, Cyc focuses on implicit knowledge that other AI platforms may take for granted. This is contrasted with facts one might find somewhere on the internet or retrieve via a search engine or Wikipedia. Cyc enables semantic reasoners to perform human-like reasoning and be less "brittle" when confronted with novel situations.
Knowledge representation and reasoning is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning, such as the application of rules or the relations of sets and subsets.
In computer science and information science, an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of concepts and categories that represent the subject.
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IDEF, initially an abbreviation of ICAM Definition and renamed in 1999 as Integration Definition, is a family of modeling languages in the field of systems and software engineering. They cover a wide range of uses from functional modeling to data, simulation, object-oriented analysis and design, and knowledge acquisition. These definition languages were developed under funding from U.S. Air Force and, although still most commonly used by them and other military and United States Department of Defense (DoD) agencies, are in the public domain.
CIMOSA, standing for "Computer Integrated Manufacturing Open System Architecture", is an enterprise modeling framework, which aims to support the enterprise integration of machines, computers and people. The framework is based on the system life cycle concept, and offers a modelling language, methodology and supporting technology to support these goals.
Loom is a knowledge representation language developed by researchers in the artificial intelligence research group at the University of Southern California's Information Sciences Institute. The leader of the Loom project and primary architect for Loom was Robert MacGregor. The research was primarily sponsored by the Defense Advanced Research Projects Agency (DARPA).
Deborah Louise McGuinness is an American computer scientist and researcher at Rensselaer Polytechnic Institute (RPI). She is a Professor of Computer, Cognitive and Web Sciences, Industrial and Systems Engineering, and an endowed chair in the Tetherless World Constellation, a multidisciplinary research institution within RPI that focuses on the study of theories, methods and applications of the World Wide Web. Her fields of expertise include interdisciplinary data integration, artificial intelligence, specifically in knowledge representation and reasoning, description logics, the semantic web, explanation, and trust.
Knowledge-based engineering (KBE) is the application of knowledge-based systems technology to the domain of manufacturing design and production. The design process is inherently a knowledge-intensive activity, so a great deal of the emphasis for KBE is on the use of knowledge-based technology to support computer-aided design (CAD) however knowledge-based techniques can be applied to the entire product lifecycle.
In information science, an upper ontology is an ontology which consists of very general terms 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.
The ISO 15926 is a standard for data integration, sharing, exchange, and hand-over between computer systems.
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Knowledge Discovery Metamodel (KDM) is a publicly available specification from the Object Management Group (OMG). KDM is a common intermediate representation for existing software systems and their operating environments, that defines common metadata required for deep semantic integration of Application Lifecycle Management tools. KDM was designed as the OMG's foundation for software modernization, IT portfolio management and software assurance. KDM uses OMG's Meta-Object Facility to define an XMI interchange format between tools that work with existing software as well as an abstract interface (API) for the next-generation assurance and modernization tools. KDM standardizes existing approaches to knowledge discovery in software engineering artifacts, also known as software mining.
BORO is an approach to developing ontological or semantic models for large complex operational applications that consists of a top ontology as well as a process for constructing the ontology. It was originally developed as a method for mining ontologies from multiple legacy systems – as the first stage in an architectural transformation or software modernization. It has also been used to enable semantic interoperability between legacy systems. It is described in detail in. It is the analysis method used in the development and maintenance of the U.S. Department of Defense Architecture Framework (DoDAF) Meta Model (DM2), where a data modeling working group of over 350 members was able to systematically resolve a broad spectrum of knowledge representation issues.
Business Semantics Management (BSM) encompasses the technology, methodology, organization, and culture that brings business stakeholders together to collaboratively realize the reconciliation of their heterogeneous metadata; and consequently the application of the derived business semantics patterns to establish semantic alignment between the underlying data structures.
In computer science, information science and systems engineering, ontology engineering is a field which studies the methods and methodologies for building ontologies, which encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities. In a broader sense, this field also includes a knowledge construction of the domain using formal ontology representations such as OWL/RDF. A large-scale representation of abstract concepts such as actions, time, physical objects and beliefs would be an example of ontological engineering. Ontology engineering is one of the areas of applied ontology, and can be seen as an application of philosophical ontology. Core ideas and objectives of ontology engineering are also central in conceptual modeling.
Model Driven Interoperability (MDI) is a methodological framework, which provides a conceptual and technical support to make interoperable enterprises using ontologies and semantic annotations, following model driven development (MDD) principles.
The following outline is provided as an overview of and topical guide to natural-language processing:
Mark Stephen Fox is a Canadian computer scientist, Professor of Industrial Engineering and Distinguished Professor of Urban Systems Engineering at the University of Toronto, known for the development of Constraint Directed Scheduling in the 1980s and the TOVE Project to develop an ontological framework for enterprise modeling and enterprise integration in the 1990s.
Michael Gruninger is a Canadian computer scientist and Professor of Industrial Engineering at the University of Toronto, known for his work on Ontologies in information science. particularly with the Process Specification Language, and in enterprise modelling on the TOVE Project with Mark S. Fox.
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