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<span id="openzim-page-title" class="mw-page-title-main"><span class="mw-page-title-main">Web data integration</span></span>
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<div id="mw-content-text" class="mw-body-content mw-content-ltr" lang="en" dir="ltr"><div class="mw-content-ltr mw-parser-output" lang="en" dir="ltr"><p><b>Web data integration</b> (WDI) is the process of aggregating and managing data from different websites into a single, homogeneous workflow. This process includes data access, transformation, mapping, quality assurance and fusion of data. Data that is sourced and structured from websites is referred to as "web data". WDI is an extension and specialization of <a href="Data_integration" title="Data integration">data integration</a> that views the web as a collection of heterogeneous databases.
</p><p>Data integration techniques in the context of the web, forms the foundation for businesses taking advantage of data available on the ever-increasing number of publicly-accessible websites.<sup id="cite_ref-1" class="reference"><a href="#cite_note-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> Corporate spending on this area amounted to about USD 2.5bn in 2017, and it is expected that by 2020 the market will reach almost USD 7bn.<sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup>
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<div class="mw-heading mw-heading2"><h2 id="Sources">Sources</h2></div>
<p>Web data integration extends and specializes data integration to see the web as a collection of views of databases accessible over the web protocols, including, but not limited to:<sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup>
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<ul><li>Open data catalogs</li>
<li>Government data catalogs</li>
<li>Web applications and sites
<ul><li>UI (<a href="Web_scraping" title="Web scraping">web scraping</a>)</li>
<li>API</li></ul></li>
<li>The semantic web (SPARQL)</li>
<li>HTML embedded structured data</li>
<li>HTML data tables</li>
<li>Spreadsheets</li>
<li>PDFs</li>
<li>Online encyclopedias</li></ul>
<div class="mw-heading mw-heading2"><h2 id="Data_access_and_transformation">Data access and transformation</h2></div>
<p>WDI has technical challenges different from data integration due to the data access and transformation required for the web data sources being often <a href="Unstructured_data" title="Unstructured data">unstructured</a> or <a href="Semi-structured_data" title="Semi-structured data">semi-structured</a> data without a standard query mechanism.
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<div class="mw-heading mw-heading2"><h2 id="Data_quality">Data quality</h2></div>
<p>Understanding the quality and veracity of data is even more important in WDI than in data integration, as the data is generally less implicitly trusted and of lower quality than that which is collected from a trusted source. There are attempts to try to automate a trust rating for web data.<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup>
</p><p>Data quality in data integration can generally happen after data access and transformation, but in WDI quality may need to be monitored as data is collected, due to both the time and the cost of re-collecting the data.<sup id="cite_ref-5" class="reference"><a href="#cite_note-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup>
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<div class="mw-heading mw-heading2"><h2 id="Applications">Applications</h2></div>
<p>WDI has application in many fields, including bioinformatics,<sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup> search engines,<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> price comparison,<sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> and forensic search<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup> data analysis, business intelligence, ecommerce,<sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> healthcare, pharmaceutical<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup> and product development.
</p><p>Most price comparison engines and recommendation systems use user generated data to create recommendations for their users. Similarly, healthcare systems use results of competitions conducted on websites like Kaggle<sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup> to see the accuracy of data and to create user-focused products. In fact, IBM estimates that poor quality WDI is costing companies over $3 trillion<sup id="cite_ref-13" class="reference"><a href="#cite_note-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> in revenue each year.
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<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>
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