Earth Science Collaboratory User Model

From Earth Science Information Partners (ESIP)
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.

Research Users

  • Research Scientists (Intradisciplinary)
    • Salient Characteristics: Well-versed in their own field and the available tools
    • Key Needs: share analysis results within projects
  • Research Scientists (Interdisciplinary/Cross-disciplinary)
    • Salient Characteristics: Well-versed in their own field but not necessarily in the Earth science discipline the data are from. May or may not have the time to learn it.
    • Key Needs: access to experts and/or expertise in the other discipline. Access to data quality info in an accessible form.
  • Graduate Student Researchers
    • Salient Characteristics: May not be well versed in the field yet, but have the motivation, time and necessity to learn it eventually.
    • Key Needs: learn analysis techniques from more experienced users in the field. See what developments are going on in the field as a whole.
  • Citizen Scientists
    • Salient Characteristics: May be lacking in background science knowledge regarding data, but interested in learning about it if the process can be gradual.
    • Key Needs: Science "stories" about interesting phenomena that progress logically from data to final result.
  • Peer Reviewers
    • Salient Characteristics: Checking on results from submitted paper, possibly re-running analysis
    • Key Needs: Examine workflows, results; rerun analysis

Applications Users

  • Applications Researchers
    • Salient Characteristics: similar to Intra-disciplinary and Inter-disciplinary science researchers, but more probably the latter.
    • Key Needs: connections to both Applications analysts and Science Researchers
  • Applications Analysts
    • Salient Characteristics: usually holders of Bachelor's or Master's degrees in related field, but with long years of practical experience. Therefore may have valuable on-the-ground knowledge of potential use to applications researchers.
    • Key Needs: access knowledge of Applications researchers AND other applications analysts
  • Decision Support Systems
    • Salient Characteristics: non-human, i.e., computer systems.
    • Key Needs: ability to access data, tools, knowledge potentially without a human in the loop.
  • Applications Decision-makers
    • Salient Characteristics: may be non-scientific, or from a very different field than the discipline from which the information comes.
    • Key Needs: (TBD - need to interview an exemplar?)

Educational Users

  • College educators
  • K-12 educators
  • Museums

Other Users

  • Program Managers / Executives
    • Salient Characteristics: main job is maximizing science return of program investments
    • Key Needs: Determine the science return of tools and data