• Corpus ID: 12171549

D3.1.1.b State-of-the-Art on Ontology Evolution

@inproceedings{Haase2004D311bSO,
  title={D3.1.1.b State-of-the-Art on Ontology Evolution},
  author={Peter Haase and York Sure-Vetter},
  year={2004}
}
This document is an informal deliverable provided to SEKT partners. The main aim of this document is to provide an overview of existing research results and ongoing research in the are of ontology evolution. It further identifies relevant open research questions with respect to ontology evolution that will be addressed within the SEKT project. 

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References

SHOWING 1-10 OF 45 REFERENCES
OntoManager - A System for the Usage-Based Ontology Management
TLDR
An approach for guiding ontology managers through the modification of an ontology with respect to users’ needs is proposed, based on the analysis of end-users’ interactions with the ontology-based applications, which are tracked into the usage-log.
The Ontology Extraction & Maintenance Framework Text-To-Onto
TLDR
The paper presents a framework for semi-automatically learning ontologies from domainspecific texts by applying machine learning techniques, and presents the TEXT-TO-ONTO framework, which integrates manual engineering facilities to follow a balanced cooperative modelling paradigm.
OntoEdit: Collaborative Ontology Development for the Semantic Web
TLDR
This paper focuses on collaborative development of ontologies with OntoEdit which is guided by a comprehensive methodology.
Tracking Changes in RDF(S) Repositories
TLDR
The research presented is the definition of a formal model for tracking changes in graph-based data models that was used in the ontology middleware module developed under the On-To-Knowledge project as an extension of the Sesame RDF(S) repository.
Ontology evolution as reconfiguration-design problem solving
TLDR
This paper presents an approach to model ontology evolution as reconfiguration-design problem solving as a graph search where the nodes are evolving ontologies and the edges represent the changes that transform the source node into the target node.
User-Driven Ontology Evolution Management
TLDR
This paper identifies a possible six-phase evolution process and introduces the concept of an evolution strategy encapsulating policy for evolution with respect to user?s requirements, focusing on providing the user with capabilities to control and customize it.
Integrity and Change in Modular Ontologies
TLDR
An architecture for modular ontologies that supports local reasoning by compiling implied subsumption relations is defined and the problem of guaranteeing the integrity of a modular ontology in the presence of local changes is addressed.
OilEd: a Reason-able Ontology Editor for the Semantic Web
TLDR
OilEd is an ontology editor that has an easy to use frame interface, yet at the same time allows users to exploit the full power of an expressive web ontology language (OIL).
OntoEdit: Multifaceted Inferencing for Ontology Engineering
TLDR
OntoEdit is an ontology editor that has been developed keeping five main objectives in mind: ease of use, methodology-guided development of ontologies, consistency, extensibility through plug-in structure, and Development of ontology axioms.
Finding and Characterizing Changes in Ontologies
TLDR
OntoView provides a transparent interface to different versions of ontologies, by maintaining not only the transformations between them, but also the conceptual relation between concepts in different versions, which allows the interoperability of data that is described by the ontologies.
...
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