About the award winning thesis

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 integrative 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. 

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Despite a growing market of tools, there is a lack of understanding of the process that knowledge workers use to make sense of these integrative multi-artefact information tasks. The current body of knowledge does not adequately explain knowledge workers’ sensemaking behaviours and strategies when interacting with these tasks. Understanding the sensemaking behaviours of knowledge workers engaged in integrative multi-artefact information tasks is crucial for designing effective digital tools that enhance decision-making and problem-solving capabilities. Insight into the sensemaking practices can inform the development of intuitive systems that align with knowledge workers’ information foraging and processing needs, promoting efficiency and reducing cognitive workload. Additionally, these insights can drive innovation in digital information artefact design and information system design, and the findings can guide targeted training programs and skill development for knowledge workers with differing levels of expertise. Hence, the research considers investigating sensemaking practices in integrative multi-artefact information tasks can impact practical tool development, and our work can contribute to theoretical advancements in sensemaking, cognition, decision making, and human-computer interaction.

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To explore this problem, the research uses sensemaking as a theoretical lens to investigate knowledge workers’ behaviours in integrative multi-artefact information tasks. Motivated by the humancentric nature of the problem, this empirical study uses a number of behavioural and performance measures to unpack the cognitive demands on knowledge workers as they make sense of integrative multi-artefact information tasks. To ensure broader generalisability, the study is conducted in the context of two research settings. The first setting focuses on integrative multi-artefact information tasks in the case of the business process model and business rules, while the second setting focuses on integrative multi-artefact information tasks in data curation, specifically related to the data quality discovery in a repurposed dataset. The findings from these settings provide novel insights and understanding of the sensemaking processes in various settings and contribute to modelling practice and the design of supporting tools.