DOCSLIB.ORG

SPARQL (SPARQL Protocol and RDF Query Language)

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
SPARQL (SPARQL Protocol and RDF Query Language) SPARQL 1 SPARQL SPARQL (pronounced "sparkle"[1] ) is an RDF query language; its name is a recursive acronym that stands for SPARQL Protocol and RDF Query Language. It was standardized by the RDF Data Access Working Group (DAWG) of the World Wide Web Consortium, and is considered a key semantic web technology. On 15 January 2008, SPARQL became an official W3C Recommendation.[2] SPARQL allows for a query to consist of triple patterns, conjunctions, disjunctions, and optional patterns.[3] Implementations for multiple programming languages exist.[4] "SPARQL will make a huge difference" according to Sir Tim Berners-Lee in a May 2006 interview.[5] There exist tools that allow one to connect and semi-automatically construct a SPARQL query for a SPARQL endpoint, for example ViziQuer.[6] Benefits SPARQL allows users to write globally unambiguous queries. For example, the following query returns names and emails of every person in the world: PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name ?email WHERE { ?person a foaf:Person. ?person foaf:name ?name. ?person foaf:mbox ?email. } ..assuming the ontologies in use to describe a person are mapped to FOAF via rules from whatever ontology the original relations were in. This illustrates the Semantic Web's vision of treating the Web as a single enormous database. Notice that this global unambiguity roots in the fact that every identifier in SPARQL, URI, is globally unambiguous, unlike "email" or "e-mail" normally used in SQL. This query can be distributed to multiple SPARQL endpoints, computed distributedly, and results gathered, a procedure known as federated query. Query Forms The SPARQL language specifies four different query variations for different purposes. SELECT query Used to extract raw values from a SPARQL endpoint, the results are returned in a table format. CONSTRUCT query Used to extract information from the SPARQL endpoint and transform the results into valid RDF. ASK query Used to provide a simple True/False result for a query on a SPARQL endpoint. DESCRIBE query Used to extract an RDF graph from the SPARQL endpoint, the contents of which is left to the endpoint to decide based on what the maintainer deems as useful information. Each of these query forms takes a WHERE block to restrict the query although in the case of the DESCRIBE query the WHERE is optional. SPARQL 2 Example Another SPARQL query example that models the question "What are all the country capitals in Africa?": PREFIX abc: <http://example.com/exampleOntology#> SELECT ?capital ?country WHERE { ?x abc:cityname ?capital ; abc:isCapitalOf ?y . ?y abc:countryname ?country ; abc:isInContinent abc:Africa . } Variables are indicated by a "?" or "$" prefix. Bindings for ?capital and the ?country will be returned. The SPARQL query processor will search for sets of triples that match these four triple patterns, binding the variables in the query to the corresponding parts of each triple. Important to note here is the "property orientation" (class matches can be conducted solely through class-attributes / properties - see Duck typing) To make queries concise, SPARQL allows the definition of prefixes and base URIs in a fashion similar to Turtle. In this query, the prefix "abc" stands for “http://example.com/exampleOntology#”. References [1] Jim Rapoza (2 May 2006). "SPARQL Will Make the Web Shine" (http:/ / www. eweek. com/ article2/ 0,1759,1965980,00. asp). eWeek. Retrieved 2007-01-17. [2] "W3C Semantic Web Activity News - SPARQL is a Recommendation" (http:/ / www. w3. org/ blog/ SW/ 2008/ 01/ 15/ sparql_is_a_recommendation). W3.org. 2008-01-15. Retrieved 2009-10-01. [3] "XML and Web Services In The News" (http:/ / www. xml. org/ xml/ news/ archives/ archive. 