Data Management in the Long Tail: Science, Software, and Service

Scientists in all fields face challenges in managing and sustaining access to their research data. The larger and longer term the research project, the more likely that scientists are to have resources and dedicated staff to manage their technology and data, leaving those scientists whose work is ba...

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Main Authors: Christine L. Borgman, Milena S. Golshan, Ashley E. Sands, Jillian C. Wallis, Rebekah L. Cummings, Peter T. Darch, Bernadette M. Randles
Format: Article
Language:English
Published: University of Edinburgh 2016-10-01
Series:International Journal of Digital Curation
Online Access:http://www.ijdc.net/article/view/428
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author Christine L. Borgman
Milena S. Golshan
Ashley E. Sands
Jillian C. Wallis
Rebekah L. Cummings
Peter T. Darch
Bernadette M. Randles
author_facet Christine L. Borgman
Milena S. Golshan
Ashley E. Sands
Jillian C. Wallis
Rebekah L. Cummings
Peter T. Darch
Bernadette M. Randles
author_sort Christine L. Borgman
collection DOAJ
description Scientists in all fields face challenges in managing and sustaining access to their research data. The larger and longer term the research project, the more likely that scientists are to have resources and dedicated staff to manage their technology and data, leaving those scientists whose work is based on smaller and shorter term projects at a disadvantage. The volume and variety of data to be managed varies by many factors, only two of which are the number of collaborators and length of the project. As part of an NSF project to conceptualize the Institute for Empowering Long Tail Research, we explored opportunities offered by Software as a Service (SaaS). These cloud-based services are popular in business because they reduce costs and labor for technology management, and are gaining ground in scientific environments for similar reasons. We studied three settings where scientists conduct research in small and medium-sized laboratories. Two were NSF Science and Technology Centers (CENS and C-DEBI) and the third was a workshop of natural reserve scientists and managers. These laboratories have highly diverse data and practices, make minimal use of standards for data or metadata, and lack resources for data management or sustaining access to their data, despite recognizing the need. We found that SaaS could address technical needs for basic document creation, analysis, and storage, but did not support the diverse and rapidly changing needs for sophisticated domain-specific tools and services. These are much more challenging knowledge infrastructure requirements that require long-term investments by multiple stakeholders.
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spelling doaj.art-f9bfa2f3c8dc4917b4a59567c3ce9f7b2022-12-22T01:28:03ZengUniversity of EdinburghInternational Journal of Digital Curation1746-82562016-10-0111110.2218/ijdc.v11i1.428Data Management in the Long Tail: Science, Software, and ServiceChristine L. Borgman0Milena S. Golshan1Ashley E. Sands2Jillian C. Wallis3Rebekah L. Cummings4Peter T. Darch5Bernadette M. Randles6University of California, Los AngelesUniversity of California, Los AngelesUniversity of California, Los AngelesUniversity of California, Los AngelesUniversity of California, Los AngelesUniversity of California, Los AngelesUniversity of California, Los AngelesScientists in all fields face challenges in managing and sustaining access to their research data. The larger and longer term the research project, the more likely that scientists are to have resources and dedicated staff to manage their technology and data, leaving those scientists whose work is based on smaller and shorter term projects at a disadvantage. The volume and variety of data to be managed varies by many factors, only two of which are the number of collaborators and length of the project. As part of an NSF project to conceptualize the Institute for Empowering Long Tail Research, we explored opportunities offered by Software as a Service (SaaS). These cloud-based services are popular in business because they reduce costs and labor for technology management, and are gaining ground in scientific environments for similar reasons. We studied three settings where scientists conduct research in small and medium-sized laboratories. Two were NSF Science and Technology Centers (CENS and C-DEBI) and the third was a workshop of natural reserve scientists and managers. These laboratories have highly diverse data and practices, make minimal use of standards for data or metadata, and lack resources for data management or sustaining access to their data, despite recognizing the need. We found that SaaS could address technical needs for basic document creation, analysis, and storage, but did not support the diverse and rapidly changing needs for sophisticated domain-specific tools and services. These are much more challenging knowledge infrastructure requirements that require long-term investments by multiple stakeholders.http://www.ijdc.net/article/view/428
spellingShingle Christine L. Borgman
Milena S. Golshan
Ashley E. Sands
Jillian C. Wallis
Rebekah L. Cummings
Peter T. Darch
Bernadette M. Randles
Data Management in the Long Tail: Science, Software, and Service
International Journal of Digital Curation
title Data Management in the Long Tail: Science, Software, and Service
title_full Data Management in the Long Tail: Science, Software, and Service
title_fullStr Data Management in the Long Tail: Science, Software, and Service
title_full_unstemmed Data Management in the Long Tail: Science, Software, and Service
title_short Data Management in the Long Tail: Science, Software, and Service
title_sort data management in the long tail science software and service
url http://www.ijdc.net/article/view/428
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