Responding to the Unexpected

1. Responding to the Unexpected Earthquake Case Investigation 2/27/2002 NSF Workshop: Responding to Unexpected

2. Panel members • Howard Shrobe • Art Lerner-Lam • Fred Krimgold • Charles Scawthorn • Frieder Seible • Laura Steinberg NSF Workshop: Responding to Unexpected

3. Issues • Identifying inadequacies • Preparation • Response and rehabilitation • Mitigation and preparation: identification of threat environment • Cross-cutting themes • Human resources • IT environment • Policy and legal environment • Cultural • Science and engineering research NSF Workshop: Responding to Unexpected

4. Themes • Policy, regulation, and jurisdiction • Prior knowledge base, RT data collection • IT infrastructure • Human assistance and performance • Organizational models (virtual, ad hoc, etc) • Security • Integration and transfer NSF Workshop: Responding to Unexpected

5. Major questions • Identifying inadequacies • Overcoming inadequacies • Identifying “unexpectedness”: transition from routine to unexpected • Security and open access to data • Integration of RT data • Role of standards • Role of monitoring and surveillance NSF Workshop: Responding to Unexpected

6. Definition of unexpectedness • Uncertainty trajectories before, during, and after event • “non-linearity” and “discontinuity”, sensitivity • Cascading effects (include. Social) • Response • Impacts not known until after • Incorporation of information in real time: modifying assessments • Common processes generic to all events that can trigger action • “orgware” et al. as technologies to improve communication NSF Workshop: Responding to Unexpected

7. Technological challenges on execution • E.g. dynamic integration of information • Dealing with unexpected in absence of planning • Dealing without planning • Search and rescue precedents • “sensory alertness” • Capacity for rapid, flexible response • Not overdefining, but generalizing capabilities • Dealing with unexpected losses of capability • Existence of generic processes • speed NSF Workshop: Responding to Unexpected

8. Research in public choice and modifying behavior • Anticipate public choice arena • Decision making and drivers • Investment incentives • Reducing the envelope • Systematic investigation of eq impacts and experience • Reaction in real time, impact on choice, social science research • NTSB approach • Extreme pressure from public • Returning the system to normalcy • Never the same • Process of recovery lengthy • Expectations are very high NSF Workshop: Responding to Unexpected

9. Providing research in problem formulation • Case studies • Examples of success • WTC: understood vulnerability, if not specifics • CA in ‘89 and ‘94 • Highway rebuilds • OEM learning curve by ‘94 • Bringing different organizations together • Orgware • Administrative structures for decision making and response • Adjustable autonomy. • Models and prioritization of efforts to minimize risk, harm, etc • Where are there vulnerabilities? • Eq experience useful: land use and fault maps • Resources and characterization of hazards NSF Workshop: Responding to Unexpected

10. Flexibility of response • Composing capabilities out of combinations • Speed of response • Robustness of response • Scenarios and training • Info overload • Redundancy of capability, but not complete distribution • First response heterogeneity • Interoperability • Societal issues as well as technological • Robustness design of infrastructure couples to robust response. NSF Workshop: Responding to Unexpected

11. Characteristic design elements of infrastructure to improve robustness • Analogs in cs • Interoperation • Standards, common data elements • Cultural changes in the tech community • Information survivability • Redundancy not subject to common-mode failure • Engineering for variability • Meaningful fault models • Threat models ? • Adaptive vs. dumb threats NSF Workshop: Responding to Unexpected

12. Swiren • unfamiliar hazards in unexpected places (eq in NYC) • Calibration of HAZUS: modification of default database (NY study) • Need more, better modeling e.g. hurricanes (coming out) • Educate decision makers, public • Correlating eq loss to other hazard loss: more “economical” solution NSF Workshop: Responding to Unexpected

13. David • Better models Existing database Ability to get and incorporate new information Not coming close to timeline in events Traffic mgmt Building floorplans Deep infrastructure Collapse/ building damage data Losing communications Databases don’t exist or are not robust enough(fast, redundant) NYC data lost, new setup. Eq are good project because of complexity, spatial extent Evaluation for habitability Debris management and tasking Gaps in regional operations coordination (Northridge had 60 jurisdictions) Field checking before FEMA assistance/ data Connection between loss estimation and govt assistance Demographic data Overwhelming dispatch centers (unanswered 911 calls in CA) Quick environmental evaluation Processes in response environment (generic; analysis of timelines and meet them technologically) Monitoring systems not in place Validating and verifying socio-economic data, data integration issues End-user systems have to be simple: stress = stupidity • Ubiquitous sensoring • Scale, granularity, can change in time • Process NSF Workshop: Responding to Unexpected

14. Data issues • New information vs. recasting of existing info • Process context should drive database research • Integration of different data formats • Recast software discussion in terms of characteristics of response processes • Problem solved for inter-company integration: what’sspecial about unexpected events? • Undesired linking / security and access management • Micro-metadata. Reliabiltiy, calibration of sensor nets • Common datga elements • Connecting operational data with incoming data, and modeling data • Information integration NSF Workshop: Responding to Unexpected

15. If we had the data and could provid info: • What would they do differently? For an unexpected event. • What have we learned from the past that helps us deeal with data integration • Different groups operating in pararllel with different tasks, with operational integration • Tension arising from information overload • Active real time data integration, decided by ebd-users: not just passive. NSF Workshop: Responding to Unexpected

16. Try to formalize exchange between practitioners and research NSF Workshop: Responding to Unexpected

17. Concept of triage in information management • Info overload • Training to improve dialog NSF Workshop: Responding to Unexpected

