Towards a standard upper ontology

By Ian Niles, Adam Pease. Formal Ontology in Information Systems, 2001

2,017 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/49bd7635eb8661b0b3f68713748c7008a6c0a7f6

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Citations in the corpus

A Survey of Schema-Based Matching Approaches (2005, neutral): “Examples are the Suggested Upper Merged Ontology (SUMO) [55] and Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) [31].”
DELIS Dynamically Evolving , Large-scale Information Systems Integrated Project Member of the FET Proactive Initiative Complex Systems DELIS-TR-594 Yago : A Large Ontology from Wikipedia and WordNet (2007, methodology): “These include WordNet [66], Cyc or OpenCyc [106], SUMO [114], and especially domain-specific ontologies and taxonomies such as UMLS2 or the GeneOntology3.”
Ontological realism: A methodology for coordinated evolution of scientific ontologies (2010, positive): “SUMO, too, has proved to have considerable value as an upper-level ontology for certain purposes (Niles & Pease, 2001).”
Semantic web technologies in AEC industry: A literature overview (2017, methodology): “optimization [50,112-131,134-148] • Connect BIM and GIS [21,165-179] • Enable automated regulation compliance”
YAGO2: A Spatially and Temporally Enhanced Knowledge Base from Wikipedia: Extended Abstract (2013, background): “Prominent examples of handcrafted knowledge resources are Cyc [1], WordNet [2], and SUMO [44], and also more recent ontologies such as GeoWordNet [13].”
Semantic integration: a survey of ontology-based approaches (2004, neutral): “While many researchers hope that domain-and applicationspeci.c ontologies will reuse the foundational ontologies, like SUMO and DOLCE, and that such reuse will indeed facilitate semantic interoperation between applications based on these ontologies, we do not yet have enough experience reports ”
PARIS: Probabilistic Alignment of Relations, Instances, and Schema (2011, background): “This is a reasonable assumption, because most ontologies are either manually designed [23, 24], or generated from a database (such as the datasets mentioned in the introduction), or designed with avoiding equivalent resources in mind [30].”
Representing General Relational Knowledge in ConceptNet 5 (2012, background): “Additional sources that may be added include the plan-oriented knowledge in Honda’s Open Mind Indoor Common Sense (Kochenderfer, 2004), connections to knowledge in Freebase (Bollacker et al., 2008), ontological connections to SUMO and MILO (Niles and Pease, 2001), and new processes that scan well-st”
YAGO: A Large Ontology from Wikipedia and WordNet (2008, methodology): “The Suggested Upper Model Ontology SUMO [39] is a highly axiomatized manually assembled ontology.”
The Geospatial Web: How Geobrowsers, Social Software and the Web 2.0 are Shaping the Network Society (2007, background): “, SUMO (Niles and Pease 2001) and NASA SWEET (Raskin 2006).”
Ontologies: How can They be Built? (2004, methodology): “8), we were performing a composition process (revision/integration), involving part of the SUMO (Niles and Pease 2001) ontology that was being constructed and updated at the same time by some members of the IEEE SUO working group.”
An ontology for context-aware pervasive computing environments (2003, background): “At present, there are two distinctive versions of spatial ontologies namely the spatial ontology in SUO [Niles and Pease, 2001] and the upper Cyc ontology [Cyc, 1997].”
Spreadsheet simulation (2004, neutral): “Two major initiatives for upper ontologies are the Suggested Upper Merged Ontology (SUMO) and the IEEE Standard Upper Ontology (SUO) (Niles and Pease 2001).”
OntoNotes: The 90% Solution (2006, background): “Omega, which has been used for MT, summarization, and database alignment, has been assembled semi-automatically by merging a variety of sources, including Princeton’s WordNet, New Mexico State University’s Mikrokosmos, and a variety of Upper Models, including DOLCE (Gangemi et al., 2002), SUMO (Nile”
Machine Common Sense Concept Paper (2018, background): “[13], YAGO [14], DOLCE [15], and hundreds of smaller ontologies on the Semantic Web [16]).”