Data Governance Practices Unveiled: Insights from Multiple Data Collection Approaches

ABSTRACT The poster discusses varying data collection approaches in investigation of an organization's data governance practice of a single case study. The aim is to promote transparency in data governance practice on a case‐by‐case basis and to unveil the circumstances of adapting approaches i...

Full description

Saved in:
Bibliographic Details
Published in:Proceedings of the ASIST Annual Meeting 2023-10, Vol.60 (1), p.905-907
Main Authors: Chang, Yun‐Chi, Lin, Fang‐Pang, Jeng, Wei
Format: Article
Language:English
Subjects:
Case study
Data collection
Data collection practice
Data governance
Field observation
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c993-fc39c6ba97722eb42c726965af354056dcdb66a99f23b35517474683bebcb2223
container_end_page 907
container_issue 1
container_start_page 905
container_title Proceedings of the ASIST Annual Meeting
container_volume 60
creator Chang, Yun‐Chi
Lin, Fang‐Pang
Jeng, Wei
description ABSTRACT The poster discusses varying data collection approaches in investigation of an organization's data governance practice of a single case study. The aim is to promote transparency in data governance practice on a case‐by‐case basis and to unveil the circumstances of adapting approaches in data collecting. Four distinct data collecting approaches were utilized in this study, each tailored to diverse needs and scenarios, including group interview, design‐thinking workshop, semi‐structured interview and field study. Clarifying the rationale of taking certain approaches, the research team aims for providing the benchmark for future data governance research.
doi_str_mv 10.1002/pra2.893
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1002_pra2_893</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2879745573</sourcerecordid><originalsourceid>FETCH-LOGICAL-c993-fc39c6ba97722eb42c726965af354056dcdb66a99f23b35517474683bebcb2223</originalsourceid><addsrcrecordid>eNp1kMFOAjEURRujiQRJ_IQmbtwMdtppO3VHUJAEIzGwbtrSkSFlOrYDhr-3iAs3rt5bnPte7gHgNkfDHCH80AaFh6UgF6CHCSeZwCS__LNfg0GMW4RQXjLCBemB1ZPqFJz6gw2NaoyFi6BMVxsb4ao52NrZ9SOcNbH-2HQRVsHv4OvedXXrLPyJjr1zNiV8A0dtG7wyGxtvwFWlXLSD39kHy8nzcvySzd-ms_FonhkhSFYZIgzTSnCOsdUFNhwzwaiqCC0QZWuz1owpISpMNKE05wUvWEm01UZjjEkf3J3Ppr-fexs7ufX71MNFiUsueEEpJ4m6P1Mm-BiDrWQb6p0KR5kjedImT9pk0pbQ7Ix-peLHfzm5eB_hE_8NXAdtaA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2879745573</pqid></control><display><type>article</type><title>Data Governance Practices Unveiled: Insights from Multiple Data Collection Approaches</title><source>Wiley-Blackwell Read &amp; Publish Collection</source><creator>Chang, Yun‐Chi ; Lin, Fang‐Pang ; Jeng, Wei</creator><creatorcontrib>Chang, Yun‐Chi ; Lin, Fang‐Pang ; Jeng, Wei</creatorcontrib><description>ABSTRACT The poster discusses varying data collection approaches in investigation of an organization's data governance practice of a single case study. The aim is to promote transparency in data governance practice on a case‐by‐case basis and to unveil the circumstances of adapting approaches in data collecting. Four distinct data collecting approaches were utilized in this study, each tailored to diverse needs and scenarios, including group interview, design‐thinking workshop, semi‐structured interview and field study. Clarifying the rationale of taking certain approaches, the research team aims for providing the benchmark for future data governance research.</description><identifier>ISSN: 2373-9231</identifier><identifier>EISSN: 2373-9231</identifier><identifier>EISSN: 1550-8390</identifier><identifier>DOI: 10.1002/pra2.893</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley &amp; Sons, Inc</publisher><subject>Case study ; Data collection ; Data collection practice ; Data governance ; Field observation</subject><ispartof>Proceedings of the ASIST Annual Meeting, 2023-10, Vol.60 (1), p.905-907</ispartof><rights>86 Annual Meeting of the Association for Information Science &amp; Technology | Oct. 27 – 31, 2023 | London, United Kingdom. Author(s) retain copyright, but ASIS&amp;T receives an exclusive publication license.</rights><rights>2023 ASIS&amp;T</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c993-fc39c6ba97722eb42c726965af354056dcdb66a99f23b35517474683bebcb2223</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><creatorcontrib>Chang, Yun‐Chi</creatorcontrib><creatorcontrib>Lin, Fang‐Pang</creatorcontrib><creatorcontrib>Jeng, Wei</creatorcontrib><title>Data Governance Practices Unveiled: Insights from Multiple Data Collection Approaches</title><title>Proceedings of the ASIST Annual Meeting</title><description>ABSTRACT The poster discusses varying data collection approaches in investigation of an organization's data governance practice of a single case study. The aim is to promote transparency in data governance practice on a case‐by‐case basis and to unveil the circumstances of adapting approaches in data collecting. Four distinct data collecting approaches were utilized in this study, each tailored to diverse needs and scenarios, including group interview, design‐thinking workshop, semi‐structured interview and field study. Clarifying the rationale of taking certain approaches, the research team aims for providing the benchmark for future data governance research.