Ontology-based data access (OBDA) is a recent paradigm for accessing large data repositories through an ontology, that is a formal description of a domain of interest. In this work, we present the Mastro plug-in for the standard ontology editor Prote´ge´, which allows users to create a full OBDA specification and pose SPARQL queries over the ontology language to extract data from the underlying data sources.
Ontology-based Data Access (OBDA) is a recent paradigm for accessing data sources
through the mediation of a concentual domain view, given in terms of an ontology [
Mastro is developed by OBDA Systems1 and Sapienza University of Rome, and
has been used in recent years in numerous projects with important business partners
from the private and public sectors [
Ontologies in Mastro are specified through languages belonging to the DL-Lite [
To illustrate the main features of the Mastro Prote´ge´ plug-in, we will invite attendees of the demo to experiment it on an OBDA specification extracted from Sapientia,
the Ontology of Multi-dimensional Research Assessment, developed within a project
funded by Sapienza University of Rome [
2
In this section, we provide a brief overview of the theoretical background of the OBDA approach, and introduce the main functionalities of the Mastro Prote´ge´ plug-in.
An OBDA specification is a triple hO; M; Di, where O is a Description Logic
ontology; D is a relational database which models the resources where data are stored;
and M is a set of mapping assertions. In Mastro, O is expressed in a logic of the
DLLite family [
The partition of M in ontology predicate mappings and SQL views allows to limit the size of the final rewritten query, and to exploit further optimizations of the rewritten query based on particular assertions that the OBDA designer can specify over the views. For instance, the designer can specify inclusion assertions between (projections of) the view predicates, which are exploited by Mastro in the rewriting process for eliminating queries contained into other queries.
Mastro’s plug-in for Prote´ge´ provides the user with a fullfledged environment to
define an OBDA specification for Mastro, and to access its query answering service. Along
with these core features, the plug-in is equipped with other functionalities among which
are: (i) the approximation module that is based on the semantic approach presented
in [
The components of Mastro’s plug-in are organized in five sub-tabs under the main Mastro tab, one item in the “Reasoner” menu´, and one “Mastro” menu´ item. Below we briefly describe each component.
Configuration. The Configuration sub-tab is used to create, open, and save a mapping specification, and to define the jdbc parameter connections to the source relational database, and to a database which Mastro uses handle query executions and to store all their information, e.g., results, execution time, ontology and mapping rewritings, and Mastro configuration parameters.
SQL Views. The SQL views sub-tab is used to create and inspect the views defined in the specification, and to specify assertions over these views, i.e., inclusion assertions, disjointness assertions, and key dependency assertions. Each view is defined by choosing its name and the SQL query code.
Mappings. The Mappings sub-tab is used to create and inspect the ontology predicate mappings in the specification, and to define the IRI templates that Mastro uses to build the answers from the data in the data source. Each ontology predicate mapping is identified by an ID, and contains the ontology predicate that is being mapped, a conjunctive query over the SQL views, and, optionally, a description.
SPARQL Query. The SPARQL Query sub-tab allows to define and execute a SPARQL query through Mastro over the ontology. Once the query has been executed, the user can consult its results and its ontology and mapping rewritings, and export the results in RDF or CSV formats. The user can also save the query into a catalog, together with a description. The catalog is managed through a catalog file which can be loaded , exported, and edited in the sub-tab. Additionally, Mastro saves all query executions into an execution log, allowing the user to visualize those of the selected query. SPARQL Query Execution Log. The SPARQL Query Execution Log sub-tab provides information regarding all executions of SPARQL queries over an OBDA specification. The data shown in the log can be exported, and the queries re-executed.
The items in the Mastro menu´ instead allow to see the details of the approximation performed by the semantic approximation module (Approximation details), in terms of approximated, translated, and rejected axioms of the original OWL 2 ontology, to access a panel where Mastro’s optimizations can be configured (Mastro properties), to export Mastro’s mappings in R2RML (Export mappings to R2RML), and to consult a tutorial of the Mastro plug-in (Help). 4
We demonstrate the Mastro Prote´ge´ plug-in through the Ontology of Multi-dimensional
Research Assessment, or Sapientia [
Sapientia models aspects of assessing research activities and their impact on human knowledge and the economic system. For example, it deals with inter-relationships between research activities, between research activities and peoples personal knowledge, and between research activities and other missions of individuals and institutions. The ontology is composed of fourteen modules, which formalize a wide array of activities, ranging from teaching, publishing, and research, to funding and preservation.
In the project, the adoption of the OBDA approach presents several advantages with respect to traditional data integration, in particular with respect to conceptual access to data, re-usability, documentation and standardization, flexibility, and extensibility.
During the demonstration, attendees will be able to inspect, query and edit the Sapientia OBDA specification through the Mastro plug-in. Initially, we will show how a user can inspect and edit the ontology through the features offered by Prote´ge´. Then, we will introduce the Mappings and SQL Views tabs, illustrating how the ontology is linked to the data sources through the mapping assertions, and showing how to edit or create new mappings and views. Furthermore, we highlight all the querying functionalities offered by the plugin through the SPARQL query tab and its execution log. Lastly, we will show attendees the details of the approximation procedure of OWL 2 into DL-Lite. Acknowledgments. Work supported by MIUR under the SIR project “MODEUS” grant n. RBSI14TQHQ.