COLAB: A Laboratory Environment for Studying Analyst Sensemaking and Collaboration

Abstract

COLAB is a laboratory for studying tools that facilitate collaboration and sensemaking among groups of human analysts as they build interpretations of unfolding situations based on accruing intelligence data. The laboratory has three components. The Hats Simulator provides a challenging problem domain involving thousands to millions of agents engaged in individual and collective behaviors, a small portion of which are terrorist. The second component, the AIID Bayesian blackboard, is an instrumented working environment within which analysts collaborate to build their interpretation of the problem domain. The third component is a web based user interface that integrates the Trellis hypothesis authoring and management tool with a query language to allow human analysts to interact with AIID and each other. Looking to the big picture, COLAB is not merely a laboratory for studying collaboration and shared knowledge creation. COLAB is a tool to explore and develop the analyst working environment of the future, in which analyst tools and methods for collaboration in edge organizations are developed and tested. We present COLAB and its components and outline our plans for the system.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2005
Accession Number
ADA464219

Entities

People

  • Clayton T. Morrison
  • Paul R. Cohen

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Counter WMD
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Automated Speech Recognition
  • Command And Control
  • Computer Simulations
  • Computers
  • Data Mining
  • Data Visualization
  • Databases
  • Information Science
  • Intelligence Analysis
  • Language
  • Lisp Programming Language
  • Operating Systems
  • Organizational Structure
  • Task Forces
  • Teamwork
  • User Interface

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Distributed Systems and Data Platform Development
  • Systems Analysis and Design

Technology Areas

  • AI & ML