TRACE: A Stigmergic Crowdsourcing Platform for Intelligence Analysis

Huichuan Xia, Carsten Oesterlund, Brian McKernan, James E. Folkestad, Patrícia Rossini, Olga Boichak, Jerry Lamont Robinson, Kenski K, Myers R, B. A. Clegg, Jennifer Stromer-Galley

Research output: Chapter in Book/Entry/PoemConference contribution


Crowdsourcing has become a frequently adopted approach to solving various tasks from conducting surveys to designing products. In the field of reasoning-support, however, crowdsourcing-related research and application have not been extensively implemented. Reasoning-support is essential in intelligence analysis to help analysts mitigate various cognitive biases, enhance deliberation, and improve report writing. In this paper, we propose a novel approach to designing a crowdsourcing platform that facilitates stigmergic coordination, awareness, and communication for intelligence analysis. We have partly materialized our proposal in the form of a crowdsourcing system which supports intelligence analysis: TRACE (Trackable Reasoning and Analysis for Collaboration and Evaluation). We introduce several stigmergic approaches integrated into TRACE and discuss the potential experimentation of these approaches. We also explain the design implications for further development of TRACE and similar crowdsourcing systems to support reasoning.
Original languageEnglish (US)
Title of host publicationProceedings of the 51st Hawaii International Conference on System Sciences
Number of pages9
StatePublished - 2019


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