Artificial Intelligence and Law

, Volume 18, Issue 4, pp 387–412

Discovery-led refinement in e-discovery investigations: sensemaking, cognitive ergonomics and system design



Given the very large numbers of documents involved in e-discovery investigations, lawyers face a considerable challenge of collaborative sensemaking. We report findings from three workplace studies which looked at different aspects of how this challenge was met. From a sociotechnical perspective, the studies aimed to understand how investigators collectively and individually worked with information to support sensemaking and decision making. Here, we focus on discovery-led refinement; specifically, how engaging with the materials of the investigations led to discoveries that supported refinement of the problems and new strategies for addressing them. These refinements were essential for tractability. We begin with observations which show how new lines of enquiry were recursively embedded. We then analyse the conceptual structure of a line of enquiry and consider how reflecting this in e-discovery support systems might support scalability and group collaboration. We then focus on the individual activity of manual document review where refinement corresponded with the inductive identification of classes of irrelevant and relevant documents within a collection. Our observations point to the effects of priming on dealing with these efficiently and to issues of cognitive ergonomics at the human–computer interface. We use these observations to introduce visualisations that might enable reviewers to deal with such refinements more efficiently.


Electronic data disclosure e-Discovery e-Disclosure Investigations Sensemaking Information interaction Collaboration Visualization 

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Interaction Design Centre, School of Engineering and Information SciencesMiddlesex University The BurroughsLondonUK
  2. 2.UCL Interaction CentreUniversity College LondonLondonUK

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