Invited talk at the data+visual meetup

This is the talk I given at the data+visual meeting in London in Aug 2016

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 information here: Any comment/feedback is welcome!


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.


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.


Timesets: Timeline visualization with set relations (Information Visualisation journal 2016)

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


Sensepath: Understanding sensemaking process through analytic provenance (TVCG 2015)

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


Patterns of Life Visualisation (Phase 1 – 2014, £90K, Phase 2 – 2014-2015, £120k)

The project designs, implements, and evaluates new Visual Analytic tool for Pattern-of-Life analysis, which tries to understand and predict movement patterns of individuals or small groups.