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A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository

Social scientists are producing an ever-expanding volume of data, leading to questions about appraisal and selection of content given finite resources to process data for reuse. We analyze users’ search activity in an established social science data repository to better understand demand for data an...

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Detalles Bibliográficos
Autores principales: Pienta, Amy, Akmon, Dharma, Noble, Justin, Hoelter, Lynette, Jekielek, Susan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6128405/
https://www.ncbi.nlm.nih.gov/pubmed/30197664
http://dx.doi.org/10.2218/ijdc.v12i2.500
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author Pienta, Amy
Akmon, Dharma
Noble, Justin
Hoelter, Lynette
Jekielek, Susan
author_facet Pienta, Amy
Akmon, Dharma
Noble, Justin
Hoelter, Lynette
Jekielek, Susan
author_sort Pienta, Amy
collection PubMed
description Social scientists are producing an ever-expanding volume of data, leading to questions about appraisal and selection of content given finite resources to process data for reuse. We analyze users’ search activity in an established social science data repository to better understand demand for data and more effectively guide collection development. By applying a data-driven approach, we aim to ensure curation resources are applied to make the most valuable data findable, understandable, accessible, and usable. We analyze data from a domain repository for the social sciences that includes over 500,000 annual searches in 2014 and 2015 to better understand trends in user search behavior. Using a newly created search-to-study ratio technique, we identified gaps in the domain data repository’s holdings and leveraged this analysis to inform our collection and curation practices and policies. The evaluative technique we propose in this paper will serve as a baseline for future studies looking at trends in user demand over time at the domain data repository being studied with broader implications for other data repositories.
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spelling pubmed-61284052018-09-07 A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository Pienta, Amy Akmon, Dharma Noble, Justin Hoelter, Lynette Jekielek, Susan Int J Digit Curation Article Social scientists are producing an ever-expanding volume of data, leading to questions about appraisal and selection of content given finite resources to process data for reuse. We analyze users’ search activity in an established social science data repository to better understand demand for data and more effectively guide collection development. By applying a data-driven approach, we aim to ensure curation resources are applied to make the most valuable data findable, understandable, accessible, and usable. We analyze data from a domain repository for the social sciences that includes over 500,000 annual searches in 2014 and 2015 to better understand trends in user search behavior. Using a newly created search-to-study ratio technique, we identified gaps in the domain data repository’s holdings and leveraged this analysis to inform our collection and curation practices and policies. The evaluative technique we propose in this paper will serve as a baseline for future studies looking at trends in user demand over time at the domain data repository being studied with broader implications for other data repositories. 2017-12-31 2017 /pmc/articles/PMC6128405/ /pubmed/30197664 http://dx.doi.org/10.2218/ijdc.v12i2.500 Text en This work is released under a Creative Commons Attribution Licence, version 4.0.For details please see https://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Pienta, Amy
Akmon, Dharma
Noble, Justin
Hoelter, Lynette
Jekielek, Susan
A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository
title A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository
title_full A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository
title_fullStr A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository
title_full_unstemmed A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository
title_short A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository
title_sort data-driven approach to appraisal and selection at a domain data repository
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6128405/
https://www.ncbi.nlm.nih.gov/pubmed/30197664
http://dx.doi.org/10.2218/ijdc.v12i2.500
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