10062006. shtml#5). xml.org. 6 October 2006. Retrieved 2007-01-17. [4] "SparqlImplementations - ESW Wiki" (http:/ / esw. w3. org/ topic/ SparqlImplementations). Esw.w3.org. Retrieved 2009-10-01. [5] Reuters (22 May 2006). "Berners-Lee looks for Web's big leap" (http:/ / web. archive. org/ web/ 20070930221904/ http:/ / news. zdnet. co. uk/ internet/ 0,1000000097,39270671,00. htm). zdnet.co.uk. Archived from the original (http:/ / news. zdnet. co. uk/ internet/ 0,1000000097,39270671,00. htm) on 2007-09-30. Retrieved 2007-01-17. [6] "ViziQuer a tool to construct SPARQL queries automaticly" (http:/ / viziquer. lumii. lv/ ). lumii.lv. Retrieved 2011-02-25. External links • W3C SPARQL Working Group (http:/ / www. w3. org/ 2001/ sw/ DataAccess/ ) (was RDF Data Access Working Group) • SPARQL Query language (http:/ / www. w3. org/ TR/ rdf-sparql-query/ ) • SPARQL Protocol (http:/ / www. w3. org/ TR/ rdf-sparql-protocol/ ) • SPARQL Query XML Results Format (http:/ / www. w3. org/ TR/ rdf-sparql-XMLres/ ) • SPARQL Tutorial (http:/ / openjena. org/ ARQ/ Tutorial/ index. html) • SPARQL Examples (http:/ / en. sparql. pro) Article Sources and Contributors 3 Article Sources and Contributors SPARQL Source: http://en.wikipedia.org/w/index.php?oldid=440661904 Contributors: A5b, Adrian.walker, Afreet, Akampman, AndersFeder, Andy Dingley, Beland, Brettz9, Cburnett, Chris the speller, Danja, Dmccreary, Doctus, EricP, Fingerz, Fleminra, Gthb, Holygoat, Jamelan, Jasy jatere, Jmrose, Jodi.a.schneider, John Vandenberg, JzG, Karima Rafes, Kcoy, Kennyluck, Khazar, KingsleyIdehen, KnightRider, Koavf, Lastorset, LeeFeigenbaum, Mdd, MeltBanana, Mortenf, Newty25, Proofreader77, Ricmitch, Risi, Rjwilmsi, Robertvan1, SarekOfVulcan, Shepard, Suruena, Tchetchenko, Theweirdguy, Thorwald, Thumperward, Tulcod, Ultimatewisdom, Universimmedia, Wesley, Woodart, Yaron K., Zviedris, 63 anonymous edits License Creative Commons Attribution-Share Alike 3.0 Unported http:/ / creativecommons. org/ licenses/ by-sa/ 3. 0/.
Load more

Recommended publications
  • Basic Querying with SPARQL
    Basic Querying with SPARQL Andrew Weidner Metadata Services Coordinator SPARQL SPARQL SPARQL SPARQL SPARQL Protocol SPARQL SPARQL Protocol And SPARQL SPARQL Protocol And RDF SPARQL SPARQL Protocol And RDF Query SPARQL SPARQL Protocol And RDF Query Language SPARQL SPARQL Protocol And RDF Query Language SPARQL Query SPARQL Query Update SPARQL Query Update - Insert triples SPARQL Query Update - Insert triples - Delete triples SPARQL Query Update - Insert triples - Delete triples - Create graphs SPARQL Query Update - Insert triples - Delete triples - Create graphs - Drop graphs Query RDF Triples Query RDF Triples Triple Store Query RDF Triples Triple Store Data Dump Query RDF Triples Triple Store Data Dump Subject – Predicate – Object Query Subject – Predicate – Object ?s ?p ?o Query Dog HasName Cocoa Subject – Predicate – Object ?s ?p ?o Query Cocoa HasPhoto ------- Subject – Predicate – Object ?s ?p ?o Query HasURL http://bit.ly/1GYVyIX Subject – Predicate – Object ?s ?p ?o Query ?s ?p ?o Query SELECT ?s ?p ?o Query SELECT * ?s ?p ?o Query SELECT * WHERE ?s ?p ?o Query SELECT * WHERE { ?s ?p ?o } Query select * WhErE { ?spiderman ?plays ?oboe } http://deathbattle.wikia.com/wiki/Spider-Man http://www.mmimports.com/wp-content/uploads/2014/04/used-oboe.jpg Query SELECT * WHERE { ?s ?p ?o } Query SELECT * WHERE { ?s ?p ?o } Query SELECT * WHERE { ?s ?p ?o } Query SELECT * WHERE { ?s ?p ?o } LIMIT 10 SELECT * WHERE { ?s ?p ?o } LIMIT 10 http://dbpedia.org/snorql SELECT * WHERE { ?s ?p ?o } LIMIT 10 http://dbpedia.org/snorql SELECT * WHERE { ?s
    [Show full text]
  • Mapping Spatiotemporal Data to RDF: a SPARQL Endpoint for Brussels
    International Journal of Geo-Information Article Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels Alejandro Vaisman 1, * and Kevin Chentout 2 1 Instituto Tecnológico de Buenos Aires, Buenos Aires 1424, Argentina 2 Sopra Banking Software, Avenue de Tevuren 226, B-1150 Brussels, Belgium * Correspondence: [email protected]; Tel.: +54-11-3457-4864 Received: 20 June 2019; Accepted: 7 August 2019; Published: 10 August 2019 Abstract: This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be displayed on a map. This endpoint is implemented using Strabon, a spatiotemporal RDF triple store built by extending the RDF store Sesame. The first part of the paper describes how R2RML is adapted to allow producing spatial RDF data and to support XML data sources. These techniques are then used to map data about cultural events and public transport in Brussels into RDF. Spatial data are stored in the form of stRDF triples, the format required by Strabon. In addition, the endpoint is enriched with external data obtained from the Linked Open Data Cloud, from sites like DBpedia, Geonames, and LinkedGeoData, to provide context for analysis.
