The ethos and pragmatics of data sharing

Ingrid Erickson, Kristin Eschenfelder, Sean Goggins, Libby Hemphill, Steve Sawyer, Kalpana Shankar, Katie Shilton

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The focus of this panel is the pragmatics of data sharing as framed by the needs and pressures of scholarly work. Panelists represent a lively blend of quantitative, qualitative and mixed methods researchers with recent experiences in developing and sharing data. Panelists will present research and address questions related to data collection and management, human subjects protocols, data archival and data repositories and other emergent issues.

Original languageEnglish (US)
Title of host publicationCSCW 2014 - Companion Publication of the 17th ACM Conference on Computer Supported Cooperative Work and Social Computing
PublisherAssociation for Computing Machinery
Pages109-112
Number of pages4
ISBN (Print)9781450325417
DOIs
StatePublished - Jan 1 2014
Event17th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2014 - Baltimore, MD, United States
Duration: Feb 15 2014Feb 19 2014

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW

Other

Other17th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2014
CountryUnited States
CityBaltimore, MD
Period2/15/142/19/14

Keywords

  • Archive
  • Collaboration
  • Data management
  • Data set
  • Data sharing
  • Infrastructure

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Networks and Communications

Cite this

Erickson, I., Eschenfelder, K., Goggins, S., Hemphill, L., Sawyer, S., Shankar, K., & Shilton, K. (2014). The ethos and pragmatics of data sharing. In CSCW 2014 - Companion Publication of the 17th ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 109-112). (Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW). Association for Computing Machinery. https://doi.org/10.1145/2556420.2556852