Defence Science and Technology Laboratory (Dstl) – 2019 – £80,000
Author: Kai
I am a Associate Professor in Data Analytics at the Middlesex University, London
EuroVis/Computer Graphics Forum 2020 There is fast-growing literature on provenance-related research, covering aspects such as its theoretical framework, use cases, and techniques for capturing, visualizing, and analyzing provenance data. As a result, there is an increasing need to identify and taxonomize the existing scholarship. Such an organization of the research landscape will provide a complete […]
IEEE Computer Graphics and Applications (CG&A) 2020 TimeSets is a temporal data visualization technique designed to reveal insights into event sets, such as all the events linked to one person or organization. In this paper we describe two TimeSets-based visual analytics tools for intelligence analysis. In the first case, TimeSets is integrated with other visual […]
IEEE Computer Graphics and Applications (CG&A) 2020 Interactive data exploration and analysis is an inherently personal process. One’s background, experience, interests, cognitive style, personality, and other sociotechnical factors often shape such a process, as well as the provenance of exploring, analyzing, and interpreting data. This viewpoint posits both what personal information and how such personal […]
This is the talk I given at the data+visual meeting in London in Aug 2016 Making sense of (big) data – visual analytics and provenance from Kai Xu
The paper is accepted by the VAST 2016 conference! The paper introduced a new tool called SenseMap that help users with online sensemaking for daily tasks such as find a camera, book a holiday, etc. The tool is available as a Chrome plugin (very early stage = lots of bugs 🙂 and there is more […]
This is a very large project funded by the European Commission, with about 20 partners and 100 personnel in many EU countries. The goal is to develop the next generation visual analytics system to address the Big Data challenges in the policing and criminal intelligence analysis. http://valcri.org/
A data visualisation project to address the data quality and lineage issues in sensemaking using provenance, using the TimeSet technique.
This paper describes a new method designed for temporal visualization with ‘set’ information. Here the ‘set’ can be different ‘theme’ or ‘topic’, such as person, location, organisation, etc. It was selected as the journal cover! More information here
The paper is accepted at VAST 2015, and later appeared in the journal TVCG. It introduces a new tool that can save a lot time doing the transcription and coding when analysing the data collected from qualitative studies such as thematic analysis. More details here
