no code implementations • 17 Oct 2023 • Linfang Ding, Guohui Xiao, Albulen Pano, Mattia Fumagalli, Dongsheng Chen, Yu Feng, Diego Calvanese, Hongchao Fan, Liqiu Meng
Moreover, embracing KGs makes it easier to integrate with other spatial data sources, e. g., OpenStreetMap and existing (Geo)KGs (e. g., Wikidata, DBPedia, and GeoNames), and to perform queries combining information from multiple data sources.
no code implementations • 9 Apr 2021 • Sihem Amer-Yahia, Georgia Koutrika, Frederic Bastian, Theofilos Belmpas, Martin Braschler, Ursin Brunner, Diego Calvanese, Maximilian Fabricius, Orest Gkini, Catherine Kosten, Davide Lanti, Antonis Litke, Hendrik Lücke-Tieke, Francesco Alessandro Massucci, Tarcisio Mendes de Farias, Alessandro Mosca, Francesco Multari, Nikolaos Papadakis, Dimitris Papadopoulos, Yogendra Patil, Aurélien Personnaz, Guillem Rull, Ana Sima, Ellery Smith, Dimitrios Skoutas, Srividya Subramanian, Guohui Xiao, Kurt Stockinger
We demonstrate that our system is uniquely accessible to a wide range of users from larger scientific communities to the public.
no code implementations • 6 Nov 2019 • Julien Corman, Guohui Xiao
More recently, OMQA has been extended to SPARQL queries, but to our knowledge, none of the efforts made in this direction (either in the literature, or the so-called SPARQL entailment regimes) is able to capture both certain answers for UCQs and the standard interpretation of SPARQL over a plain graph.
no code implementations • 1 Jun 2019 • Diego Calvanese, Davide Lanti, Ana Ozaki, Rafael Penaloza, Guohui Xiao
In particular, we investigate the problems of (i) deciding whether a provenance annotated OBDA instance entails a provenance annotated conjunctive query, and (ii) computing a polynomial representing the provenance of a query entailed by a provenance annotated OBDA instance.
no code implementations • 12 Apr 2018 • Xiangnan Ren, Olivier Curé, Hubert Naacke, Guohui Xiao
The trade-off between language expressiveness and system scalability (E&S) is a well-known problem in RDF stream reasoning.
1 code implementation • 21 Jul 2016 • Davide Lanti, Guohui Xiao, Diego Calvanese
The advantage of the approach is that the user is not required to manually input the characteristics of the data to be produced, making it particularly suitable for OBDA benchmarks, where the complexity of database schemas might pose a challenge for manual input (e. g., the NPD benchmark contains 70 tables with some containing more than 60 columns).
Databases
no code implementations • 13 May 2016 • Dag Hovland, Davide Lanti, Martin Rezk, Guohui Xiao
In Ontology Based Data Access (OBDA) users pose SPARQL queries over an ontology that lies on top of relational datasources.
no code implementations • 26 Nov 2015 • Elena Botoeva, Diego Calvanese, Valerio Santarelli, Domenico Fabio Savo, Alessandro Solimando, Guohui Xiao
Ontology-based data access (OBDA) is a novel paradigm facilitating access to relational data, realized by linking data sources to an ontology by means of declarative mappings.