Earth Science Collaboratory User Model

From Federation of Earth Science Information Partners

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