    [Show full text]
  • Validating RDF Data Using Shapes
    83 Validating RDF data using Shapes a Jose Emilio Labra Gayo ​ ​ a University​ of Oviedo, Spain Abstract RDF forms the keystone of the Semantic Web as it enables a simple and powerful knowledge representation graph based data model that can also facilitate integration between heterogeneous sources of information. RDF based applications are usually accompanied with SPARQL stores which enable to efficiently manage and query RDF data. In spite of its well known benefits, the adoption of RDF in practice by web programmers is still lacking and SPARQL stores are usually deployed without proper documentation and quality assurance. However, the producers of RDF data usually know the implicit schema of the data they are generating, but they don't do it traditionally. In the last years, two technologies have been developed to describe and validate RDF content using the term shape: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL). We will present a motivation for their appearance and compare them, as well as some applications and tools that have been developed. Keywords RDF, ShEx, SHACL, Validating, Data quality, Semantic web 1. Introduction In the tutorial we will present an overview of both RDF is a flexible knowledge and describe some challenges and future work [4] representation language based of graphs which has been successfully adopted in semantic web 2. Acknowledgements applications. In this tutorial we will describe two languages that have recently been proposed for This work has been partially funded by the RDF validation: Shape Expressions (ShEx) and Spanish Ministry of Economy, Industry and Shapes Constraint Language (SHACL).ShEx was Competitiveness, project: TIN2017-88877-R proposed as a concise and intuitive language for describing RDF data in 2014 [1].
    [Show full text]
  • Semantics Developer's Guide
    MarkLogic Server Semantic Graph Developer’s Guide 2 MarkLogic 10 May, 2019 Last Revised: 10.0-8, October, 2021 Copyright © 2021 MarkLogic Corporation. All rights reserved. MarkLogic Server MarkLogic 10—May, 2019 Semantic Graph Developer’s Guide—Page 2 MarkLogic Server Table of Contents Table of Contents Semantic Graph Developer’s Guide 1.0 Introduction to Semantic Graphs in MarkLogic ..........................................11 1.1 Terminology ..........................................................................................................12 1.2 Linked Open Data .................................................................................................13 1.3 RDF Implementation in MarkLogic .....................................................................14 1.3.1 Using RDF in MarkLogic .........................................................................15 1.3.1.1 Storing RDF Triples in MarkLogic ...........................................17 1.3.1.2 Querying Triples .......................................................................18 1.3.2 RDF Data Model .......................................................................................20 1.3.3 Blank Node Identifiers ..............................................................................21 1.3.4 RDF Datatypes ..........................................................................................21 1.3.5 IRIs and Prefixes .......................................................................................22 1.3.5.1 IRIs ............................................................................................22
    [Show full text]
  • Computational Integrity for Outsourced Execution of SPARQL Queries
    Computational integrity for outsourced execution of SPARQL queries Serge Morel Student number: 01407289 Supervisors: Prof. dr. ir. Ruben Verborgh, Dr. ir. Miel Vander Sande Counsellors: Ir. Ruben Taelman, Joachim Van Herwegen Master's dissertation submitted in order to obtain the academic degree of Master of Science in Computer Science Engineering Academic year 2018-2019 Computational integrity for outsourced execution of SPARQL queries Serge Morel Student number: 01407289 Supervisors: Prof. dr. ir. Ruben Verborgh, Dr. ir. Miel Vander Sande Counsellors: Ir. Ruben Taelman, Joachim Van Herwegen Master's dissertation submitted in order to obtain the academic degree of Master of Science in Computer Science Engineering Academic year 2018-2019 iii c Ghent University The author(s) gives (give) permission to make this master dissertation available for consultation and to copy parts of this master dissertation for personal use. In the case of any other use, the copyright