Skip to main content

Neuroscience Data in the Cloud Opportunities and Challenges: Proceedings of a Workshop (2020) / Chapter Skim
Currently Skimming:

5 Assigning Credit, Determining Ownership, and Licensing Data in the Cloud
Pages 31-36

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 31...
... . • Allowing researchers to include data citations in their curricu lum vitae could enable them to receive credit for generating data from grant and tenure review committees (Martone)
Read the entire page →
From page 32...
... Researchers might be incentivized to adhere to standards if there was a common incentive structure with reliable metrics that track who contributed to a dataset, what their contributions were, how well the dataset has been maintained, and how influential it has been, because such a structure would make it easier for institutions to effectively account for useful data sharing in their procedures for hiring and promotion, said Cohen. Cohen cited four factors that should be considered in assigning credit: • Type of data, such as demographic, physiological or genetic; • Stakeholders, including participants who provide the data as well as those who collect, process, analyze, curate, and maintain it; • Evaluative factors and metrics that can be used to track quality, value, and other aspects of the data; and • Incentivization of investigators who promote data sharing.
Read the entire page →
From page 33...
... CURRENT PROMISING PRACTICES FOR ASSIGNING CREDIT AND LICENSING DATA Tracking data provenance is essential for assigning credit for sharing different types of data, according to Hill. The World Wide Web Consortium (W3C)
Read the entire page →
From page 34...
... While not requesting authorship, ABIDE collaborators agreed on assigning credit at three levels: on a website for each data collection, in a data descriptor paper that listed all contributors, and in an appendix table for each lab. CREDIT, OWNERSHIP, AND LICENSING ISSUES TO BE RESOLVED Figuring out the best way to assign credit across the continuum of data generation is essential to encourage data sharing across databases, including those in the cloud, according to Cohen, Martone, Jane Roskams, professor of neuroscience at the University of British Columbia, and several others at the workshop.
Read the entire page →
From page 35...
... Hill noted that the neuroscience community is not alone in addressing issues regarding data ownership and access. The World Wide Web has created models for publishing structured data,6 and Google has built indexes of these data,7 he said.
Read the entire page →
From page 36...
... 36 NEUROSCIENCE DATA IN THE CLOUD added that the neuroscience community could follow the same model, but would first have to identify the core incentives for doing so, that is, whether there is value in being able to discover -- and having other people access and use -- an investigator's data and resources.
Read the entire page →

Key Terms

  • data sharing
  • data provenance
  • licensing data
  • data citations
  • protecting data

  • data ownership
  • tracking data
  • encourage data
  • data generation
  • allowing researchers

  • joint declaration
  • collecting metadata
  • promoting interoperability
  • assign credit
  • citizen scientists

  • allows investigators
  • martone noted
  • hill noted
  • unconditional data
  • useful data

  • data commons
  • data quality
  • data versus
  • data citation
  • share data

  • data allows
  • data descriptor
  • include data
  • data alliance
  • produce data


    • This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
    More information on Chapter Skim is available.