An Integrated Platform for Collaborative Data Analytics
While collaboration among data scientists is a key to organizational productivity, data analysts face significant barriers to achieving this end, including data sharing, accessing and configuring the required computational environment, and a unified method of sharing knowledge. Each of these barrier...
Gespeichert in:
Veröffentlicht in: | arXiv.org 2020-12 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Oesch, Sean Gillen, Rob Karnowski, Tom |
description | While collaboration among data scientists is a key to organizational productivity, data analysts face significant barriers to achieving this end, including data sharing, accessing and configuring the required computational environment, and a unified method of sharing knowledge. Each of these barriers to collaboration is related to the fundamental question of knowledge management "how can organizations use knowledge more effectively?". In this paper, we consider the problem of knowledge management in collaborative data analytics and present ShareAL, an integrated knowledge management platform, as a solution to that problem. The ShareAL platform consists of three core components: a full stack web application, a dashboard for analyzing streaming data and a High Performance Computing (HPC) cluster for performing real time analysis. Prior research has not applied knowledge management to collaborative analytics or developed a platform with the same capabilities as ShareAL. ShareAL overcomes the barriers data scientists face to collaboration by providing intuitive sharing of data and analytics via the web application, a shared computing environment via the HPC cluster and knowledge sharing and collaboration via a real time messaging application. |
format | Article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2471086910</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2471086910</sourcerecordid><originalsourceid>FETCH-proquest_journals_24710869103</originalsourceid><addsrcrecordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mQwd8xT8MwrSU0vSixJTVEIyEksScsvylUAEgrO-Tk5iUn5QJnMslQFl8SSRAXHvMScypLM5GIeBta0xJziVF4ozc2g7OYa4uyhW1CUX1iaWlwSn5VfWgRUXRxvZGJuaGBhZmloYEycKgDmTTVz</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2471086910</pqid></control><display><type>article</type><title>An Integrated Platform for Collaborative Data Analytics</title><source>Free E- Journals</source><creator>Oesch, Sean ; Gillen, Rob ; Karnowski, Tom</creator><creatorcontrib>Oesch, Sean ; Gillen, Rob ; Karnowski, Tom</creatorcontrib><description>While collaboration among data scientists is a key to organizational productivity, data analysts face significant barriers to achieving this end, including data sharing, accessing and configuring the required computational environment, and a unified method of sharing knowledge. Each of these barriers to collaboration is related to the fundamental question of knowledge management "how can organizations use knowledge more effectively?". In this paper, we consider the problem of knowledge management in collaborative data analytics and present ShareAL, an integrated knowledge management platform, as a solution to that problem. The ShareAL platform consists of three core components: a full stack web application, a dashboard for analyzing streaming data and a High Performance Computing (HPC) cluster for performing real time analysis. Prior research has not applied knowledge management to collaborative analytics or developed a platform with the same capabilities as ShareAL. ShareAL overcomes the barriers data scientists face to collaboration by providing intuitive sharing of data and analytics via the web application, a shared computing environment via the HPC cluster and knowledge sharing and collaboration via a real time messaging application.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Applications programs ; Clusters ; Collaboration ; Dashboards ; Data analysis ; Data retrieval ; Knowledge management ; Mathematical analysis ; Real time ; Scientists</subject><ispartof>arXiv.org, 2020-12</ispartof><rights>2020. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,780</link.rule.ids></links><search><creatorcontrib>Oesch, Sean</creatorcontrib><creatorcontrib>Gillen, Rob</creatorcontrib><creatorcontrib>Karnowski, Tom</creatorcontrib><title>An Integrated Platform for Collaborative Data Analytics</title><title>arXiv.org</title><description>While collaboration among data scientists is a key to organizational productivity, data analysts face significant barriers to achieving this end, including data sharing, accessing and configuring the required computational environment, and a unified method of sharing knowledge. Each of these barriers to collaboration is related to the fundamental question of knowledge management "how can organizations use knowledge more effectively?". In this paper, we consider the problem of knowledge management in collaborative data analytics and present ShareAL, an integrated knowledge management platform, as a solution to that problem. The ShareAL platform consists of three core components: a full stack web application, a dashboard for analyzing streaming data and a High Performance Computing (HPC) cluster for performing real time analysis. Prior research has not applied knowledge management to collaborative analytics or developed a platform with the same capabilities as ShareAL. ShareAL overcomes the barriers data scientists face to collaboration by providing intuitive sharing of data and analytics via the web application, a shared computing environment via the HPC cluster and knowledge sharing and collaboration via a real time messaging application.</description><subject>Applications programs</subject><subject>Clusters</subject><subject>Collaboration</subject><subject>Dashboards</subject><subject>Data analysis</subject><subject>Data retrieval</subject><subject>Knowledge management</subject><subject>Mathematical analysis</subject><subject>Real time</subject><subject>Scientists</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mQwd8xT8MwrSU0vSixJTVEIyEksScsvylUAEgrO-Tk5iUn5QJnMslQFl8SSRAXHvMScypLM5GIeBta0xJziVF4ozc2g7OYa4uyhW1CUX1iaWlwSn5VfWgRUXRxvZGJuaGBhZmloYEycKgDmTTVz</recordid><startdate>20201216</startdate><enddate>20201216</enddate><creator>Oesch, Sean</creator><creator>Gillen, Rob</creator><creator>Karnowski, Tom</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20201216</creationdate><title>An Integrated Platform for Collaborative Data Analytics</title><author>Oesch, Sean ; Gillen, Rob ; Karnowski, Tom</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_24710869103</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Applications programs</topic><topic>Clusters</topic><topic>Collaboration</topic><topic>Dashboards</topic><topic>Data analysis</topic><topic>Data retrieval</topic><topic>Knowledge management</topic><topic>Mathematical analysis</topic><topic>Real time</topic><topic>Scientists</topic><toplevel>online_resources</toplevel><creatorcontrib>Oesch, Sean</creatorcontrib><creatorcontrib>Gillen, Rob</creatorcontrib><creatorcontrib>Karnowski, Tom</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Oesch, Sean</au><au>Gillen, Rob</au><au>Karnowski, Tom</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>An Integrated Platform for Collaborative Data Analytics</atitle><jtitle>arXiv.org</jtitle><date>2020-12-16</date><risdate>2020</risdate><eissn>2331-8422</eissn><abstract>While collaboration among data scientists is a key to organizational productivity, data analysts face significant barriers to achieving this end, including data sharing, accessing and configuring the required computational environment, and a unified method of sharing knowledge. Each of these barriers to collaboration is related to the fundamental question of knowledge management "how can organizations use knowledge more effectively?". In this paper, we consider the problem of knowledge management in collaborative data analytics and present ShareAL, an integrated knowledge management platform, as a solution to that problem. The ShareAL platform consists of three core components: a full stack web application, a dashboard for analyzing streaming data and a High Performance Computing (HPC) cluster for performing real time analysis. Prior research has not applied knowledge management to collaborative analytics or developed a platform with the same capabilities as ShareAL. ShareAL overcomes the barriers data scientists face to collaboration by providing intuitive sharing of data and analytics via the web application, a shared computing environment via the HPC cluster and knowledge sharing and collaboration via a real time messaging application.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2020-12 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2471086910 |
source | Free E- Journals |
subjects | Applications programs Clusters Collaboration Dashboards Data analysis Data retrieval Knowledge management Mathematical analysis Real time Scientists |
title | An Integrated Platform for Collaborative Data Analytics |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T13%3A26%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=An%20Integrated%20Platform%20for%20Collaborative%20Data%20Analytics&rft.jtitle=arXiv.org&rft.au=Oesch,%20Sean&rft.date=2020-12-16&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2471086910%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2471086910&rft_id=info:pmid/&rfr_iscdi=true |