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The Role of Conceptions of Value in ...

Akmon, Dharma R.

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The Role of Conceptions of Value in Data Practices: A Multi-Case Study of Three Small Teams of Ecological Scientists.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The Role of Conceptions of Value in Data Practices: A Multi-Case Study of Three Small Teams of Ecological Scientists./
作者:	Akmon, Dharma R.
面頁冊數:	239 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-08(E), Section: A.
Contained By:	Dissertation Abstracts International75-08A(E).
標題:	Information science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3619609
ISBN:	9781303890109

The Role of Conceptions of Value in Data Practices: A Multi-Case Study of Three Small Teams of Ecological Scientists.
Akmon, Dharma R.

The Role of Conceptions of Value in Data Practices: A Multi-Case Study of Three Small Teams of Ecological Scientists. - 239 p.

Source: Dissertation Abstracts International, Volume: 75-08(E), Section: A.

Thesis (Ph.D.)--University of Michigan, 2014.

This item must not be sold to any third party vendors.

This dissertation examines the role of conceptions of data's value in data practices. Based on a study of three small teams of scientists carrying out ecological research at a biological station, my study addresses the following main question: How do scientists conceive of the value of their data, and how do scientists enact conceptions of value in their data practices? I relied on interviews and participant observations for my study and analyzed my data through the lens of theories of value and meaning. I found that scientists were primarily concerned with data's value for their team's own, relatively narrow uses: addressing a gap in knowledge and producing the outputs that would garner them credit and prestige. When asked about their data's potential value beyond their studies, scientists regularly cited metaanalysis, cross-site comparison, and time-based studies as worthy secondary uses for data and assessed data's value according to how well they thought the data could serve those ends.

ISBN: 9781303890109Subjects--Topical Terms:

554358
Information science.

The Role of Conceptions of Value in Data Practices: A Multi-Case Study of Three Small Teams of Ecological Scientists.
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520 $a This dissertation examines the role of conceptions of data's value in data practices. Based on a study of three small teams of scientists carrying out ecological research at a biological station, my study addresses the following main question: How do scientists conceive of the value of their data, and how do scientists enact conceptions of value in their data practices? I relied on interviews and participant observations for my study and analyzed my data through the lens of theories of value and meaning. I found that scientists were primarily concerned with data's value for their team's own, relatively narrow uses: addressing a gap in knowledge and producing the outputs that would garner them credit and prestige. When asked about their data's potential value beyond their studies, scientists regularly cited metaanalysis, cross-site comparison, and time-based studies as worthy secondary uses for data and assessed data's value according to how well they thought the data could serve those ends.
520 $a As they collected data and conducted their studies, scientists did not think about data's value beyond whether or not they were good as resources for addressing a gap in knowledge. However, when asked to make their data more openly available, researchers indicated that their decision to share was based strongly on data's value for producing publications for the team. Data that teams were still working with and planned to publish were regarded as too valuable to the team to make widely available. Conversely, when scientists thought data's publication value had been fully exploited for the team, they saw little threat in sharing. In addition to publication potential, scientists also suggested that study type influenced their decision to share data and told me that they felt less compelled to share data from controlled studies because they assumed such data had inherently limited value.
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