View source for DMelt:Dev/Usage And Popularity

== Usage and Popularity ==

This section is a working draft for wikipedia.

==Reviews==


DataMelt and its earlier versions, SCaVis (2013-2015) and JHepWork (2005-2013), which are still  available from [http://jwork.org/dmelt/index.php?id=previous DataMelt archive repository] are discussed and compared with similar packages in:
<ref>Comparative Study of Diverse Collection  of Data Mining Tools. By  S. Sarumathi, N. Shanthi, S. Vidhya, M. Sharmila.  International Journal of Computer, Control, Quantum and Information Engineering. 2014; 8(6). 7.
</ref>
<ref>jHepWork – full-featured multiplatform data-analysis framework. [http://blog.dreamcss.com/frameworks/jhepwork-multiplatform-data-analysis-framework/]
</ref>
<ref>Data Analysis and Data Mining Using Java, Jython and jHepWork Blog [https://community.oracle.com/docs/DOC-982931]
</ref>
<ref>Java Applications: Weka, Svnkit, Jhepwork, Fiji, Memoranda, Livegraph, Dirsync Pro, Moneydance, Rachota Timetracker, Data Mapping Engine. de LLC Books (2010) (Redactor) [https://www.amazon.es/Java-Applications-Memoranda-Moneydance-Timetracker/dp/1156999391]
</ref>
<ref>HEP data analysis using jHepWork and Java. Proceedings of the HERA-LHC workshops (2007-2008), DESY-CERN [https://arxiv.org/abs/0809.0840]
</ref>
<ref>A Study of Tools, Techniques, and Trends for Big Data Analytics. By R.Shireesha et al.  (2016) International Journal of Advance Computing Technique and Applications (IJACTA), ISSN : 2321-4546, Vol 4, Issue 1 [http://www.ijacta.com/index.php/ojs/article/download/41/33]
</ref>
<ref>Comparison of Various Tools for Data Mining. By P.Kaur etc. IJERT ISSN: 2278-0181 Vol. 3 Issue 10 (2010) [[https://www.ijert.org/download/11405/comparison-of-various-tools-for-data-mining]]
</ref>
<ref>Advanced Web and Network Technologies, and Applications. By Heng Tao Shen et al. Springer Science & Business Media - 2006-01-09
</ref>
<ref>SCaVis 2.1. Review by Pete Daniel  (2014) [https://www.download3k.com/Home-Education/Science/Download-SCaVis.html]
</ref>
<ref>DataMelt – Werkbank für technisch-wissenschaftliche Berechnungen und Visualisierungen mit Java und Jython, Java SPEKTRUM (German) 5/2013, 26-28, [https://www.sigs-datacom.de/fachzeitschriften/javaspektrum/archiv/artikelansicht/artikel-titel/integrationsspektrum-scavis-werkbank-fuer-technisch-wissenschaftliche-berechnungen-und-visualis.html]
</ref>
<ref>Suitability analysis of data mining tools and methods. [https://is.muni.cz/th/255695/fi_b/]. S.Kovac, Bachelor's thesis (in English), jHepWork is reviewed on page 39-42, Masaryk University.
</ref>
<ref>
Gestion del Conocimiento (in Spanish), Universidad del Magdalena, A.E.Gonzalez, A.M.Pertuz, S.Pimienta, A,Cana, A.Quiceno,
[https://es.slideshare.net/andresedogonzalez/gestion-del-conocimiento-41769491] (p 20-25).
</ref>
<ref>
VeryCD. [http://www.verycd.com/topics/2817300/ JHepWork tutorial]  
</ref>
<ref>
5 of the Best Free and Open Source Data Mining Software.  by Jun Auza (2010). TechSource  [http://www.junauza.com/2010/11/free-data-mining-software.html]
</ref>
.

