Database techniques for semantics-rich semi-structured Web data
type: Dataset
description: Since the beginning of the Semantic Web, RDF and SPARQL have become the standard data model and query language to describe resources on the Web. Large amounts of RDF data are now available either as stand-alone datasets or as metadata over semi-structured documents, typically XML. The ability to apply RDF annotations over XML data emphasizes the need to represent and query data and metadata simultaneously. While significant efforts have been invested into producing and publishing annotations manually or automatically, little attention has been devoted to exploiting such data. This thesis aims at setting database foundations for the management of hybrid XML-RDF data. We present a data model capturing the structural aspects of XML data and the semantics of RDF. Our model is general enough to describe pure XML or RDF datasets, as well as RDF-annotated XML data, where any XML node can act as a resource. We also introduce the XRQ query language that combines features of both XQuery and SPARQL. XRQ not only allows querying the structure of documents and the semantics of their annotations, but also producing annotated semi-structured data on-the-fly. We introduce the problem of query composition in XRQ, and exhaustively study query evaluation techniques for XR data to demonstrate the feasibility of this data management setting. We have developed an XR platform on top of well-known data management systems for XML and RDF. The platform features several query processing algorithms, whose performance is experimentally compared. We present an application built on top of the XR platform. The application provides manual and automatic annotation tools, and an interface to query annotated Web page and publicly available XML and RDF datasets concurrently. As a generalization of RDF and SPARQL, XR and XRQ enables RDFS-type of query answering. In this respect, we present a technique to support RDFS-entailments in RDF (and by extension XR) data management systems.
identifier: NNT: 2013PA112193
issued: 2026-05-09T09:20:13.036990
language: en
modified: 2026-05-09T09:20:13.036995
contact point: Organization
  fn: CCSD
keyword: composition-de-requetes
keyword: data-models
keyword: infoeu-reposemanticsdoctoralthesis
keyword: infoinfo-ohcomputer-science-csother-csoh
keyword: langages-de-requetes
keyword: linked-data
keyword: modeles-de-donnees
keyword: optimisation-de-requetes
keyword: query-answering
keyword: query-composition
keyword: query-languages
keyword: query-optimization
keyword: rdf
keyword: reponse-aux-requetes
keyword: semantic-web
keyword: theses
keyword: web-semantique
keyword: xml
landing page: https://theses.hal.science/tel-00872883

Database techniques for semantics-rich semi-structured Web data
type: Distribution
format: HTML
issued: 2026-05-09T09:20:13.046707
modified: 2026-05-09T09:20:13.015711
access URL: https://theses.hal.science/tel-00872883

test_moissonnage_selune
type: Agent