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		<id>http://www.colloquiam.com/wd/index.php?action=history&amp;feed=atom&amp;title=Truong_et_al_2019a</id>
		<title>Truong et al 2019a - Revision history</title>
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		<updated>2026-05-17T06:49:16Z</updated>
		<subtitle>Revision history for this page on the wiki</subtitle>
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	<entry>
		<id>http://www.colloquiam.com/wd/index.php?title=Truong_et_al_2019a&amp;diff=204448&amp;oldid=prev</id>
		<title>Scipediacontent: Scipediacontent moved page Draft Content 231612407 to Truong et al 2019a</title>
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				<updated>2021-02-03T15:10:56Z</updated>
		
		<summary type="html">&lt;p&gt;Scipediacontent moved page &lt;a href=&quot;/public/Draft_Content_231612407&quot; class=&quot;mw-redirect&quot; title=&quot;Draft Content 231612407&quot;&gt;Draft Content 231612407&lt;/a&gt; to &lt;a href=&quot;/public/Truong_et_al_2019a&quot; title=&quot;Truong et al 2019a&quot;&gt;Truong et al 2019a&lt;/a&gt;&lt;/p&gt;
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				&lt;tr style='vertical-align: top;' lang='en'&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan='1' style=&quot;background-color: white; color:black; text-align: center;&quot;&gt;Revision as of 15:10, 3 February 2021&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan='2' style='text-align: center;' lang='en'&gt;&lt;div class=&quot;mw-diff-empty&quot;&gt;(No difference)&lt;/div&gt;
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		<author><name>Scipediacontent</name></author>	</entry>

	<entry>
		<id>http://www.colloquiam.com/wd/index.php?title=Truong_et_al_2019a&amp;diff=204447&amp;oldid=prev</id>
		<title>Scipediacontent: Created page with &quot; == Abstract ==   Smart manufacturing is strongly correlated with the digitization of all manufacturing activities. This increases the amount of data available to drive produc...&quot;</title>
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				<updated>2021-02-03T15:10:53Z</updated>
		
		<summary type="html">&lt;p&gt;Created page with &amp;quot; == Abstract ==   Smart manufacturing is strongly correlated with the digitization of all manufacturing activities. This increases the amount of data available to drive produc...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
== Abstract ==&lt;br /&gt;
&lt;br /&gt;
 Smart manufacturing is strongly correlated with the digitization of all manufacturing activities. This increases the amount of data available to drive productivity and profit through data-driven decision making programs. The goal of this article is to assist data engineers in designing big data analysis pipelines for manufacturing process data. Thus, this paper characterizes the requirements for process data analysis pipelines and surveys existing platforms from academic literature. The results demonstrate a stronger focus on the storage and analysis phases of pipelines than on the ingestion, communication, and visualization stages. Results also show a tendency towards custom tools for ingestion and visualization, and relational data tools for storage and analysis. Tools for handling heterogeneous data are generally well-represented throughout the pipeline. Finally, batch processing tools are more widely adopted than real-time stream processing frameworks, and most pipelines opt for a common script-based data processing approach. Based on these results, recommendations are offered for each phase of the pipeline.&lt;br /&gt;
&lt;br /&gt;
Document type: Article&lt;br /&gt;
&lt;br /&gt;
== Full document ==&lt;br /&gt;
&amp;lt;pdf&amp;gt;Media:Draft_Content_231612407-beopen5168-7087-document.pdf&amp;lt;/pdf&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Original document ==&lt;br /&gt;
&lt;br /&gt;
The different versions of the original document can be found in:&lt;br /&gt;
&lt;br /&gt;
* [http://dx.doi.org/10.1186/s40537-018-0162-3 http://dx.doi.org/10.1186/s40537-018-0162-3] under the license https://creativecommons.org/licenses/by/4.0&lt;br /&gt;
&lt;br /&gt;
* [https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-018-0162-3 https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-018-0162-3] under the license https://creativecommons.org/licenses/by/4.0&lt;br /&gt;
&lt;br /&gt;
* [http://link.springer.com/article/10.1186/s40537-018-0162-3 http://link.springer.com/article/10.1186/s40537-018-0162-3],&lt;br /&gt;
: [https://doaj.org/toc/2196-1115 https://doaj.org/toc/2196-1115] under the license cc-by&lt;br /&gt;
&lt;br /&gt;
* [http://link.springer.com/content/pdf/10.1186/s40537-018-0162-3.pdf http://link.springer.com/content/pdf/10.1186/s40537-018-0162-3.pdf],&lt;br /&gt;
: [http://link.springer.com/article/10.1186/s40537-018-0162-3/fulltext.html http://link.springer.com/article/10.1186/s40537-018-0162-3/fulltext.html],&lt;br /&gt;
: [http://dx.doi.org/10.1186/s40537-018-0162-3 http://dx.doi.org/10.1186/s40537-018-0162-3]&lt;br /&gt;
&lt;br /&gt;
* [https://link.springer.com/article/10.1186/s40537-018-0162-3 https://link.springer.com/article/10.1186/s40537-018-0162-3],&lt;br /&gt;
: [https://journalofbigdata.springeropen.com/articles/10.1186/s40537-018-0162-3 https://journalofbigdata.springeropen.com/articles/10.1186/s40537-018-0162-3],&lt;br /&gt;
: [https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-018-0162-3 https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-018-0162-3],&lt;br /&gt;
: [https://link.springer.com/content/pdf/10.1186%2Fs40537-018-0162-3.pdf https://link.springer.com/content/pdf/10.1186%2Fs40537-018-0162-3.pdf],&lt;br /&gt;
: [https://dblp.uni-trier.de/db/journals/jbd/jbd6.html#IsmailTK19 https://dblp.uni-trier.de/db/journals/jbd/jbd6.html#IsmailTK19],&lt;br /&gt;
: [https://paperity.org/p/185384357/manufacturing-process-data-analysis-pipelines-a-requirements-analysis-and-survey https://paperity.org/p/185384357/manufacturing-process-data-analysis-pipelines-a-requirements-analysis-and-survey],&lt;br /&gt;
: [https://academic.microsoft.com/#/detail/2909445826 https://academic.microsoft.com/#/detail/2909445826] under the license https://creativecommons.org/licenses/by/4.0&lt;br /&gt;
&lt;br /&gt;
* [ ]&lt;/div&gt;</summary>
		<author><name>Scipediacontent</name></author>	</entry>

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