The DataMelt (2015-), a new development of the JHepWork and  SCaVis programs.
Comparisons of DataMelt with other popular packages for statistical and numeric analysis are given in these reviews
<ref>Comparative Analysis of Information Extraction Techniques for Data Mining, by Amit Verma et al. Indian Journal of Science and Technology, Vol 9, March 2016 [http://www.indjst.org/index.php/indjst/article/download/80464/67992]
</ref>
<ref>Evaluation and comparison of open source software suites for data mining and knowledge discovery. A.H. Altalhi et al.  Wiley Online Library (2017) [https://onlinelibrary.wiley.com/doi/full/10.1002/widm.1204]
</ref>
<ref>Brief Review of Educational Applications Using Data Mining  and Machine Learning, [https://redie.uabc.mx/redie/article/viewFile/1305/1586], by A. Berenice Urbina Nájera, Jorgede la Calleja Mora, Redie ISSN 1607-4041. Revista Electrónica de Investigación Educativa, 19(4), 84-96
</ref>
<ref>Analysis of Data Using Data Mining tool Orange. Maqsud S.Kukasvadiya et. al. [https://www.ijedr.org/papers/IJEDR1702288.pdf] (2017) IJEDR,  Volume 5, Issue 2, ISSN: 2321-9939
</ref>
<ref>Big Data - A Survey of Big Data Technologies. By P.Dhavalchandra, M.Jignasu, R.Amit. International Journal of Science and Technology. Volume 2, p45-50 (2016) [http://www.ijsrt.us/vol2issue1/pdf%209.pdf]
</ref>
.

DataMelt is often discussed in various lists with similar software
<ref>
Best free data analytics tools, 2018.  CIO. Aticle. By Matt Kapko. [https://www.cio.com/article/3269456/analytics/best-free-data-analytics-tools-2018.html]
</ref>
<ref>
Top 15 Best Free Data Mining Tools. Software Testing Help [https://www.softwaretestinghelp.com/data-mining-tools/]
</ref>
<ref>DataMelt. Predictive analytic review. [https://www.predictiveanalyticstoday.com/datamelt/]
</ref> 
<ref>Free statistical software. Article published from the Citizendium [http://en.citizendium.org/wiki/Free%20statistical%20software]
</ref> 
<ref>19 Best Data Mining Tools. Data Mining Tutorials by Data Flair [https://data-flair.training/blogs/data-mining-tools-techniques/]
</ref> 
<ref>Other data analysis frameworks. [http://www.inr.ru/~nozik/dataforge/misc.html]. Review by DataForge. Institute for Nuclear Research of Russian academy of Sciences
</ref> 
<ref>DataMaition. Hadoop and Big Data: 60 Top Open Source Tools [https://www.datamation.com/applications/hadoop-and-big-data-60-top-open-source-tools-3.html]
</ref> 
<ref>The Data Science Toolkit: 24 free data science tools by Naina Sethi. [https://www.springboard.com/blog/data-science-toolkit/]
</ref>
<ref>Top 7 Data Mining Tools. [http://www.techyv.com/article/top-7-data-mining-tools/] By Snyder Libbys (2018)
</ref>
<ref>The Most Popular Python Scientific Libraries. Apr 2017. [https://stxnext.com/blog/2017/04/12/most-popular-python-scientific-libraries/]
</ref>
<ref>5 Most Commonly Used Open Source Data Mining Tools. CodeCondo blog by Sabeer Shaikh [https://codecondo.com/author/ntq9vrkcj/]
</ref>
<ref>25 amazing Java desktop applications by  M. Schulenburg. [http://www.blueseal.eu/it/25-java-applications/]
</ref>
<ref>
Big Data Mining. 2017 Open Source Big Data Mining Tools. Intelegency.ORG (2017) [http://www.intelligency.org/big_data_mining.php]
</ref> 
<ref>
5 of the Best Free and Open Source Data Mining Software. Blog (2010) J. Auza. TechSource. News. Reviews. [http://www.junauza.com/2010/11/free-data-mining-software.html]
</ref> 
<ref>PC Quest review. 8 Enterprise Class Open Source Tools for Data and Text Mining by by Raj Kumar Maurya. Oct 2015 [http://www.pcquest.com/8-enterprise-class-open-source-tools-for-data-and-text-mining/]
</ref>
<ref>
25+ Free Data Mining Tools for Better Analysis. RankRED. By Varun Kumar. (2015)  Internet Technology Knowledge. [https://www.rankred.com/free-data-mining-tools/]
</ref> 
<ref>8 Best Open Source Data Mining Tools [https://securityonline.info/8-best-open-source-data-mining-tools-weka-rapid-miner-orange-knime-jhepwork-apache-mahout-elki-rattl]e/]
</ref>
<ref>Top application for scientific computation, data analysis and data visualization that features IDE, Jython shell and BeanShell consoles, various programming languages, and LaTeX editing capabilities [http://www.softpedia.com/get/Science-CAD/jHepWork.shtml]
</ref>
<ref>
Top 10 open source data mining tools. By I.V.Shravan, Open Source Portal. 2017, [https://opensourceforu.com/2017/03/top-10-open-source-data-mining-tools/]
</ref> 
<ref>
7 ferramentas gratuitas e eficazes para análise de dados, by Matt Kapko (2018). ComputerWord [http://computerworld.com.br/7-ferramentas-gratuitas-e-eficazes-para-analise-de-dados]
</ref>
<ref>
2018年7款最佳免费数据分析工具 (2018) [http://bigdata.51cto.com/art/201805/573023.htm]
</ref>
.

