RT Journal Article
T1 A rule-based transducer forquerying incompletely aligned datasets
A1 Torre-Bastida, Ana I.
A1 Bermúdez, Jesús
A1 Illarramendi, Arantza
AB A growing number of Linked Open Data sources (from diverse provenances and about different domains) that can be freely browsed and searched to find and extract useful information have been made available. However, access to them is difficult for different reasons. This study addresses access issues concerning heterogeneity. It is common for datasets to describe the same or overlapping domains while using different vocabularies. Our study presents a transducer that transforms a SPARQL query suitably expressed in terms of the vocabularies used in a source dataset into another SPARQL query suitably expressed for a target dataset involving different vocabularies. The transformation is based on existing alignments between terms in different datasets. Whenever the transducer is unable to produce a semantically equivalent query because of the scarcity of term alignments, the transducer produces a semantic approximation of the query to avoid returning the empty answer to the user. Transformation across datasets is achieved through the management of a wide range of transformation rules. The feasibility of our proposal has been validated with a prototype implementation that processes queries that appear in well-known benchmarks and SPARQL endpoint logs. Results of the experiments show that the system is quite effective in achieving adequate transformations.
SN 1559-1131
YR 2018
FD 2018-09
LK https://hdl.handle.net/11556/4092
UL https://hdl.handle.net/11556/4092
LA eng
NO Torre-Bastida , A I , Bermúdez , J & Illarramendi , A 2018 , ' A rule-based transducer forquerying incompletely aligned datasets ' , ACM Transactions on the Web , vol. 12 , no. 4 , 23 . https://doi.org/10.1145/3228328
NO Publisher Copyright: © 2018 Association for Computing Machinery.
NO This work was supported by the FEDER/TIN2013-46238-C4-1-R project, the FEDER/TIN2016-78011-C4-2-R project, and the Iñaki Goenaga (FCT-IG) Technology Centers Foundation. This work was supported by the FEDER/TIN2013-46238-C4-1-R project, the FEDER/TIN2016-78011-C4-2-R project, and the Iñaki Goenaga (FCT-IG) Technology Centers Foundation. Authors’ addresses: A. I. Torre-Bastida, Optima Area, Tecnalia Research & Innovation, 48170 Zamudio, Bizkaia, Spain; email: isabel.torre@tecnalia.com; J. Bermúdez and A. Illarramendi, Department of Languages and Information Systems, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastián, Spain; emails: {jesus.bermudez, a.illarramendi}@ehu.eus. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2018 ACM 1559-1131/2018/09-ART23 $15.00 https://doi.org/10.1145/3228328
DS TECNALIA Publications
RD 1 sept 2024