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Semantic query
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<h2 id="background">Background</h2> <p><a href="/facts/Relational_database/pEKGmJLy">Relational databases</a> represent all relationships between data in an <i>implicit</i> manner only.<a class="footnote-ref" id="fnref:3" href="#fn:3"><sup>3</sup></a><a class="footnote-ref" id="fnref:4" href="#fn:4"><sup>4</sup></a> For example, the relationships between customers and products (stored in two content-tables and connected with an additional link-table) only come into existence in a query statement (<a href="/facts/SQL/UjQLJcYm">SQL</a> in the case of relational databases) written by a developer. Writing the query demands exact knowledge of the <a href="/facts/Database_schema/DBq8fooY">database schema</a>.<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a><a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a> </p><p><a href="/facts/Linked_Data/XKhE5aTQ">Linked-Data</a> represent all relationships between data in an <i>explicit</i> manner. In the above example, no query code needs to be written. The correct product for each customer can be fetched automatically. Whereas this simple example is trivial, the real power of linked-data comes into play when a <i>network of information</i> is created (customers with their geo-spatial information like city, state and country; products with their categories within sub- and super-categories). Now the system can automatically answer more complex queries and analytics that look for the connection of a particular location with a product category. The development effort for this query is omitted. Executing a semantic query is conducted by <i>walking</i> the network of information and finding matches (also called <i>Data Graph Traversal</i>). </p><p>Another important aspect of semantic queries is that the type of the relationship can be used to incorporate intelligence into the system. The relationship between a customer and a product has a fundamentally different nature than the relationship between a neighbourhood and its city. The latter enables the semantic query engine to <i>infer</i> that a customer <i>living in Manhattan is also living in New York City</i> whereas other relationships might have more complicated patterns and "contextual analytics". This process is called inference or reasoning and is the ability of the software to derive new information based on given facts. </p> <h2 id="articles">Articles</h2> <ul><li>Velez, Golda (2008). <a href="http://www.wallstreetandtech.com/data-management/semantics-help-wall-street-cope-with-data-overload/d/d-id/1259662.html">"Semantics Help Wall Street Cope With Data Overload"</a>. wallstreetandtech.com.</li> <li>Zhifeng, Xiao (2009). "Spatial information semantic query based on SPARQL". In Liu, Yaolin; Tang, Xinming (eds.). <i>International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining</i>. Vol. 7492. SPIE. pp. 74921P. <a href="/facts/Bibcode_(identifier)/9HtdQSGB">Bibcode</a>:<a href="https://ui.adsabs.harvard.edu/abs/2009SPIE.7492E..60X">2009SPIE.7492E..60X</a>. <a href="/facts/Doi_(identifier)/muM9Etpq">doi</a>:<a href="https://doi.org/10.1117%2F12.838556">10.1117/12.838556</a>. <a href="/facts/S2CID_(identifier)/ldJsHa2Y">S2CID</a> <a href="https://api.semanticscholar.org/CorpusID:62191842">62191842</a>.</li> <li>Aquin, Mathieu (2010). <a href="http://www.semantic-web-journal.net/sites/default/files/swj96_1.pdf">"Watson, more than a Semantic Web search engine"</a> (PDF). Semantic Web Journal.</li> <li>Dworetzky, Tom (2011). <a href="http://www.ibtimes.com/how-siri-works-iphones-brain-comes-natural-language-processing-stanford-professors-teach-free-online">"How Siri Works: iPhone's 'Brain' Comes from Natural Language Processing"</a>. <i>International Business Times</i>.</li> <li>Horwitt, Elisabeth (2011). <a href="http://www.computerworld.com/s/article/9209118/The_semantic_Web_gets_down_to_businessarticleID=208700210&pgno=2">"The semantic Web gets down to business"</a>. computerworld.com.