東華大學圖書館 |

Data Curation for Qualitative Data Reuse and Big Social Research : = Connecting communities of practice.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data Curation for Qualitative Data Reuse and Big Social Research :/
其他題名:	Connecting communities of practice.
作者:	Mannheimer, Sara.
面頁冊數:	1 online resource (283 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-06, Section: B.
Contained By:	Dissertations Abstracts International84-06B.
標題:	Privacy. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30164118click for full text (PQDT)
ISBN:	9798358406797

Data Curation for Qualitative Data Reuse and Big Social Research : = Connecting communities of practice.
Mannheimer, Sara.

Data Curation for Qualitative Data Reuse and Big Social Research :Connecting communities of practice. - 1 online resource (283 pages)

Source: Dissertations Abstracts International, Volume: 84-06, Section: B.

Thesis (Ph.D.)--Humboldt Universitaet zu Berlin (Germany), 2022.

Includes bibliographical references

Trends toward open science practices, along with advances in technology, have promoted increased data archiving in recent years, thus bringing new attention to the reuse of archived qualitative data. Qualitative data reuse can increase efficiency and reduce the burden on research subjects, since new studies can be conducted without collecting new data. Qualitative data reuse also supports larger-scale, longitudinal research by combining datasets to analyze more participants. At the same time, qualitative research data can increasingly be collected from online sources. Social scientists can access and analyze personal narratives and social interactions through social media such as blogs, vlogs, online forums, and posts and interactions from social networking sites like Facebook and Twitter. These big social data have been celebrated as an unprecedented source of data analytics, able to produce insights about human behavior on a massive scale. This study addresses the following research questions. RQ1: How is big social data curation similar to and different from qualitative data curation? RQ1a: How are epistemological, ethical, and legal issues different or similar for qualitative data reuse and big social research? RQ1b: How can data curation practices such as metadata and archiving support and resolve some of these epistemological and ethical issues? RQ2: What are the implications of these similarities and differences for big social data curation and qualitative data curation, and what can we learn from combining these two conversations? My research employs a social constructivist paradigm and engages with the theories of communities of practice and epistemic cultures. I answered my research questions through an in-depth review of the literature and semi-structured interviews. In the literature review, I identified six key issues in common between qualitative data reuse and big social research. The semi-structured interviews were conducted with three distinct communities of practice: qualitative researchers, big social researchers, and data curators. I used critical incident technique to structure the interview guide and I followed grounded theory methodology for conducting a qualitative content analysis of interview transcripts. This dissertation research produced the following insights. First, this research identified six key issues for qualitative data reuse and big social research: context, data quality and trustworthiness, data comparability, informed consent, privacy and confidentiality, and intellectual property and data ownership. Second, this research showed that each community of practice-qualitative researchers, big social researchers, and data curators-viewed each of the six issues through a different lens, thus prioritizing different dimensions of each issue. This variation in perspective shows that connecting these three communities of practice can support a broader understanding of the key issues, and therefore lead to more epistemologically sound, ethical, and legal research practices. Third, this dissertation finds that data curators are well-positioned to provide guidance for epistemologically sound, ethical, and legal qualitative data reuse and big social data. Curators have the skills and perspectives to translate between communities of practice, and they have the competencies to take care of both types of data.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798358406797Subjects--Topical Terms:

