Abstract/Summary

The development of IDV (Interactive Data Visualisation) takes into account users’ inputs, visualisation and analysis, in order to comprehend dataset. Insufficient research focuses on the methodology of developing IDV, with a particular emphasis upon acquiring and managing user demands as well as with different interpretation purposes and in various business contexts. It is vital to construct a framework for facilitating the IDV development. This can help visualisation designers to understand how users make sense of datasets and to deploy suitable interactive mechanisms for the corresponding demands. This research delivers an Abductive Framework for Interactive Data Visualisation Development (FINVID) based on exploration and illustration in two case studies. It mainly lays the building blocks of organisational semiotics, the doctrine of signs in the context of business and organisations. IDV development can be interpreted as a socio-technical design, which needs to establish a holistic view of users’ requirements, including both technical and social aspects. Abduction is also embedded in FINVID to iteratively acquire and incorporate students’ updating demands during the IDV process. IDV development is assumed to maintain an equilibrium between the following three aspects: process and artefact, data and interpretation and subjectivity and objectivity. To be specific, firstly, FINVID portrays IDV development as a norm-centric process, where users’ requirements can be articulated in norm specification to be documented and communicated among different stages of IDV development. Secondly, FINVID adapts an abductive reasoning process in IDV development, where users are empowered to continuously address their new request while exploring and analysing dataset via IDV. Finally, FINVID enables IDV to facilitate users’ knowledge exploration. It demonstrates six significant steps of IDV development with abductive nature. It specifies subactivities and techniques for each step, which involve different stakeholders. This method is used to acquire and refine users’ knowledge.