</li> <li>Rodriguez, Marko (2011). <a href="http://markorodriguez.com/2011/06/15/graph-pattern-matching-with-gremlin-1-1/">"Graph Pattern Matching with Gremlin"</a>. <i>Marko A. Rodriguez</i>. markorodriguez.com on Graph Computing.</li> <li>Sequeda, Juan (2011). <a href="http://www.cambridgesemantics.com/semantic-university/sparql-nuts-and-bolts">"SPARQL Nuts & Bolts"</a>. Cambridge Semantics.</li> <li>Freitas, Andre (2012). <a href="https://www.deri.ie/sites/default/files/publications/freitas_ic_12.pdf">"Querying Heterogeneous Datasets on the Linked Data Web"</a> (PDF). IEEE Internet Computing.</li> <li>Kauppinen, Tomi (2012). <a href="http://linkedscience.org/tools/sparql-package-for-r/tutorial-on-sparql-package-for-r/">"Using the SPARQL Package in R to handle Spatial Linked Data"</a>. linkedscience.org.</li> <li>Lorentz, Alissa (2013). <a href="https://www.wired.com/2013/04/with-big-data-context-is-a-big-issue/">"With Big Data, Context is a Big Issue"</a>. Wired.</li></ul> <h2 id="see-also">See also</h2> <ul><li><a href="/facts/Attention/pleJPaeQ">Attention</a></li> <li><a href="/facts/Dataspaces/j4ynMytG">Dataspaces</a></li> <li><a href="/facts/Knowledge_Representation/9lnzyILD">Knowledge Representation</a></li> <li><a href="/facts/Linked_Data/XKhE5aTQ">Linked Data</a></li> <li><a href="/facts/Ontology_alignment/Szbtc6zR">Ontology alignment</a></li> <li><a href="/facts/Philosophy/zAH5PVD6">Philosophy</a></li> <li><a href="/facts/Semantic_Integration/IGcgnczH">Semantic Integration</a></li> <li><a href="/facts/Semantic_publishing/cML1yAN0">Semantic publishing</a></li> <li><a href="/facts/Semantics_of_Business_Vocabulary_and_Business_Rules/Yw3lyUGN">Semantics of Business Vocabulary and Business Rules</a></li> <li><a href="/facts/SPARQL/XPP7pFDJ">SPARQL</a></li></ul> <h2 id="external-links">External links</h2> <ul><li><a href="http://www.w3.org/standards/semanticweb/query">W3C Semantic Web Standards - Query</a></li></ul> <h2 id="references">References</h2> <ol> <li id="fn:1"><p>"Introducing SPARQL: Querying the Semantic Web". XML.com. 2005. <a href="http://www.xml.com/pub/a/2005/11/16/introducing-sparql-querying-semantic-web-tutorial.html" target="_blank">http://www.xml.com/pub/a/2005/11/16/introducing-sparql-querying-semantic-web-tutorial.html</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li> <li id="fn:2"><p>"SPARQL Query Language for RDF". W3C. 2008. <a href="http://www.w3.org/TR/rdf-sparql-query" target="_blank">http://www.w3.org/TR/rdf-sparql-query</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li> <li id="fn:3"><p>Semantic queries in databases: problems and challenges. Cikm '09. ACM Digital Library. 2009. pp. 1505–1508. doi:10.1145/1645953.1646157. ISBN 9781605585123. S2CID 1578867. <a href="9781605585123" target="_blank">9781605585123</a> <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li> <li id="fn:4"><p>"Karma: A System for Mapping Structured Sources into the Semantic Web" (PDF). eswc-conferences.org. 2012. <a href="http://2012.eswc-conferences.org/sites/default/files/eswc2012_submission_357.pdf" target="_blank">http://2012.eswc-conferences.org/sites/default/files/eswc2012_submission_357.pdf</a> <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li> <li id="fn:5"><p>"A Scalable Approach to Learn Semantic Models of Structured Sources" (PDF). 8th IEEE International Conference on Semantic Computing. 2014. <a href="http://www-scf.usc.edu/~taheriya/papers/taheriyan14-icsc-paper.pdf" target="_blank">http://www-scf.usc.edu/~taheriya/papers/taheriyan14-icsc-paper.pdf</a> <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li> <li id="fn:6"><p>"Semantics for Big Data Integration and Analysis" (PDF). AAAI Fall Symposium on Semantics for Big Data. 2013. <a href="http://www.isi.edu/integration/papers/knoblock13-sbd.pdf" target="_blank">http://www.isi.edu/integration/papers/knoblock13-sbd.pdf</a> <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li> </ol>