Observatorio de I+D+i UPM

Descripción
Ontology Based Data Access (OBDA) refers to a range of techniques, algorithms and systems that can be used todeal with the heterogeneity of data that is common inside many organisations as well as in inter-organisational settings andmore openly on the Web. In OBDA, ontologies are used to provide a global view over multiple local datasets; and mappings arecommonly used to describe the relationships between such global and local schemas. Since its inception, this area has evolvedin several directions. Initially, the focus was on the translation of original sources into a global schema, and its materialisation,including non-OBDA approaches such as the use of Extract Transform Load (ETL) workflows in data warehouses and, morerecently, in data lakes. Then OBDA-based query translation techniques, relying on mappings, were proposed, with the aim ofremoving the need for materialisation, something especially useful for very dynamic data sources. We think that we are nowwitnessing the emergence of a new generation of OBDA approaches. It is driven by the fact that a new set of declarative mappinglanguages, most of which stem from the W3C Recommendation R2RML for Relational Databases (RDB), are being created.In this vision paper, we enumerate the reasons why new mapping languages are being introduced. We discuss why it may berelevant to work on translations among them, so as to benefit from the engines associated to each of them whenever one languageand/or engine is more suitable than another. We discuss the emerging concept of ?mapping translation?, the basis for this newgeneration of OBDA, together with some of its desirable properties: information preservation and query result preservation. Weshow several scenarios where mapping translation can be or is being already applied, even though this term has not necessarilybeen used in existing literature.
Internacional	Si
JCR del ISI	Si
Título de la revista	Semantic Web
ISSN	1570-0844
Factor de impacto JCR	3,182
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• Autor: Oscar Corcho Garcia (UPM)
• Autor: Freddy Priyatna . (UPM)
• Autor: David Chaves Fraga (UPM)

• Creador: Grupo de Investigación: Ontology Engineering Group
• Departamento: Inteligencia Artificial