{"id":{"repo_id":"gmu","oai_identifier":"oai:MARS:1920/8366"},"canonical_url":"https://search.dev.ndltd.org/etd/gmu/oai:MARS:1920/8366","repository":{"repo_id":"gmu","name":"George Mason University","base_url":"https://mars.gmu.edu/server/oai/request"},"display":{"title":"An Extensive Framework for Generating Ontology From Various Data Models","abstract":"In the Information Technology field, Ontology is concerned with the use of formal representation to describe concepts and relationships in a domain of knowledge. Using ontologies, organizations can facilitate processes such as integrating heterogeneous systems, assessing data quality, validating business rules, and discovering hidden facts. Ontology engineering, however, is not a trivial process. Developing ontologies is highly dependent on the availability and knowledge of ontology modelers and domain experts. Moreover, the development process is often lengthy and error-prone.","abstract_html":"In the Information Technology field, Ontology is concerned with the use of formal representation to describe concepts and relationships in a domain of knowledge. Using ontologies, organizations can facilitate processes such as integrating heterogeneous systems, assessing data quality, validating business rules, and discovering hidden facts. Ontology engineering, however, is not a trivial process. Developing ontologies is highly dependent on the availability and knowledge of ontology modelers and domain experts. Moreover, the development process is often lengthy and error-prone.","abstract_has_math":false,"creators":["Albarrak, Khalid"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-08","date_published":"2013-08","updated_at":"2026-07-27T19:52:04Z","subjects":["Information technology","Computer science","Artificial intelligence","Database","Data Models","Ontology","Semantic Computing","Symmetric Relations","Transitive Relations"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/8366"],"render_values":[{"text":"hdl:1920/8366","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2013-08"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Information technology","Computer science","Artificial intelligence","Database","Data Models","Ontology","Semantic Computing","Symmetric Relations","Transitive Relations"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/8366"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.other","label":"Dc Description Other","values":["In the Information Technology field, Ontology is concerned with the use of formal representation to describe concepts and relationships in a domain of knowledge. Using ontologies, organizations can facilitate processes such as integrating heterogeneous systems, assessing data quality, validating business rules, and discovering hidden facts. Ontology engineering, however, is not a trivial process. Developing ontologies is highly dependent on the availability and knowledge of ontology modelers and domain experts. Moreover, the development process is often lengthy and error-prone."]},{"key":"dc:title","label":"Title","values":["An Extensive Framework for Generating Ontology From Various Data Models"]}]}],"canonical_facts":{"dc:date.issued":["2013-08"],"dc:description.other":["In the Information Technology field, Ontology is concerned with the use of formal representation to describe concepts and relationships in a domain of knowledge. Using ontologies, organizations can facilitate processes such as integrating heterogeneous systems, assessing data quality, validating business rules, and discovering hidden facts. Ontology engineering, however, is not a trivial process. Developing ontologies is highly dependent on the availability and knowledge of ontology modelers and domain experts. Moreover, the development process is often lengthy and error-prone."],"dc:identifier":["hdl:1920/8366"],"dc:subject":["Information technology","Computer science","Artificial intelligence","Database","Data Models","Ontology","Semantic Computing","Symmetric Relations","Transitive Relations"],"dc:title":["An Extensive Framework for Generating Ontology From Various Data Models"],"dc:type":["Dissertation"]},"updated_at":"2026-07-27T19:52:04Z"}