terms have to be respected, in particular with regard to the obligation to state expressly the source when quoting results from this master dissertation. August 16, 2019 Acknowledgements The topic of this thesis concerns a rather novel and academic concept. Its research area has incredibly talented people working on a very promising technology. Understanding the core principles behind proof systems proved to be quite difficult, but I am strongly convinced that it is a thing of the future. Just like the often highly-praised artificial intelligence technology, I feel that verifiable computation will become very useful in the future. I would like to thank Joachim Van Herwegen and Ruben Taelman for steering me in the right direction and reviewing my work quickly and intensively.
    [Show full text]
  • RDF Query Languages Need Support for Graph Properties
    RDF Query Languages Need Support for Graph Properties Renzo Angles1, Claudio Gutierrez1, and Jonathan Hayes1,2 1 Dept. of Computer Science, Universidad de Chile 2 Dept. of Computer Science, Technische Universit¨at Darmstadt, Germany {rangles,cgutierr,jhayes}@dcc.uchile.cl Abstract. This short paper discusses the need to include into RDF query languages the ability to directly query graph properties from RDF data. We study the support that current RDF query languages give to these features, to conclude that they are currently not supported. We propose a set of basic graph properties that should be added to RDF query languages and provide evidence for this view. 1 Introduction One of the main features of the Resource Description Framework (RDF) is its ability to interconnect information resources, resulting in a graph-like structure for which connectivity is a central notion [GLMB98]. As we will argue, basic concepts of graph theory such as degree, path, and diameter play an important role for applications that involve RDF querying. Considering the fact that the data model influences the set of operations that should be provided by a query language [HBEV04], it follows the need for graph operations support in RDF query languages. For example, the query “all relatives of degree 1 of Alice”, submitted to a genealogy database, amounts to retrieving the nodes adjacent to a resource. The query “are suspects A and B related?”, submitted to a police database, asks for any path connecting these resources in the (RDF) graph that is stored in this database. The query “what is the Erd˝osnumber of Alberto Mendelzon”, submitted to (a RDF version of) DBLP, asks simply for the length of the shortest path between the nodes representing Erd˝osand Mendelzon.
    [Show full text]
  • Introduction Vocabulary an Excerpt of a Dbpedia Dataset
    D2K Master Information Integration Université Paris Saclay Practical session (2): SPARQL Sources: http://liris.cnrs.fr/~pchampin/2015/udos/tuto/#id1 https://www.w3.org/TR/2013/REC-sparql11-query-20130321/ Introduction For this practical session, we will use the DBPedia SPARQL access point, and to access it, we will use the Yasgui online client. By default, Yasgui (http://yasgui.org/) is configured to query DBPedia (http://wiki.dbpedia.org/), which is appropriate for our tutorial, but keep in mind that: - Yasgui is not linked to DBpedia, it can be used with any SPARQL access point; - DBPedia is not related to Yasgui, it can be queried with any SPARQL compliant client (in fact any HTTP client that is not very configurable). Vocabulary An excerpt of a dbpedia dataset The vocabulary of DBPedia is very large, but in this tutorial we will only need the IRIs below. foaf:name Propriété Nom d’une personne (entre autre) dbo:birthDate Propriété Date de naissance d’une personne dbo:birthPlace Propriété Lieu de naissance d’une personne dbo:deathDate Propriété Date de décès d’une personne dbo:deathPlace Propriété Lieu de décès d’une personne dbo:country Propriété Pays auquel un lieu appartient dbo:mayor Propriété Maire d’une ville dbr:Digne-les-Bains Instance La ville de Digne les bains dbr:France Instance La France -1- /!\ Warning: IRIs are case-sensitive. Exercises 1. Display the IRIs of all Dignois of origin (people born in Digne-les-Bains) Graph Pattern Answer: PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX owl: <http://www.w3.org/2002/07/owl#> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX skos: <http://www.w3.org/2004/02/skos/core#> PREFIX dc: <http://purl.org/dc/elements/1.1/> PREFIX dbo: <http://dbpedia.org/ontology/> PREFIX dbr: <http://dbpedia.org/resource/> PREFIX db: <http://dbpedia.org/> SELECT * WHERE { ?p dbo:birthPlace dbr:Digne-les-Bains .