==Popularity==

jHepWork, SCaVis/DatMelt are part of the software library of National Institutes of Health Library
<ref>Data Sciences Workstation: SCaVis. By Lisa Federer. National Institutes of Health Library [http://nihlibrary.campusguides.com/c.php?g=102650&p=672758]</ref>,
Mathematical support of Institute for Nuclear Research of Russian academy of Sciences<ref>The DataForge, Sector for Mathematical Support of Institute for Nuclear Research of Russian academy of Sciences [http://www.inr.ru/~nozik/dataforge/misc.html]</ref> and others.
On a commercial site, DataMelt is provided as a service on Amazon EC2 clouds by the Miri Infotech IT Solution Provider company
<ref>Miri Infotech. A Complete IT Solution Provider. [http://www.miritech.com/products/aws/datamelt.aspx  DataMelt deployment]</ref>.

It is difficult to judge how many users use DataMelt since download information from the main resource [http://jwork.org/dmelt] is not available.
[[Sourceforge|Sourceforge]], which provides an alternative download option, quotes 300 monthly downloads [https://sourceforge.net/projects/dmelt/] (May 2018).

One estimate can be done by looking at the popularity of the book<ref>Numeric Computation and Statistical Data Analysis on the Java Platform, S.Chekanov, Springer, 2016</ref>
which,  de facto,  is a description of the DataMelt program. According to the
Springer International, this book is top 25% most downloadable books in 2016 and 2017 in the category "Advanced Information and Knowledge Processing"
<ref>Springer Book Performance Report [http://jwork.org/dmelt/data_dm/reports/BookPerformanceReport2017.pdf]</ref>.
Since the publication of the book, Springer detects 26k chapter downloads until May 2018<ref>Springer download Statistics of the book "Numeric Computation and Statistical Data Analysis on the Java Platform" 2016 [http://www.bookmetrix.com/detail/book/1b56c407-cc52-49ee-9547-5ec300e18498#downloads]</ref>, about 1500 per chapter.
The previous book describing jHepWork had a similar popularity <ref>Springer download Statistics of the book "Scientific Data Analysis using Jython Scripting and Java" [http://www.bookmetrix.com/detail/book/0d0c46b5-edee-4145-b112-4167b6739c11#downloads]</ref>.
Bookmetrix estimates 140 readers of the DataMelt book.

==References==