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Unifying Faceted Search and Analytics over RDF Knowledge Graphs

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Abstract

The formulation of analytical queries over Knowledge Graphs in RDF is a challenging task that presupposes familiarity with the syntax of the corresponding query languages and the contents of the graph. To alleviate this problem, we introduce a model for aiding users in formulating analytic queries over complex, i.e., not necessarily star schema-based, RDF Knowledge Graphs. To come up with an intuitive interface, we leverage the familiarity of users with Faceted Search systems. In particular, we start from a general model for Faceted Search over RDF data, and we extend it with actions that enable users to formulate analytic queries, too. Thus, the proposed model can be used not only for formulating analytic queries but also for exploratory purposes, i.e., for locating the desired resources in a Faceted Search manner. We describe the model from various perspectives, i.e., (1) we propose a generic user interface for intuitively analyzing RDF Knowledge Graphs, (2) we define formally the state space of the interaction model and the required algorithms for producing the user interface actions, (3) we present an implementation of the model that showcases its feasibility, and (4) we discuss the results of an evaluation with users that provides evidence for the acceptance of the method by users. Apart from being intuitive for end users, another distinctive characteristic of the proposed model is that it allows the gradual formulation of complex analytic queries (including nested ones).

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Data availability

The dataset used in the running example as well as the running system is publicly accessible.

Notes

  1. https://en.wikipedia.org/wiki/RDF_Schema.

  2. https://www.w3.org/standards/semanticweb/inference.

  3. http://data.persee.fr/explore/sparklis/?lang=en.

  4. https://team.inria.fr/oak/projects/warg/.

  5. https://www.w3.org/TR/vocab-data-cube/.

  6. i.e., the results of the SPARQL query “select ?x where { ?x rdf:type owl:NamedIndividual. }.”

  7. The reflexive and transitive reduction in a binary relation R is the smallest relation R’ such as both R and R’ have the same reflexive and transitive closure.

  8. http://docs.openlinksw.com/virtuoso/.

  9. https://angular.io/.

  10. The deployment of the system that was used is accessible at https://demos.isl.ics.forth.gr/rdf-analytics.

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Acknowledgements

Many thanks to Alexandros Perrakis for proof reading the entire paper and for developing the second implementation of the model.

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FORTH-ICS.

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Authors and Affiliations

  1. Institute of Computer Science, FORTH-ICS, Vasilika Vouton, 70013, Heraklion, Crete, Greece

    Maria-Evangelia Papadaki & Yannis Tzitzikas

  2. Department of Computer Science, University of Crete, Panepistimioupoli Vouton, 70013, Heraklion, Crete, Greece

    Maria-Evangelia Papadaki & Yannis Tzitzikas

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  1. Maria-Evangelia Papadaki
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All authors contributed to the study conception, design, and writing of this work. The implementation of the system was done by Maria-Evangelia Papadaki.

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Correspondence to Maria-Evangelia Papadaki.

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Papadaki, ME., Tzitzikas, Y. Unifying Faceted Search and Analytics over RDF Knowledge Graphs. Knowl Inf Syst (2024). https://doi.org/10.1007/s10115-024-02076-9

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