</description><subject>Case study</subject><subject>Data collection</subject><subject>Data collection practice</subject><subject>Data governance</subject><subject>Field observation</subject><issn>2373-9231</issn><issn>2373-9231</issn><issn>1550-8390</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp1kMFOAjEURRujiQRJ_IQmbtwMdtppO3VHUJAEIzGwbtrSkSFlOrYDhr-3iAs3rt5bnPte7gHgNkfDHCH80AaFh6UgF6CHCSeZwCS__LNfg0GMW4RQXjLCBemB1ZPqFJz6gw2NaoyFi6BMVxsb4ao52NrZ9SOcNbH-2HQRVsHv4OvedXXrLPyJjr1zNiV8A0dtG7wyGxtvwFWlXLSD39kHy8nzcvySzd-ms_FonhkhSFYZIgzTSnCOsdUFNhwzwaiqCC0QZWuz1owpISpMNKE05wUvWEm01UZjjEkf3J3Ppr-fexs7ufX71MNFiUsueEEpJ4m6P1Mm-BiDrWQb6p0KR5kjedImT9pk0pbQ7Ix-peLHfzm5eB_hE_8NXAdtaA</recordid><startdate>202310</startdate><enddate>202310</enddate><creator>Chang, Yun‐Chi</creator><creator>Lin, Fang‐Pang</creator><creator>Jeng, Wei</creator><general>John Wiley &amp; Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>JQ2</scope></search><sort><creationdate>202310</creationdate><title>Data Governance Practices Unveiled: Insights from Multiple Data Collection Approaches</title><author>Chang, Yun‐Chi ; Lin, Fang‐Pang ; Jeng, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c993-fc39c6ba97722eb42c726965af354056dcdb66a99f23b35517474683bebcb2223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Case study</topic><topic>Data collection</topic><topic>Data collection practice</topic><topic>Data governance</topic><topic>Field observation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chang, Yun‐Chi</creatorcontrib><creatorcontrib>Lin, Fang‐Pang</creatorcontrib><creatorcontrib>Jeng, Wei</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><jtitle>Proceedings of the ASIST Annual Meeting</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chang, Yun‐Chi</au><au>Lin, Fang‐Pang</au><au>Jeng, Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Data Governance Practices Unveiled: Insights from Multiple Data Collection Approaches</atitle><jtitle>Proceedings of the ASIST Annual Meeting</jtitle><date>2023-10</date><risdate>2023</risdate><volume>60</volume><issue>1</issue><spage>905</spage><epage>907</epage><pages>905-907</pages><issn>2373-9231</issn><eissn>2373-9231</eissn><eissn>1550-8390</eissn><abstract>ABSTRACT The poster discusses varying data collection approaches in investigation of an organization's data governance practice of a single case study. The aim is to promote transparency in data governance practice on a case‐by‐case basis and to unveil the circumstances of adapting approaches in data collecting. Four distinct data collecting approaches were utilized in this study, each tailored to diverse needs and scenarios, including group interview, design‐thinking workshop, semi‐structured interview and field study. Clarifying the rationale of taking certain approaches, the research team aims for providing the benchmark for future data governance research.</abstract><cop>Hoboken, USA</cop><pub>John Wiley &amp; Sons, Inc</pub><doi>10.1002/pra2.893</doi><tpages>3</tpages></addata></record>
fulltext fulltext
identifier ISSN: 2373-9231
ispartof Proceedings of the ASIST Annual Meeting, 2023-10, Vol.60 (1), p.905-907
issn 2373-9231
2373-9231
1550-8390
language eng
recordid cdi_crossref_primary_10_1002_pra2_893
source Wiley-Blackwell Read & Publish Collection
subjects Case study
Data collection
Data collection practice
Data governance
Field observation
title Data Governance Practices Unveiled: Insights from Multiple Data Collection Approaches
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T07%3A06%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Data%20Governance%20Practices%20Unveiled:%20Insights%20from%20Multiple%20Data%20Collection%20Approaches&rft.jtitle=Proceedings%20of%20the%20ASIST%20Annual%20Meeting&rft.au=Chang,%20Yun%E2%80%90Chi&rft.date=2023-10&rft.volume=60&rft.issue=1&rft.spage=905&rft.epage=907&rft.pages=905-907&rft.issn=2373-9231&rft.eissn=2373-9231&rft_id=info:doi/10.1002/pra2.893&rft_dat=%3Cproquest_cross%3E2879745573%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c993-fc39c6ba97722eb42c726965af354056dcdb66a99f23b35517474683bebcb2223%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2879745573&rft_id=info:pmid/&rfr_iscdi=true