    [Show full text]
  • Supporting SPARQL Update Queries in RDF-XML Integration *
    Supporting SPARQL Update Queries in RDF-XML Integration * Nikos Bikakis1 † Chrisa Tsinaraki2 Ioannis Stavrakantonakis3 4 Stavros Christodoulakis 1 NTU Athens & R.C. ATHENA, Greece 2 EU Joint Research Center, Italy 3 STI, University of Innsbruck, Austria 4 Technical University of Crete, Greece Abstract. The Web of Data encourages organizations and companies to publish their data according to the Linked Data practices and offer SPARQL endpoints. On the other hand, the dominant standard for information exchange is XML. The SPARQL2XQuery Framework focuses on the automatic translation of SPARQL queries in XQuery expressions in order to access XML data across the Web. In this paper, we outline our ongoing work on supporting update queries in the RDF–XML integration scenario. Keywords: SPARQL2XQuery, SPARQL to XQuery, XML Schema to OWL, SPARQL update, XQuery Update, SPARQL 1.1. 1 Introduction The SPARQL2XQuery Framework, that we have previously developed [6], aims to bridge the heterogeneity issues that arise in the consumption of XML-based sources within Semantic Web. In our working scenario, mappings between RDF/S–OWL and XML sources are automatically derived or manually specified. Using these mappings, the SPARQL queries are translated on the fly into XQuery expressions, which access the XML data. Therefore, the current version of SPARQL2XQuery provides read-only access to XML data. In this paper, we outline our ongoing work on extending the SPARQL2XQuery Framework towards supporting SPARQL update queries. Both SPARQL and XQuery have recently standardized their update operation seman- tics in the SPARQL 1.1 and XQuery Update Facility, respectively. We have studied the correspondences between the update operations of these query languages, and we de- scribe the extension of our mapping model and the SPARQL-to-XQuery translation algorithm towards supporting SPARQL update queries.
    [Show full text]
  • Querying Distributed RDF Data Sources with SPARQL
    Querying Distributed RDF Data Sources with SPARQL Bastian Quilitz and Ulf Leser Humboldt-Universit¨at zu Berlin {quilitz,leser}@informatik.hu-berlin.de Abstract. Integrated access to multiple distributed and autonomous RDF data sources is a key challenge for many semantic web applications. As a reaction to this challenge, SPARQL, the W3C Recommendation for an RDF query language, supports querying of multiple RDF graphs. However, the current standard does not provide transparent query fed- eration, which makes query formulation hard and lengthy. Furthermore, current implementations of SPARQL load all RDF graphs mentioned in a query to the local machine. This usually incurs a large overhead in network traffic, and sometimes is simply impossible for technical or le- gal reasons. To overcome these problems we present DARQ, an engine for federated SPARQL queries. DARQ provides transparent query ac- cess to multiple SPARQL services, i.e., it gives the user the impression to query one single RDF graph despite the real data being distributed on the web. A service description language enables the query engine to decompose a query into sub-queries, each of which can be answered by an individual service. DARQ also uses query rewriting and cost-based query optimization to speed-up query execution. Experiments show that these optimizations significantly improve query performance even when only a very limited amount of statistical information is available. DARQ is available under GPL License at http://darq.sf.net/. 1 Introduction Many semantic web applications require the integration of data from distributed, autonomous data sources. Until recently it was rather difficult to access and query data in such a setting because there was no standard query language or interface.
