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Sensemaking in Multi-artefact Information Tasks
Conference paper   Open access   Peer reviewed

Sensemaking in Multi-artefact Information Tasks

Tianwa Chen
CEUR Workshop Proceedings, Vol.3139, pp.77-86
International Conference on Advanced Information Systems Engineering (CAiSE), 34th (Leuven, Belgium, 06-Jun-2022–10-Jun-2022)
Rheinisch-Westfaelische Technische Hochschule Aachen, Lehrstuhl Informatik V
2022
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Abstract

Business process modeling Data curation Data quality Sensemaking
Confronted with information silos and a growing volume of data in an increasingly interconnected data driven world, knowledge workers, including technical and business users, often have to navigate multiple information artefacts to complete their tasks. These artefacts dispersed across various representational formats, and various information systems, can lead to overlapping, redundant or even conflicting information and inefficiency in information retrieval and knowledge workers’ understanding. Despite a growing market of tools, there is a lack of understanding in the current body of knowledge of how knowledge workers make sense of the multi-artefact information tasks and through that strategies. Motivated by the human-centric nature of the problem, this PhD project employs experiments, both in lab studies and on crowdsourcing platforms, and uses a number of behavioral and performance measures to unpack the cognitive demands on knowledge workers as they make sense of dual artefact tasks and multi-artefact tasks respectively. This project aims to propose an integrative model of sensemaking and cognitive processing in multi-artefact information tasks. The findings contribute to a better understanding of the sensemaking processes in various settings, inform modeling practice, and design supporting tools.

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