Conceptual Schema Transformation in Ontology-Based Data Access

  • Diego CalvaneseEmail author
  • Tahir Emre Kalayci
  • Marco Montali
  • Ario Santoso
  • Wil van der Aalst
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11313)


Ontology-based Data Access (OBDA) is a by now well-established paradigm that relies on conceptually representing a domain of interest to provide access to relational data sources. The conceptual representation is given in terms of a domain schema (also called an ontology), which is linked to the data sources by means of declarative mapping specifications, and queries posed over the conceptual schema are automatically rewritten into queries over the sources. We consider the interesting setting where users would like to access the same data sources through a new conceptual schema, which we call the upper schema. This is particularly relevant when the upper schema is a reference model for the domain, or captures the data format used by data analysis tools. We propose a solution to this problem that is based on using transformation rules to map the upper schema to the domain schema, building upon the knowledge contained therein. We show how this enriched framework can be automatically transformed into a standard OBDA specification, which directly links the original relational data sources to the upper schema. This allows us to access data directly from the data sources while leveraging the domain schema and upper schema as a lens. We have realized the framework in a tool-chain that provides modeling of the conceptual schemas, a concrete annotation-based mechanism to specify transformation rules, and the automated generation of the final OBDA specification.


Conceptual schema transformation Ontology-based data access Ontology-to-ontology mapping 



This research is supported by the Euregio IPN12 KAOS (Knowledge-Aware Operational Support) project, funded by the “European Region Tyrol-South Tyrol-Trentino” (EGTC), and by the UNIBZ internal project OnProm (ONtology-driven PROcess Mining).


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Diego Calvanese
    • 1
    Email author
  • Tahir Emre Kalayci
    • 1
    • 2
  • Marco Montali
    • 1
  • Ario Santoso
    • 1
    • 3
  • Wil van der Aalst
    • 4
  1. 1.KRDB Research Centre for Knowledge and DataFree University of Bozen-BolzanoBolzanoItaly
  2. 2.Virtual Vehicle Research CenterGrazAustria
  3. 3.Department of Computer ScienceUniversity of InnsbruckInnsbruckAustria
  4. 4.Process and Data Science (PADS)RWTH Aachen UniversityAachenGermany

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