Group #1 (Data) Session #B Data: Collecting, Accessing, Using

1. Group #1 (Data)Session #BData: Collecting, Accessing, Using Discussion lead by Cherri Pancake Reported on by Yigal Arens

2. CI 20 years from now • No single control • Elements exist in symbiosis, together • Complex, like a human body • Can self-repair, self-heal and self-improve

3. The Challenge • How we move from domain specific to general • How we bring everything together • Or at least have everything inter-operate

4. Investment needs • Testbeds • Domain-specific, e.g., NEES and CLEANER • Pilot studies • Community integration tools • Social: Community building, collaboration and cooperation among members • Consortium development should be first • Not immediate infrastructure development • This is a major effort that is not typically recognized, let along budgeted for • E. g., in case of NEES

5. Investment needs: The NSF role • Take a systems view and consider explicitly the order in which community components should be funded • Consider also the possibility of components being shared between research communities

6. CI building schedule • Consider schedule explicitly: Development, research, etc. • Build incrementally • “Funnel model”: start with a larger collection and narrow down over time • Need to be concerned with standards • The best will succeed and those who depend on the others will accommodate, like in industry • Perhaps include tech transfer in proposals and evaluations

7. Don’t forget • Coordination and infrastructure work shouldn’t overwhelm researchers • Time should be left to researchers to engage in their own creative work • Some of the infrastructure work is for professionals in those areas • Of course, in partnership with researchers in the various fields • The economic and management issues need to be considered • Industry must be involved

8. Build out • Discover understandings, phenomena, dynamics that may be invariant and apply to diverse situations • We have models that are derived from non-universal data sets • We have rules of thumb • We now have an opportunity to reexamine these and discover more, discover principles, apply them elsewhere • Re-use data in areas for which it may not have been intended to be used

9. What about standardization? • A strategy in this area is important, since it is very difficult to redo • Industry is often very proprietary about what it develops • NSF can sponsor standardization efforts in science and engineering, and industry will participate (since the efforts are often based on their experience)

10. Other comments • Risk management in CI? • This is not a strength in CS, yet it’s required • An engineer would not have launched the Hubble telescope without testing it • Where will engineering get largest payoff from CI? • Advances in scientific and mathematical underpinnings • Understanding large-scale complex systems and building them

11. What are the needed investments? • Build good domain pieces • Develop ways to model the behavior of those domain pieces • Develop ways to link them, and • Support people from the different areas to interact within one project/group • Optimizing the pieces does not necessarily lead to an optimized complete system!

12. How can NSF manage CI? • A directorate-neutral group is needed to manage the effort • Perhaps create a matrix-like organization • They need funds as well as management responsibility • This was a problem with ITR • The scientific issues here are the building of large-scale complex systems • Joint solicitations between Directorates have not been easy… • Support for maintenance must be provided through appropriate programs, probably in collaboration with industry • The burden cannot be left on the researchers • Federal support is often the only way to keep it open

13. How to engage new researchers in the CI? • NEES showed that one needs incremental rollouts • Lets one get feedback for design decisions • Gets users excited and makes them marketing agents • What’s the most engaging first element to have? • Having “the world in your hand” – information instantly and ubiquitously accessible • Removing the tether to the data acquisition mechanisms

14. Big payoffs • Networked embedded systems – it’s already emerging • MEMS devices • Linked systems • Need to deal with robustness and performance of these at the systems level • As opposed to using redundancy

15. Legal issues • IP and legal aspects need to be considered • Is the model the power grid? The internet? • Who owns the CI • Is it regulated?

16. Knowledge gaps to be bridged • Need to clearly articulate the grand challenges being addressed, and soon! • Make all information available to everyone, everywhere at any time • Democratize the world! • Get things out to people early so they can benefit (and get excited!) • Publicize well • This needs to be done at NSF level – it can’t be done at project level

17. Future activities • Domain experts/users involvement in CI research should be encouraged and incentivized • Evaluations and reconfigurations of efforts • Linkages with other projects should be valued • Linkages should be built from now among the different CI-related centers/communities • Cross-directorate workshops • The recent sensor program could be a model, although the size difference needs to be kept in mind • Must involve industry