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Scaling Scientometrics: Dimensions on Google BigQuery as an Infrastructure for Large-Scale Analysis

Cloud computing has the capacity to transform many parts of the research ecosystem, from particular research areas to overall strategic decision making and policy. Scientometrics sits at the boundary between research and the decision-making, policy-making, and evaluation processes that underpin rese...

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Detalles Bibliográficos
Autores principales: Hook, Daniel W., Porter, Simon J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080851/
https://www.ncbi.nlm.nih.gov/pubmed/33937619
http://dx.doi.org/10.3389/frma.2021.656233
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author Hook, Daniel W.
Porter, Simon J.
author_facet Hook, Daniel W.
Porter, Simon J.
author_sort Hook, Daniel W.
collection PubMed
description Cloud computing has the capacity to transform many parts of the research ecosystem, from particular research areas to overall strategic decision making and policy. Scientometrics sits at the boundary between research and the decision-making, policy-making, and evaluation processes that underpin research. One of the biggest challenges in research policy and strategy is having access to data in a way that allows for analysis that can respond in an iterative way to inform decisions. Many decisions are based on “global” measures such as benchmark metrics that are hard to source and hence are often nonspecific or outdated. The use of cloud technologies may be promising in addressing this area of providing data for research strategy and policy decisions. A novel visualisation technique is introduced and used as a means to explore the potential for scaling scientometrics by democratising both access to data and compute capacity using the cloud.
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spelling pubmed-80808512021-04-29 Scaling Scientometrics: Dimensions on Google BigQuery as an Infrastructure for Large-Scale Analysis Hook, Daniel W. Porter, Simon J. Front Res Metr Anal Research Metrics and Analytics Cloud computing has the capacity to transform many parts of the research ecosystem, from particular research areas to overall strategic decision making and policy. Scientometrics sits at the boundary between research and the decision-making, policy-making, and evaluation processes that underpin research. One of the biggest challenges in research policy and strategy is having access to data in a way that allows for analysis that can respond in an iterative way to inform decisions. Many decisions are based on “global” measures such as benchmark metrics that are hard to source and hence are often nonspecific or outdated. The use of cloud technologies may be promising in addressing this area of providing data for research strategy and policy decisions. A novel visualisation technique is introduced and used as a means to explore the potential for scaling scientometrics by democratising both access to data and compute capacity using the cloud. Frontiers Media S.A. 2021-04-14 /pmc/articles/PMC8080851/ /pubmed/33937619 http://dx.doi.org/10.3389/frma.2021.656233 Text en Copyright © 2021 Hook and Porter. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Research Metrics and Analytics
Hook, Daniel W.
Porter, Simon J.
Scaling Scientometrics: Dimensions on Google BigQuery as an Infrastructure for Large-Scale Analysis
title Scaling Scientometrics: Dimensions on Google BigQuery as an Infrastructure for Large-Scale Analysis
title_full Scaling Scientometrics: Dimensions on Google BigQuery as an Infrastructure for Large-Scale Analysis
title_fullStr Scaling Scientometrics: Dimensions on Google BigQuery as an Infrastructure for Large-Scale Analysis
title_full_unstemmed Scaling Scientometrics: Dimensions on Google BigQuery as an Infrastructure for Large-Scale Analysis
title_short Scaling Scientometrics: Dimensions on Google BigQuery as an Infrastructure for Large-Scale Analysis
title_sort scaling scientometrics: dimensions on google bigquery as an infrastructure for large-scale analysis
topic Research Metrics and Analytics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080851/
https://www.ncbi.nlm.nih.gov/pubmed/33937619
http://dx.doi.org/10.3389/frma.2021.656233
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