Skip to main content
Engineering LibreTexts

9.3: An OBDA Architecture

  • Page ID
    6452
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    Among the options described in the previous section, the architecture with its components that we will look at here are an example of Option 1 v1 [CGL+07]. The intuitive idea for solving the sysadmin issues is depicted in Figure 8.3.1, tophalf (in blue): we add a “semantic layer” to a traditional database, or: we have a semantic layer and store information about all individuals in the knowledge base not in the OWL ABox but in external storage (a relational database) and create a new link between the OWL TBox and the data store.

    There are different tools for each component that make up a realised OBDA system. For instance, one can choose less or no reasoning, such as the Virtuoso system2, and an RDF triple store versus relational database technology to store the data. We shall take a look at the OBDA system (and theory behind it) that was developed at “La Sapienza” University in Rome and Free University of BozenBolzano, Italy, which is described in [CGL+09]3.

    Its principal ingredients are:

    • Formal language: a language in the DL-Lite family, (roughly OWL 2 QL);
    • OBDA-enabled reasoner: e.g., QuOnto [ACDG+05], Quest [RMC12];
    • Data storage: an RDBMS, e.g., Oracle, PostgreSQL, DB2;
    • Developer interface: OWL ontology development environment, such as Protégé and an OBDA plugin [RMLC08], to manage the mappings and data access, and a developer API facing toward the application to be developed;
    • End-user interface: OBDA plugin for Protégé for SPARQL queries4 and results [RMLC08], and, optionally, a system for graphical querying (e.g., [CKN+10, SKZ+ss]).

    This is shown schematically in Figure 8.3.1, bottom-half.

    Screenshot (110).png

    Figure 8.3.1: OBDA approach and some practical components (bottom-half): the relational database, mappings, an ontology, a reasoner, and a user interface both to hide the technicalities from the end-user and a way for the OBDA administrator to manage the ontology and mapping layer.

    Footnotes

    2http://virtuoso.openlinksw.com/, used for, among others DBPedia

    3The latest version is Ontop [CCKE+17], which has more features, but introducing those here as well would distract for the core principles. It also compares Ontop to other OBDA and SPARQL query answering systems and lists where the system has been used in academia and industry.

    4SPARQL is a query language, alike SQL but then for querying OWL and RDF. The W3C specification of SPARQL can be found at http://www.w3.org/TR/rdf-sparql-query/.


    This page titled 9.3: An OBDA Architecture is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by Maria Keet via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.

    • Was this article helpful?