18. Feds don’t understand state and local aresponse • How do state and local governments respond to disasters? • How do policies and info get down to local level • Heterogeneous local response NSF Workshop: Responding to Unexpected

19. Military AI model • Decisions in high-risk environments • Stand-off decision making / robotics/ stand-off sensors/ AI NSF Workshop: Responding to Unexpected

20. NSF and practitioner interactions • Applications and bridging culture • Mel: what is the form of the research? • Pilots, test beds, scenario • Mission agencies • Private sector • Program structure is a challenge NSF Workshop: Responding to Unexpected

21. Case study • Observer participants in response NSF Workshop: Responding to Unexpected

22. Recent experience • Use certain examples to bring IT and social science community together • Airline security, communicalbe diseases • Half-life lessons, learn from experience, but take advantage of timing NSF Workshop: Responding to Unexpected

23. Tech transfer access to practitioners NSF Workshop: Responding to Unexpected

24. Flexibility • Improve interagency organization and coordination • Multiple agencies wil always be involved • Some organization streuctgure better than others • Best interagency structures • Improving adaptive behavior: analogy to war games and simulation tools • Factor in heterogeniety of population: need to be sensitive to feedback related to heterogeneity NSF Workshop: Responding to Unexpected

25. Drawing in practitioners • “clinical” track • Working with regional govt agencies • Formal and informal • Tech partnerships • Testbeds with locals and regionals • Get some data from them, some infromation • Professional organizations • Effort to get eq simulation of Kobe (whole sim city) challenge posed as a competition “rescue simulation” robocup.org • Simulations should be used to generate unexpected event NSF Workshop: Responding to Unexpected

26. Classified material • Data may not be available: dilemma • Access to infrasystems may be denied • “sanitized” data, abstracted form • Reduced precision, dithering • Policies on what can be shared govt: no risk approach CoE invnetory of dams off the web • Infrastructure security • Security clearance situaion has changed • Civilian classification systems • Privacy-preserving data mining • Study implications of classifying data on ability to respond to unexpected. • Time varying need to know and thus time-varying classification • Dithering context specific NSF Workshop: Responding to Unexpected

27. Modality issues • Classification of data • Structure of reserasch program • Issues of transition NSF Workshop: Responding to Unexpected

28. Cahan • 9/11 Research issues • Redundancy, mutual-aid, drills, pulling the trigger on contacts and technology • Management logistics and communications NSF Workshop: Responding to Unexpected

29. Case study • Spirit of Pier 92: 9/11 case study • Folios for each specialty NSF Workshop: Responding to Unexpected

30. Documentary of behind the scenes NSF Workshop: Responding to Unexpected

31. Companion website to feature lessons and clips NSF Workshop: Responding to Unexpected

32. I-Teams Implementation strategy: OMB geospatial initiative: state plans. NSF Workshop: Responding to Unexpected

33. Consensus portal elements (life-cycle of 9/11 has not eneded) • Team lists • Calendar • Authoritites • GIS • Security • Public comments NSF Workshop: Responding to Unexpected

34. Joe Picciano FEMA Reg 2 • Need to consider worst-case scenario: out of box, not capable of predicting • Federal partnership • Initial priorities • Life-saving support • Mobilization centers • Infrastructure • Devbris assessment NSF Workshop: Responding to Unexpected

35. Effort coordination: existing capabilities (7000 people) NSF Workshop: Responding to Unexpected

36. Driven by IT • Wireless • Dfo setup • Coordnation with major providers • Portable satellites NSF Workshop: Responding to Unexpected

37. Possibilites • National all-response information management system for local and state governments Resource links Existing databases Critical first response availability Mainatined by public-private consortium R&D for high-rise and dirty fires Enhanced personal communications for first responders Real time computer simulation for first responders Review of crisis managmenet educatgional programs NSF Workshop: Responding to Unexpected

38. 48-72 hours to set up: critical need for local and stgate first response NSF Workshop: Responding to Unexpected

39. Federal response plan Interagency WMD and terrorism Earthquaes NSF Workshop: Responding to Unexpected

40. Transportations Lead agency DoT FAA closed down airspace Distribution of emergency supplies and officials Development of standards and models for catastrophic events in urban environments Pre-identification of critical routes Evacuation alternatives and event-dependence (NYC and hurricanse) Cricitacl asset transprotation planning Linkages to regional planning for wide-=spread events Enhanced Remote sensing systems for evac and id of critical assset requirements NSF Workshop: Responding to Unexpected

41. Communications Needs Stadards Protocols Modernization training Develop a national emergency managmenenmt communications systems with applications at state and local levels NSF Workshop: Responding to Unexpected

42. Public works and engineering (ACOE) Debris managmgnet New technologies for sseparation and managmenet Study on existing infrastufcture load impact and project life NSF Workshop: Responding to Unexpected

43. Firefighting Incident managmenet teams NSF Workshop: Responding to Unexpected

44. Information and planning FEMA lead on infomration Decision support NSF Workshop: Responding to Unexpected

45. GIS Hot spots Site hazard analysis Estimate total debris NSF Workshop: Responding to Unexpected

46. possibilities National response information managmenet system Enhanced urban infrrastrucgure database (911, hazus, etc) and loss modeling More use of remote sensing NSF Workshop: Responding to Unexpected

47. Resource support GSA Development of immediate resource requirment list linked to national data base NSF Workshop: Responding to Unexpected

48. Health and medical Us public health service NSF Workshop: Responding to Unexpected

49. Urban search and rescue Nre first responder strategies NSF Workshop: Responding to Unexpected

50. Hazmat (EPA New strategies for: Health registries Indoor and outdoor residential hazards NSF Workshop: Responding to Unexpected