Effects of Sensemaking Translucence on Distributed Collaborative Analysis

TL;DR

This paper introduces a sensemaking translucence interface for collaborative crime analysis, which improves task performance but affects user experience, highlighting the trade-offs in designing distributed sensemaking tools.

Contribution

It presents a novel interface that enhances clue discovery and crime solving in collaborative analysis by making sensemaking processes more transparent.

Findings

Sensemaking translucence interface improves clue finding

Enhanced crime solving performance observed

Users rated the interface lower on subjective measures

Abstract

Collaborative sensemaking requires that analysts share their information and insights with each other, but this process of sharing runs the risks of prematurely focusing the investigation on specific suspects. To address this tension, we propose and test an interface for collaborative crime analysis that aims to make analysts more aware of their sensemaking processes. We compare our sensemaking translucence interface to a standard interface without special sensemaking features in a controlled laboratory study. We found that the sensemaking translucence interface significantly improved clue finding and crime solving performance, but that analysts rated the interface lower on subjective measures than the standard interface. We conclude that designing for distributed sensemaking requires balancing task performance vs. user experience and real-time information sharing vs. data accuracy.