Moving Forward on the Earth Science Collaboratory

Moving forward on the Earth Science Collaboratory:

ESC tracks

• Technical Track
• Program
• User stories
• Human Factors

Technical Track:

ESIP and EarthCube similarities

• EC focuses on end-user community and long tail science
  • Not much perspective on Earth Science Data Centers
  • Long-term road map
  • Big language barrier
    • CS versus geosciences

Comment: Trust barrier from Human Factors

• between CS and Geosciences

EarthCube Frequently Discussed Challenges:

• community engagement, governance, integration and coordination, motivation, semantics, access and discovery, tools, dark data

Fundamental Differences:

EC

Structure:

• community groups & concept wards (implies funding)
• governance of a community group
• active for 1-2 years
• focus on long-talk of science
• some direct funding activities

ESIP

Structure:

Cluster and committee

Comments:

1. Would be more analogous if he had a cluster working on governance
   1. Not all done on a volunteer basis
   2. more on a continuum, we do more of this and we do less of this
2. We should keep an eye on EarthCube program for ideas (example, something like the concept award)
3. What should be the roles of ESC, EC, and other cluster

Trying to see what the gaps are:

Workflow (ESIP)

Preservation and Stewardship (EC)

Metadata (EC)

Visualization (EC)

Human Factor – subgroup, you don’t see it in EarthCube also

Interoperability Community: in EarthCube: focused on data & models

Brokering:

What should be the role of brokering within an Earth Science Collaboratory?

Questions/Comments:

1. Comparison, talking about ESIP as it is now (very mature) compared to EC(baby)
   1. what comparison would you make between EC now and ESIP at 1 ½ years old
   2. EC focused on fundamental research
   3. ESIP much more agile
2. Definition of long-tail science: front tail science (heavily funded), smaller projects (are the long-tail), collectively they make up the bulk of the community
   1. there weren’t enough of the long-tail scientists at the Charrette
3. Community groups talked about subgroups for community engagement & use cases
4. Needs to be clear benefits to long tail scientist (EC)
   1.  We need to ask that to ourselves (ESIP)
      1. part of success of ESIP has been the larger groups and smaller involved
      2. ESIPs description says we’re a group of practitioners
5. Thinks the intention of EC to focus on spectrum
6. DataONE is a similar organization to think about
   1. There are five DataNet awards
   2. They are not an archive, they connect the archive (they are the glue) DataONE
7. NSF has different focus than NASA, NOAA, USGS
8. What is NSF trying to solve by EC?
   1. We don’t know where all the data is, interoperable, etc…
   2. Finding, understanding, using, accessing data
   3. NSF more focused on fundamental research
9. EC could be a more conceptual/intellectual level and ESC more implementation layer
10. DataONE satisfies certain components of EC
    1. Need to think about how DataONE satisfies some of the EC capabilities
    2. Increasing recognition in that contributes to data interoperability
    3. Either you’re a node or not a node, we’re taking certain implementation choices right now
    4. Working towards groups that will be members tomorrow
    5. ESIP is much more of a grassroot came without funding, ESIP ESC is broader in concept than DataONE
    6. DataONE is OCI
11. ESC more of a collaboratory as tools/toolkits
12. Maybe we should infuse some of the existing work
13. Parallel activities, if there are enough people in same room then more chance of getting things done
    1. Many of us wearing both hats
    2. Do we want to thing anything outside of current status quo?
    3. There are a lot of other hats
14. EC seems to be more of a discussion than a program
15. We want to address, what we want to do moving forward, do we want to join EC or not?