528582
Privacy.
Index Terms--Genre/Form:

542853
Electronic books.

Data Curation for Qualitative Data Reuse and Big Social Research : = Connecting communities of practice.
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500 $a Source: Dissertations Abstracts International, Volume: 84-06, Section: B.
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502 $a Thesis (Ph.D.)--Humboldt Universitaet zu Berlin (Germany), 2022.
504 $a Includes bibliographical references
520 $a Trends toward open science practices, along with advances in technology, have promoted increased data archiving in recent years, thus bringing new attention to the reuse of archived qualitative data. Qualitative data reuse can increase efficiency and reduce the burden on research subjects, since new studies can be conducted without collecting new data. Qualitative data reuse also supports larger-scale, longitudinal research by combining datasets to analyze more participants. At the same time, qualitative research data can increasingly be collected from online sources. Social scientists can access and analyze personal narratives and social interactions through social media such as blogs, vlogs, online forums, and posts and interactions from social networking sites like Facebook and Twitter. These big social data have been celebrated as an unprecedented source of data analytics, able to produce insights about human behavior on a massive scale. This study addresses the following research questions. RQ1: How is big social data curation similar to and different from qualitative data curation? RQ1a: How are epistemological, ethical, and legal issues different or similar for qualitative data reuse and big social research? RQ1b: How can data curation practices such as metadata and archiving support and resolve some of these epistemological and ethical issues? RQ2: What are the implications of these similarities and differences for big social data curation and qualitative data curation, and what can we learn from combining these two conversations? My research employs a social constructivist paradigm and engages with the theories of communities of practice and epistemic cultures. I answered my research questions through an in-depth review of the literature and semi-structured interviews. In the literature review, I identified six key issues in common between qualitative data reuse and big social research. The semi-structured interviews were conducted with three distinct communities of practice: qualitative researchers, big social researchers, and data curators. I used critical incident technique to structure the interview guide and I followed grounded theory methodology for conducting a qualitative content analysis of interview transcripts. This dissertation research produced the following insights. First, this research identified six key issues for qualitative data reuse and big social research: context, data quality and trustworthiness, data comparability, informed consent, privacy and confidentiality, and intellectual property and data ownership. Second, this research showed that each community of practice-qualitative researchers, big social researchers, and data curators-viewed each of the six issues through a different lens, thus prioritizing different dimensions of each issue. This variation in perspective shows that connecting these three communities of practice can support a broader understanding of the key issues, and therefore lead to more epistemologically sound, ethical, and legal research practices. Third, this dissertation finds that data curators are well-positioned to provide guidance for epistemologically sound, ethical, and legal qualitative data reuse and big social data. Curators have the skills and perspectives to translate between communities of practice, and they have the competencies to take care of both types of data.
520 $a Trends in Richtung Open-Science-Praktiken haben zusammen mit technologischen Fortschritten in den letzten Jahren eine verstarkte Datenarchivierung gefordert und damit der Nachnutzung archivierter qualitativer Daten neue Aufmerksamkeit geschenkt. Nachnutzung von qualitativen Daten (qualitative data re-use) kann die Effizienz steigern und die untersuchten Populationen entlasten, da neue Studien durchgefuhrt werden konnen, ohne neue Daten zu erheben. Die Nachnutzung von qualitativen Daten unterstutzt auch grosere Langsschnittforschung, indem Datensatze kombiniert werden, um mehr Teilnehmende zu analysieren. Gleichzeitig konnen qualitative Forschungsdaten zunehmend aus Online-Quellen erhoben werden. Sozialwissenschaftler*innen konnen uber soziale Medien wie Blogs, Vlogs, Online-Foren sowie Beitrage und Interaktionen von Websites sozialer Netzwerke wie Facebook und Twitter auf personliche Erzahlungen und soziale Interaktionen zugreifen und diese analysieren. Diese grosen sozialen Daten (big social data) wurden als beispiellose Quelle fur Datenanalysen zelebriert, die in grosem Umfang Erkenntnisse uber das menschliche Verhalten liefern konnen. Diese Studie befasst sich mit den folgenden Forschungsfragen. RQ1: Wie unterscheidet sich die Kuratierung von Big Social Data von der Kuratierung qualitativer Daten? RQ1a: Wie unterscheiden oder ahneln sich epistemologische, ethische und rechtliche Fragen bei der Nachnutzung qualitativer Daten und bei Big Social Research? RQ1b: Wie konnen Datenkuratierungspraktiken wie Metadaten und Archivierung einige dieser epistemologischen und ethischen Probleme unterstutzen und losen? RQ2: Welche Auswirkungen haben diese Ahnlichkeiten und Unterschiede auf die Kuratierung groser sozialer Daten und die Kuratierung qualitativer Daten, und was konnen wir aus der Kombination dieser beiden Communities lernen? Meine Forschung verwendet ein sozialkonstruktivistisches Paradigma und befasst sich mit den Theorien der Communities of Practice und epistemischen Kulturen. Ich beantwortete meine Forschungsfragen durch eine eingehende Literaturanalyse und semi-strukturierte Interviews. Bei der Literaturanalyse habe ich sechs zentrale Gemeinsamkeiten zwischen der Nachnutzung qualitativer Daten und Big Social Research identifiziert. Die Interviews wurden mit drei unterschiedlichen Communities of Practices durchgefuhrt: qualitativ Forschende, Big Social Data Forschende und Datenkurator*innen. Ich habe die Critical-Incident-Technik verwendet, um den Interviewleitfaden zu strukturieren und die Methodik der Grounded Theory befolgt, um eine qualitative Inhaltsanalyse der Interviewtranskripte durchzufuhren. Diese Dissertation brachte folgende wichtige Erkenntnisse hervor. Erstens identifizierte diese Forschung sechs Schlusselthemen fur die qualitative Datennachnutzung und Big Social Data: Kontext, Datenqualitat und Vertrauenswurdigkeit, Datenvergleichbarkeit, informierte Einwilligung, Datenschutz und Vertraulichkeit sowie geistiges Eigentum und Dateneigentum. Zweitens zeigte diese Forschung, dass jede Praxisgemeinschaft - qualitativ Forschende, Big Social Data Forschende und Datenkurator*innen - jedes der sechs Themen aus einer anderen Perspektive betrachtete und somit unterschiedliche Dimensionen jedes Themas priorisierte. Diese Variation der Perspektiven zeigt, dass die Verbindung dieser drei Praxisgemeinschaften ein breiteres Verstandnis der Schlusselfragen unterstutzen und daher zu epistemologisch fundierteren, ethischeren und rechtlicheren Forschungspraktiken fuhren kann. Drittens stellt diese Dissertation fest, dass Datenkurator*innen gut positioniert sind, um Leitlinien fur eine epistemologisch fundierte, ethische und rechtliche qualitative Datennachnutzung und Big Social Data bereitzustellen. Sie haben die Fahigkeiten und Perspektiven, um zwischen Praxisgemeinschaften zu ubersetzen, und die Kompetenzen, sich um beide Arten von Daten zu kummern.
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