Abstract
Information systems rely more and more on semantic web ontologies to share and interpret data within and across research domains. However, an important problem when dealing with ontologies is the fact that they are living artefacts and subject to change. When ontologies evolve, queries formulated using a past ontology version might become invalid and should be redefined or adapted. In this paper we propose a solution in order to identify the impact of ontology evolution on queries and to ease query migration. We present a module that receives as input the sequence of changes between the two ontology versions along with a set of queries and automatically identifies the specific change operations that affect the input queries. Besides the automatic identification of the affecting change operations, query migration is further aided by providing an explanation for the specific invalidation. This explanation is presented graphically by means of change paths that represent the evolution of the specific parts of the ontology that invalidate the query. We evaluate the time complexity of our approach and show how it can possibly reduce the human effort spent on query redefinition/adaptation.
Keywords
- Gene Ontology
- Conjunctive Query
- SPARQL Query
- Change Operation
- Ontology Evolution
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Kondylakis, H., Plexousakis, D. (2012). Ontology Evolution: Assisting Query Migration. In: Atzeni, P., Cheung, D., Ram, S. (eds) Conceptual Modeling. ER 2012. Lecture Notes in Computer Science, vol 7532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34002-4_26
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DOI: https://doi.org/10.1007/978-3-642-34002-4_26
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