AutoMap4OBDA: Automated Generation of R2RML Mappings for OBDA

  • Álvaro Sicilia
  • German Nemirovski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10024)


Ontology-Based Data Access (OBDA) has become a popular paradigm for the integration of heterogeneous data. The key components of an OBDA system are the mappings between the data source and the target ontology. The great efforts required to create manual mappings are still a significant barrier to adopting the OBDA. Current relational-to-ontology mapping generators are far from providing 100 % of the mappings required in real-world problems. To overcome this issue we present AutoMap4OBDA, a system which automatically generates R2RML mappings based on the intensive use of relational source contents and features of the target ontology. Ontology learning techniques are applied to infer class hierarchies, the string similarity metrics are selected based on the target ontology labels, and graph structures are applied to generate the mappings. We have used the RODI benchmarking suite to evaluate AutoMap4OBDA which outperforms the most advanced state-of-the-art mapping generators.


Relational-to-ontology mappings R2RML Ontology learning OBDA 



This work was carried out within the research project ENERSI funded by Ministry of Economy and Competitiveness of the Government of Spain (Reference number RTC-2014-2676-3)


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.ARC Enginyeria i Arquitectura La SalleUniversitat Ramon LlullBarcelonaSpain
  2. 2.Business and Computer ScienceAlbstadt-Sigmaringen-University of Applied SciencesAlbstadtGermany

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