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Highlights Networks Papers Sensemaking Visual Analytics

RAMPVIS: Answering the Challenges of Building Visualisation Capabilities for Large-scale Emergency Responses

Epidemics (journal) This paper describes the collaborative efforts from the RAMPVIS consortium to help the epidemiologists modelling the various aspects of Covid19, including the spread of the disease and the impact of different isolation policies. Started as a voluntary effort, there are many challenges faced by the group of close to 20 visualisation experts, including […]

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Funding Highlights Visual Analytics

RAMP VIS – Visual Analytics for Covid-19 (2021-2022, £430,000)

EPSRC, 2021-2022, £430,000 This is a collaborative efforts with many visualisation researchers across the UK to provide visual analytics support in the fight against Covid-19. It started as a volunteer effort, led by Prof. Min Chen from Oxford University. A team of 20 visualisation researchers from over 10 different universities worked closely with epidemiologists who […]

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Highlights Papers Provenance Sensemaking Visual Analytics

Survey on the Analysis of User Interactions and Visualization Provenance (EuroVis/Computer Graphics Forum)

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 […]

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Highlights Papers Provenance Sensemaking Visual Analytics

TimeSets: Temporal sensemaking in intelligence analysis (IEEE Computer Graphics and Applications)

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 […]

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Highlights Papers Provenance Sensemaking Visual Analytics

Putting the “i” in interaction: Interactive interfaces personalized to individuals (IEEE Computer Graphics and Applications)

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 […]

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Highlights Provenance Sensemaking Visual Analytics

Provenance analysis for sensemaking

IEEE Computer Graphics and Applications 2020 This is the introduction I wrote (with the other co-editors) for the special issue on Provenance Analysis for Sensemaking in the IEEE Computer Graphics and Applications. This special issue reports the outcomes from the Dagstuhl Seminar I co-organised a year earlier on the same topic. https://ieeexplore.ieee.org/document/8889811

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Highlights Invited talks Provenance Sensemaking Visual Analytics

Invited talk at the data+visual meetup

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

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Highlights Papers Provenance Sensemaking Visual Analytics

SenseMap: Supporting Browser-based Online Sensemaking through Analytic Provenance (VAST 2016)

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 […]

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Funding Highlights Provenance Sensemaking Visual Analytics

VALCRI – Visual AnaLytics for sense-making in CRiminal Intelligence analysis (2014-2018, €13 million)

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/

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Funding Highlights Provenance Sensemaking Visual Analytics

TimeSets: Timeline visualisation for provenance-based big data sensemaking (2016, £100k)

A data visualisation project to address the data quality and lineage issues in sensemaking using provenance, using the TimeSet technique.