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Exploring the Long Tail of Astronomy...
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Stahlman, Gretchen R.
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Exploring the Long Tail of Astronomy: A Mixed-Methods Approach to Searching for Dark Data.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Exploring the Long Tail of Astronomy: A Mixed-Methods Approach to Searching for Dark Data./
作者:
Stahlman, Gretchen R.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:
298 p.
附註:
Source: Dissertations Abstracts International, Volume: 82-02, Section: A.
Contained By:
Dissertations Abstracts International82-02A.
標題:
Information science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28027682
ISBN:
9798662486706
Exploring the Long Tail of Astronomy: A Mixed-Methods Approach to Searching for Dark Data.
Stahlman, Gretchen R.
Exploring the Long Tail of Astronomy: A Mixed-Methods Approach to Searching for Dark Data.
- Ann Arbor : ProQuest Dissertations & Theses, 2020 - 298 p.
Source: Dissertations Abstracts International, Volume: 82-02, Section: A.
Thesis (Ph.D.)--The University of Arizona, 2020.
This item must not be sold to any third party vendors.
As research datasets and analyses grow in complexity, data that could be valuable to other researchers and to support the integrity of published work remain uncurated across disciplines. These data are especially concentrated in the "Long Tail" of funded research where curation resources and related expertise are often inaccessible. In the domain of astronomy - which relies heavily on sophisticated instrumentation - it is undisputed that "dark" uncurated data exist, along with data at risk of becoming dark in the future. However, the scope of the problem remains uncertain. The dissertation project described here implements a mixed-methods research approach to characterize the Long Tail in astronomy as well as the properties of uncurated and at-risk astronomical data, and to develop methods for locating potentially-useful data to be targeted for curation through indicators in the scholarly literature. This project aims to enhance our understanding of the nature and prevalence of astronomical dark data and characterize astronomy's Long Tail by: conducting interviews with experts; mapping the decision-making protocols used by astronomers while searching the astronomical literature for references to underlying data; and conducting a survey of authors of journal publications with a questionnaire about the data associated with their papers. The project aims to deepen scholarly insight into domain-specific astronomy data practices, overall addressing epistemological claims that enhanced data access and open science result in scientific knowledge and producing a characterization and theory of the distribution and accessibility of dark and at-risk data in astronomy.
ISBN: 9798662486706Subjects--Topical Terms:
554358
Information science.
Subjects--Index Terms:
Astronomy
Exploring the Long Tail of Astronomy: A Mixed-Methods Approach to Searching for Dark Data.
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As research datasets and analyses grow in complexity, data that could be valuable to other researchers and to support the integrity of published work remain uncurated across disciplines. These data are especially concentrated in the "Long Tail" of funded research where curation resources and related expertise are often inaccessible. In the domain of astronomy - which relies heavily on sophisticated instrumentation - it is undisputed that "dark" uncurated data exist, along with data at risk of becoming dark in the future. However, the scope of the problem remains uncertain. The dissertation project described here implements a mixed-methods research approach to characterize the Long Tail in astronomy as well as the properties of uncurated and at-risk astronomical data, and to develop methods for locating potentially-useful data to be targeted for curation through indicators in the scholarly literature. This project aims to enhance our understanding of the nature and prevalence of astronomical dark data and characterize astronomy's Long Tail by: conducting interviews with experts; mapping the decision-making protocols used by astronomers while searching the astronomical literature for references to underlying data; and conducting a survey of authors of journal publications with a questionnaire about the data associated with their papers. The project aims to deepen scholarly insight into domain-specific astronomy data practices, overall addressing epistemological claims that enhanced data access and open science result in scientific knowledge and producing a characterization and theory of the distribution and accessibility of dark and at-risk data in astronomy.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28027682
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