1. Inspiration and Development

2. From Hurricane Katrina to Mega-Collaboration

3. Large disasters like Hurricane Katrina offer familiar

lessons.
Responders need to gather information from diverse

and unexpected sources.
Responders also need to use the information

effectively.
There is limited information access in the disaster zone.

But many of the important decisions are made

elsewhere.
An agile, ad hoc response is needed.

Modern technology must support this.


4. There is a rush to organize:

Ephemeral groups (Farnham)

Hastily Formed Networks (Denning)

Grassroots Self-Organization

A trade-off emerges between:

Command-and-Control Efficiency

Creative Response to:

 Unforeseen Problems
 Volunteered Resources
Mega-Collaboration happens:

Thousands of people spontaneously collaborate over the

internet

5. There are several aspects to collaboration if enormous

virtual teams are to be effective.
Participants must to come to agreement on:

The problem definition

Group norms

Individuals’ roles

They must capture information and know how to pass

it to those who need it.
They must make decisions by forming a consensus

among massive numbers of participants

6. Teammates establish common ground by

combining their individual mental models of
the problem into a team model.
Convergent processes:

Information Pooling

Cognitive Consensus

Divergent processes:

Specialization

Transactive Memory

 Transmission of Information to the Appropriate Expert

7. The Mega-Collaboration Tool

8. This collaboration tool will go beyond existing social

networking tools.
The basic functional unit will consist of two interfaces:

The data entry interface will allow easy

entry, categorization, and visualization of large amounts of
critical data.
The interaction interface will support the formation of ad-hoc

teams and the engineering of collaboration protocols for
negotiation of coordinated action.
These basic units will be coordinated with a

third, agent-augmented mixed-initiative interface.
In this way, we hope to break any large problem into

small pieces and solve it in a coordinated manner.

9. This approach allows the combination of unstructured

chat with structured knowledge-building.
It splits a team of unlimited size into unlimited sub-

teams of limited size.
The communication and processing power of the

Internet can then be used to coordinate both intra-
group and inter-group interactions of these sub-teams.

10. Users must have the ability to gain access to the MCT.

Users must be interested in joining a team and in

helping each other.
Users must be able to learn the interface quickly and

under stressful conditions.
Users must understand both the interface and the

subject matter well enough to develop and negotiate
data models and action plans.

11. The Phases of MCT

12. Initial use cases
1.
Conceptual Design
2.
Paper Prototype -> Focus Groups -> Specs
a.
Working Prototype of the Sub-Team Interface
b.
Phase 1 Prototype – Initial testing of the MCT
3.
Effects on team-building and decision-making
a.
23 participants -> 4 Test Teams, 4 Control Teams
b.
Test team had full interface, control team only chat
c.
Used pre/post surveys, analyzed chat/artifacts
d.
Phase 2 Prototype – Redesign and Follow-Up Testing
4.
10 participants for requirements gathering using previous
a.
interface
10 participants -> 5 using previous interface, 5 using new one
b.
Tested five basic data entry and manipulation tasks
c.

13. Motivating Goal for
Type User
Use
Local Emergency District Fire Determination of
Responders Superintendent Priorities
Volunteer Labor Firefighters’ Union Resource Coordination
Organizations Coordinator
Non-Profit Aid Resource Coordination
Red Cross Coordinator
Organizations
National Guard Response Activity
Military Organizations
Coordinator Tracking
Federal Emergency Jurisdiction
FEMA Coordinator
Responders Coordination
Concerned Common Resource Donation
Store Manager
Citizens
Volunteer Workers Social Worker Resource Donation
Volunteer Experts Computer Expert Technology Donation
Rescue of Family
Affected Individuals Relative
Members

14. Stakeholders

Formal Responders

Victims and Families

Volunteers

Types of Interaction

Person to person

Group to group

Human to agent


15. ID Interaction ID Interaction
1 Find Site 10 Develop Mental Models
2 Use Site 11 Negotiate Group Models
3 Find Area of Interest 12 Vote
4 Participate 13 Take Turns
5 Converse 14 Exchange Information and Resources
6 Create Team 15 Form Teams of Agents
7 Join Team 16 Agent-Mediated Playoffs
8 Leave Team 17 Inter-Group Negotiation
9 Disband Team 18 Provide Help

17. Users wanted flexible categories.

Alternative hierarchies

Temporal versus logical organizations

Users wanted capable data handling.

