THE MEGA-COLLABORATION

INTERFACE

Inspiration and Development

InspirationFrom Hurricane Katrina to Mega-Collaboration

Familiar Disaster Lessons

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.

Emerging Social Phenomena

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

Mega-Collaboration Requirements

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

Collaboration Mechanisms

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

MCTThe Mega-Collaboration Tool

MCT Design Goals

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.

Advantages

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.

Constraints

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.

DevelopmentThe Phases of MCT

Iterative Design Process1. Initial use cases

2. Conceptual Designa. Paper Prototype -> Focus Groups -> Specs

b. Working Prototype of the Sub-Team Interface

3. Phase 1 Prototype – Initial testing of the MCTa. Effects on team-building and decision-making

b. 23 participants -> 4 Test Teams, 4 Control Teams

c. Test team had full interface, control team only chat

d. Used pre/post surveys, analyzed chat/artifacts

4. Phase 2 Prototype – Redesign and Follow-Up Testinga. 10 participants for requirements gathering using previous

interface

b. 10 participants -> 5 using previous interface, 5 using new one

c. Tested five basic data entry and manipulation tasks

Current Use CasesType User

Motivating Goal for Use

Local Emergency Responders

District Fire Superintendent

Determination of Priorities

Volunteer Labor Organizations

Firefighters’ Union Coordinator

Resource Coordination

Non-Profit Aid Organizations

Red Cross Coordinator

Resource Coordination

Military Organizations

National Guard Coordinator

Response Activity Tracking

Federal Emergency Responders FEMA Coordinator

Jurisdiction Coordination

Concerned Common Citizens Store Manager

Resource Donation

Volunteer Workers Social Worker Resource Donation

Volunteer Experts Computer ExpertTechnology Donation

Affected Individuals RelativeRescue of Family Members

Interactions to be Supported

Stakeholders Formal Responders

Victims and Families

Volunteers

Types of Interaction Person to person

Group to group

Human to agent

Interaction RequirementsID Interaction ID Interaction1 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

User Interface

Results from Testing 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.

FuturePlans for What Comes Next

Powerful Data Manipulation

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

The Data Tree

Engineered Collaboration Protocols

Initial collaboration design in prototype:1. Each individual creates a data model.

2. Individuals look at each others models.

3. Individuals take turns building the team model.

4. Team elects a leader.

5. Leader develops action plan.

Possible alternative design using thinkLets1. Free Brainstorm

2. Fast Focus

3. Multi-Criteria

Ultimate Goal: The team dynamically designs the design

What is a ThinkLet?

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.

The ThinkLet Description Document

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

Engineered Collaborations

The Problem

with Dynamic Design:

Extensive New Testing

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.

The NeoCITIES Disaster Simulator

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

The Test Environment

Agent-Mediated Coordination

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.

The Concept

The Concept

The Concept

The Development Team 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

Questions?Discussion and Clarification