    [Show full text]
  • SPARQL Query Processing with Conventional Relational Database Systems
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by e-Prints Soton SPARQL query processing with conventional relational database systems Steve Harris IAM, University of Southampton, UK [email protected] Abstract. This paper describes an evolution of the 3store RDF storage system, extended to provide a SPARQL query interface and informed by lessons learned in the area of scalable RDF storage. 1 Introduction The previous versions of the 3store [1] RDF triplestore were optimised to pro- vide RDQL [2] (and to a lesser extent OKBC [3]) query services, and had no efficient internal representation of the language and datatype extensions from RDF 2004 [4]. This revision of the 3store software adds support for the SPARQL [5] query language, RDF datatype and language support. Some of the representation choices made in the implementation of the previous versions of 3store made efficient support for SPARQL queries difficult. Therefore, a new underlying rep- resentation for the RDF statements was required, as well as a new query en- gine capable of supporting the additional features of SPARQL over RDQL and OKBC. 2 Related Work The SPARQL query language is still at an early stage of standardisation, but there are already other implementations. 2.1 Federate Federate [6] is a relational database gateway, which maps RDF queries to existing database structures. Its goal is for compatibility with existing relational database systems, rather than as a native RDF storage and querying engine. However, it shares the approach of pushing as much processing down into the database engine as possible, though the algorithms employed are necessarily different.
    [Show full text]
  • Web and Semantic Web Query Languages: a Survey
    Web and Semantic Web Query Languages: A Survey James Bailey1, Fran¸coisBry2, Tim Furche2, and Sebastian Schaffert2 1 NICTA Victoria Laboratory Department of Computer Science and Software Engineering The University of Melbourne, Victoria 3010, Australia http://www.cs.mu.oz.au/~jbailey/ 2 Institute for Informatics,University of Munich, Oettingenstraße 67, 80538 M¨unchen, Germany http://pms.ifi.lmu.de/ Abstract. A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This ar- ticle introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced us- ing common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion. 1 Introduction The Semantic Web Vision A major endeavour in current Web research is the so-called Semantic Web, a term coined by W3C founder Tim Berners-Lee in a Scientific American article describing the future of the Web [37]. The Semantic Web aims at enriching Web data (that is usually represented in (X)HTML or other XML formats) by meta-data and (meta-)data processing specifying the “meaning” of such data and allowing Web based systems to take advantage of “intelligent” reasoning capabilities. To quote Berners-Lee et al. [37]: “The Semantic Web will bring structure to the meaningful content of Web pages, creating an environment where software agents roaming from page to page can readily carry out sophisticated tasks for users.” The Semantic Web meta-data added to today’s Web can be seen as advanced semantic indices, making the Web into something rather like an encyclopedia.
    [Show full text]
  • XML-Based RDF Data Management for Efficient Query Processing
    XML-Based RDF Data Management for Efficient Query Processing Mo Zhou Yuqing Wu Indiana University, USA Indiana University, USA [email protected] [email protected] Abstract SPARQL[17] is a W3C recommended RDF query language. A The Semantic Web, which represents a web of knowledge, offers SPARQL query contains a collection of triples with variables called new opportunities to search for knowledge and information. To simple access patterns which form graph patterns for describing harvest such search power requires robust and scalable data repos- query requirements. For SELECT ?t example, the SPARQL itories that can store RDF data and support efficient evaluation of WHERE {?p type Person. ?r ?x ?t. SPARQL queries. Most of the existing RDF storage techniques rely ?p name ?n. ?p write ?r} query on the left re- on relation model and relational database technologies for these trieves all properties of tasks. They either keep the RDF data as triples, or decompose it reviews written by a person whose name is known. into multiple relations. The mis-match between the graph model The needs to develop applications on the Semantic Web and sup- of the RDF data and the rigid 2D tables of relational model jeop- port search in RDF graphs call for RDF repositories to be reliable, ardizes the scalability of such repositories and frequently renders a robust and efficient in answering SPARQL queries. As in the con- repository inefficient for some types of data and queries. We pro- text of RDB and XML, the selection of storage models is critical to pose to decompose RDF graph into a forest of semantically cor- a data repository as it is the dominating factor to determine how to related XML trees, store them in an XML repository and rewrite evaluate queries and how the system behaves when it scales up.
    [Show full text]