Ontology Evolution: Not the Same as Schema Evolution

By Natasha Noy, Michel C. A. Klein. Knowledge and Information Systems, 2004

648 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/e38f9d0878d9b06713142331695efe9ce5e5e0e0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Computer Networks and Communications

In Information Systems

Citations in the corpus

Methodologies, tools and languages for building ontologies: Where is their meeting point? (2003, methodology): “However, many other methods and methodologies have been proposed for other tasks, such as ontology reengineering [29], ontology learning [2] [45], ontology evaluation [25] [27] [35] [36] [41] [42], ontology evolution [47] [48] [58] [63], ontology merging [59], etc.”
Consistent Evolution of OWL Ontologies (2005, background): “While there exist significant differences between schema evolution and ontology evolution, as elaborated in [13], particular aspects of schema evolution in databases are relevant for our work.”
Methods and tools for ontology evolution (2004, background): “Since the ontology model is richer than an object-oriented model [94], (i) the consistency definition includes more consistency constraints; and (ii) the number of possible changes is much richer than in a typical (relational or object-oriented) database schema.”
Ontology mapping: the state of the art (2003, background): “For example, in a comparative survey, Noy & Klein (2002) identified a number of areas where ontologies and database schemata are different from the perspective of evolution.”
A Protégé Plug-In for Ontology Extraction from Text Based on Linguistic Analysis (2004, background): “Additionally, as ontologies are domain descriptions that tend to evolve rapidly over time and between different applications (see e.g. Noy and Klein, 2002) there has been an increasing development in recent years towards learning or adapting ontologies dynamically, e.g. by analysis of a…”
User-Driven Ontology Evolution Management (2002, background): “In [18] authors discuss the differences that steam from different knowledge models and different usage paradigms.”
A Survey of Schema-Based Matching Approaches (2005, neutral): “In this respect, ontology alignment differs substantially from schema matching in the following two (among the others, see [36]) areas: • Database schemas often do not provide explicit semantics for their data.”
Ontology change: classification and survey (2008, background): “In (Stojanovic et al. 2002), 12 different composite changes are identiﬁed; in (Noy & Klein 2004), 22 such operations are listed; in (Stuckenschmidt & Klein 2003) however, the authors mention that they have identiﬁed 120 different interesting composite operations and that the list is still growing!”
Ontology Matching (2007, background): “Its main focus is on discovering the differences, e.g., which ontology entities have been added, deleted or renamed, between two ontology versions (Roddick 1995; Noy and Klein 2004; Noy and Musen 2002b, 2004; Kirsten et al. 2011; Hartung et al. 2013).”