Bulk input

Cut and paste

Free-form manipulation

Chain manipulation

Users wanted flexible interaction sequencing.

Emergent leadership helped and should be supported.

The merging of models increased data organization.


18. Plans for What Comes Next

19. Rapid input and output of data

Abstraction and Type Development

Move from a set of everything…

To many sets of specific types of things

Define the relationships between the sets

Requires cut and paste of entire structures


21. Initial collaboration design in prototype:

Each individual creates a data model.
1.
Individuals look at each others models.
2.
Individuals take turns building the team model.
3.
Team elects a leader.
4.
Leader develops action plan.
5.
Possible alternative design using thinkLets

Free Brainstorm
1.
Fast Focus
2.
Multi-Criteria
3.
Ultimate Goal: The team dynamically designs the

design

22. A thinkLet is a facilitation intervention that creates a

predictable, repeatable pattern of collaboration among
people working together toward a goal.
It includes everything a designer needs to reproduce

this pattern of collaboration.
It is the smallest unit of collaborative activity that the

process designer can manipulate.

23. ThinkLet name – descriptive and/or metaphorical

Choose this thinkLet… – list appropriate uses

Do not choose this thinkLet… – list inappropriate uses

Overview – give a brief narrative description

Inputs – enumerate what is needed to start

Outputs – enumerate what deliverables will result

Setup – describe the necessary preparations

Steps – describe each step of the procedure

Insights – discuss how and why it works, tips, pitfalls

Success stories – describe examples of successful field use

What’s in a name – explain how the thinkLet got its name


26. Validation Considerations

User testing to date has used static scenarios.

But lives hang in the balance in a real disaster.

The MCT must be tested in a safe environment that effectively

mimics real-world disaster conditions.
Disaster Simulation

With the expansion of our research team we have gained access

to such a test bed.
The NeoCITIES disaster simulator is

 A computer-based scaled-world simulation
 Designed to mimic the situation assessment and resource allocation
tasks of distributed emergency crisis-management teams.

27. The group activity consists of distributed individuals:

Jointly gathering information about emergency events,

Allocating the appropriate type and quantity of resources to

address these events
Detecting emerging threats and patterns of activity from an

underlying scenario
This experimental approach provides a holistic

assessment of distributed cognition by:
Providing real-time challenges

Allowing the tool to be used in addressing these challenges

Supporting intra and inter team communication measures


29. The autonomous software agents use data-mining

techniques to compare the models of all the sub-teams.
Small-worlds networking principles are used to link

the agents to each other.
Collaboration among the agents then leads to

suggestions for collaboration among the sub-teams.
Representatives from each sub-team are sent to a

“playoff” team.
Information from the playoff team then feeds back to

each sub-team.

30. The Concept

31. The Concept

32. The Concept

33. Chris Newlon

Graduate Student

PhD Candidate Informatics, Indiana University, Indianapolis, IN

Anthony Faiola

Executive Associate Dean, IU School of Informatics

Director, Media Informatics and Human-Computer Interaction

Ph.D. Purdue University, West Lafayette, IN (2005)

Karl MacDorman

Associate Professor, IU School of Informatics

Ph.D. Computer Science, University of Cambridge, UK (1996)

Himalaya Patel

Graduate Student

M.S. Candidate HCI, Indiana University, Indianapolis, IN

Mark Pfaff

Assistant Professor, IU School of Informatics

Ph.D. Information Sciences and Technology

The Pennsylvania State University (2008)

Gert-Jan de Vreede,

Kayser Distinguished Professor and Director, Center for

Collaboration Science, University of Nebraska at Omaha
 PhD Organizational Change, Delft University of Technology

34. Discussion and Clarification