Difference between revisions of "Template:Article of the week"
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:List1 Stocker DataSciJourn 19-1.png|240px]]</div> | <!--<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:List1 Stocker DataSciJourn 19-1.png|240px]]</div> //--> | ||
'''"[[Journal: | '''"[[Journal:Data without software are just numbers|Data without software are just numbers]]"''' | ||
Great strides have been made to encourage researchers to [[Archival informatics|archive]] data created by research and provide the necessary systems to support their storage. Additionally, it is recognized that data are meaningless unless their provenance is preserved, through appropriate [[metadata]]. Alongside this is a pressing need to ensure the [[Software quality|quality]] and archiving of the software that generates data, through simulation and control of experiment or data collection, and that which [[Data analysis|analyzes]], modifies, and draws value from raw data. In order to meet the aims of reproducibility, we argue that [[Information management|data management]] alone is insufficient: it must be accompanied by [[Systems development life cycle|good software practices]], the training to facilitate it, and the support of stakeholders, including appropriate recognition for software as a research output. ('''[[Journal:Data without software are just numbers|Full article...]]''')<br /> | |||
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Revision as of 15:44, 4 October 2021
"Data without software are just numbers"
Great strides have been made to encourage researchers to archive data created by research and provide the necessary systems to support their storage. Additionally, it is recognized that data are meaningless unless their provenance is preserved, through appropriate metadata. Alongside this is a pressing need to ensure the quality and archiving of the software that generates data, through simulation and control of experiment or data collection, and that which analyzes, modifies, and draws value from raw data. In order to meet the aims of reproducibility, we argue that data management alone is insufficient: it must be accompanied by good software practices, the training to facilitate it, and the support of stakeholders, including appropriate recognition for software as a research output. (Full article...)
Recently featured:
