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| Identifier |
000364677 |
| Title |
Managing the Specificity of Ontological Descriptions under Ontology Evolution. |
| Alternative Title |
Εξέλιξη οντολογιών και διαχείριση της ειδικότητας των οντολογικών περιγραφών |
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Author
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Καμπουράκη, Μαίρη Γεώργιος
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Thesis advisor
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Τζίτζικας, Ιωάννης
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Collaborator
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Αναλυτή, Αναστασία
Πλεξουσάκης, Δημήτρης
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| Abstract |
Semantic Web Ontologies are not static but evolve as the understanding of the domain (or
the domain itself) grows or evolves. This evolution happens independently of the
ontological instance descriptions (for short metadata) which are stored in the various
Metadata Repositories (MRs) or Knowledge Bases (KBs). However, it is a common practice
for a MR/ΚΒto periodically update its ontologies to their latest versions. This is done
by migrating the available metadata to the latest version of the ontology. Usually such
migrations are not difficult because new ontology versions are usually compatible with
the past versions. However such migrations incur gaps regarding the specificity of
migrated metadata. This results in inability to distinguish those metadata that should
be reexamined for possible specialization (as consequence of the migration) from those
for which this is not necessary. For this reason there is a need for principles,
techniques, and tools that can manage the uncertainty incurred by such migrations,
specifically techniques which can identify automatically the descriptions that are
candidate for specialization, compute, rank and recommend possible specializations, and
flexible interactive techniques for updating the metadata repository (and its candidate
specializations), after the user (curator) accepts/rejects such recommendations. This
problem is especially important for curated KBs which have increased quality
requirements (e-Science).
This is the first work that elaborates on this problem. It formulates the problem,
introduces the notion of extended KB consisting of the certain plus the possible (due to
migration) specialized knowledge, and proposes principles and rules for updating it,
assuming the RDF/S framework. Subsequently, it provides algorithms and reports
experimental results (over real and synthetic datasets) demonstrating the feasibility of
the approach. In addition, a compact representation of the possibilities is proposed for
reducing the storage space requirements. Finally, it presents RIMQA (RDF Instance
Migration Quality Assistant), a tool which has been designed and implemented for
supporting the entire lifecycle.
To conclude, the proposed approach can enrich the lifecycle of curated Semantic Web data
with quality management processes appropriate for scenarios where ontologies evolve
frequently and independently from instance descriptions. As a consequence, this allows
adopting iterative and agile ontology modeling approaches, appropriate for open
environments like Linked Open Data (LOD).
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| Language |
English |
| Subject |
Knowledge Base |
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Ontology Evolution |
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Specificity of Ontological Descriptions |
| Issue date |
2011-03-18 |
| Collection
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School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
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Type of Work--Post-graduate theses
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| Permanent Link |
https://elocus.lib.uoc.gr//dlib/e/9/1/metadata-dlib-22946458563ac5fafa646e86da6f8972_1300262829.tkl
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| Views |
560 |
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