2015
DOI: 10.1016/j.geomorph.2015.03.039
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Data management, sharing, and reuse in experimental geomorphology: Challenges, strategies, and scientific opportunities

Abstract: The field of experimental geomorphology is in a data-rich era with rapid expansion of high-resolution, digital data sets. Millions of dollars have been invested in building and renovating flume laboratories that run experiments at increasing sophistication, scale, and resolution. However, this overflowing body of laboratory data is not easily analyzed, stored, or accessed. This lack of organization comes at substantial cost to the Earth-surface science community (i.e., geomorphologists, sedimentary geologists,… Show more

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Cited by 30 publications
(32 citation statements)
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References 38 publications
(41 reference statements)
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“…Data sharing and publication are important in ensuring reproducible science (e.g., Costello and Wieczorek, 2014;Hsu et al, 2015). Scientists wish to (or may be required by funding agencies or journals to) publish their data with their results to ensure that others can reproduce their work.…”
Section: Introductionmentioning
confidence: 99%
“…Data sharing and publication are important in ensuring reproducible science (e.g., Costello and Wieczorek, 2014;Hsu et al, 2015). Scientists wish to (or may be required by funding agencies or journals to) publish their data with their results to ensure that others can reproduce their work.…”
Section: Introductionmentioning
confidence: 99%
“…The Data LifeCycle (DLC) models represent one great solution to focus on planning, organization and management of data beyond any specific technology, system and software, from creation to consumption [33][34][35]. Several DLC models generated for specific scenarios (like smart city [10,36]), sciences [34,[37][38][39][40] and environments (like big data [29,32]) have been proposed by many researchers in academia and industries.…”
Section: Fog Layermentioning
confidence: 99%
“…Cragin, Palmer, Carlson, and Witt (2010) studied data sharing in small science and found variety and complexity in how these subdisciplines created, curated, and shared data, often dependent on the practices and resources of the lead PI or small network of collaborators. Schmidt, Gemeinholzer, and Treloar (2016) and Hsu, Martin, McElroy, Litwin-Miller, and Kim (2015) Swan, Gargouri, Hunt, and Harnad (2015) compare deposits in mandated and non-mandated institutional repositories by discipline and show that for Earth Sciences, only about 12% of articles were deposited for mandated institutions and barely 2% for non-mandated institutions.…”
Section: Literature Reviewmentioning
confidence: 99%