Data Management Training/meeting notes 20150320

From Earth Science Information Partners (ESIP)

Data Management training - cross collaboration 20 March 2015

(Link to Notes in Google Document format)


  • Earth Cube funding proposal:
  • Data Management workshop at ESIP Summer meeting.

Attendees: Nancy Hoebelheinrich, Justin Goldstein, Jake Carlson, and Sophie Hou.

Action Items:

  • All: Review the Executive summaries and more specific workshop summaries for those seeming to have the most potential as domains / target audiences for an Earth Cube proposal, especially:
  • Experimental Stratigraphy
  • Critical Zone
  • Modeling
  • Deep Sea Floor
  • Sedimentary Geology
  • Education
  • Sophie & Ruth: Identify datasets that could be used as Use Cases within several disciplines such as Oceanography, Terrestial, Antarctic.
  • Nancy & Sophie: Write an outline / abstract that describes the objectives and outcomes for a proposal for initial vetting by the group & possible inclusion in a workshop / session at ESIP Summer.
  • All: Think about possibilities for a workshop /session proposal for ESIP Summer.
  • All / Erin: Identify possible PIs for an Earth Cube proposal (depending upon subject domains / approach in the proposal); bring Nic Weber into this discussion.


  • We wanted to explore what are the groups in Earth Sciences that we can collaborate with and what are the topics we can propose to continue to the update/improvement of the current modules.
  • The group reviewed the EarthCube End-User Workshops: Executive Summaries:
  • The proposal will be aimed for late summer/early fall; need to determine when the next round will probably happen.
  • Nancy reviewed the Executive Summaries with the focus on “training”.
  • Domain areas that had the most feedback on training requirements are: “Experimental Stratigraphy,” “Critical Zone” (page 33, 36), “Modelling,” “Deep Sea Floor,” “Sedimentary Geology.”
  • “Education” area:
  • Page 50: Data Literacy and “savviness”.
  • Page 52: Learning science research agenda.
  • This could help us identify the focus for the next version of the module updates.
  • “Petrology, Geochemistry & Volcanology”: Page 55.
  • “Sedimentary Geology”: Page 61.
  • “Modeling”: Page 65, 67, and 70.
  • Use modeling examples to demonstrate data management training.
  • “Deep Sea Floor”: Page 81, 83, and 84.
  • Seemed to have the most data management needs.
  • Jake reviewed the Executive Summaries from the LIS professional’s perspective on data management.
  • We could help the scientists/researchers to consider themselves as data producers that will facilitate their data to be better used by the data consumers, which could include the scientists/researchers themselves.
  • Being aware of both the data producer’s and the data consumer’s points of view could help with abridging the knowledge gap. This would in term help allow the data to be more discoverable and usable by all parties.
  • Gaining an understanding of how a research agenda can help people understand the overall purpose of the research, and as a result, identify the areas in which further training on data management would be useful / helpful.
  • One question to consider is could we use existing practices to develop the training about the common or best practices for data management as part of the next stage of training?
  • Another element to consider is how can we bring different groups together to achieve the most collaboration/interoperability for our approach.
  • Is there a model that we could develop to guide the data management collaboration process? → Look up and out to the overall data management ecosystem including data producers, data managers, data users, data management trainers / supporters (such as Research LIS).
  • We could use the May meeting when Kerstin discusses CODPESS to gain a better understanding of how the CODPESS work could relate to our interests / proposal for data management training.
  • Sophie reviewed the Executive Summaries from the scientists’ point of view and to determine what elements could help them meet their needs cross disciplines.
  • Observed at least 8 common areas that were proposed as scientific end-user needs:
  • Multi-disciplinary
  • One-stop access
  • Data collection building
  • Data integration/comparison
  • International collaboration
  • Dark data - especially how to avoid data from becoming dark
  • Share/deposit at repositories
  • Social/Community relationship building
  • All of these needs could be addressed by data management training because the training could help people build a common set of skills and vocabularies to work on these issues together. For example, metadata/file structure/file storage method could all be learned from data management training, and in return, help with ameliorating the issues identified above.
  • Next steps:
  • How do we get further information needed to help us focus a proposal for the next round of call?
  • What is the problem we’re trying to solve and how do we want to solve it?
  • We might want to pick a specific science domain if we would like to make our proposal stronger.
  • How about selection of PI(s)?
  • Preliminary approach:
  • Take case studies from each of the major sciences (antarctic, oceanography, and terrestrial), build on the case that even though each discipline has specific study topics and data needs, similar data management challenges are often faced by all the scientific disciplines. Resolving these through data management training could help greatly in scientific collaboration, and therefore, scientific advancement.
  • Get a better understanding of what the gaps are in the current approaches, training resources and options for data management training in the Earth Sciences.
  • Take a stab at an approach and vet it while also making people aware of ESIP’s Data management modules.
  • Meet again in 3 - 4 weeks to keep up the momentum.
  • Jake will be more free to participate after May 12th.