# Presentation: 313552

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

- Discussion lead by Cherri Pancake
- Reported on by Yigal Arens

## 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

## The Challenge

- How we move from domain specific to general
- How we bring everything together
- Or at least have everything inter-operate

## 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

## 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

## 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

## 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

## 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

## 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)

## 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

## 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!

## 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

## 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

## 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

## 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?

## 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

## 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