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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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Papers Provenance Sensemaking Visual Analytics

Provenance and logging for sense making

Dagstuhl Reports 2019 This the report for the Dagstuhl Seminar I co-organised. Sense making is one of the biggest challenges in data analysis faced by both the industry and the research community. It involves understanding the data and uncovering its model, generating a hypothesis, selecting analysis methods, creating novel solutions, designing evaluation, and also critical […]

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Machine learning Papers Provenance Sensemaking Visual Analytics

An Approach to Human-Machine Teaming in Legal Investigations Using Anchored Narrative Visualisation and Machine Learning

The First International Workshop on AI and Intelligent Assistance for Legal Professionals in the Digital Workplace (LegalAIIA 2019) During legal investigations, analysts typically create external representations of an investigated domain as resource for cognitive offloading, reflection and collaboration. For investigations involving very large numbers of documents as evidence, creating such representations can be slow and […]

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Papers Provenance Sensemaking Visual Analytics

Uncertainty of visualizations for SenseMaking in criminal intelligence analysis

EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3) 2018 Uncertainty in visualization is an inevitable issue for sensemaking in criminal intelligence. Accuracy and precision of adoptedvisualization techniques have got greater role in trustworthiness with the system while finding out insights from crime relateddataset. In this paper, we have presented a case study to […]

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Funding Machine learning Sensemaking Social media Visual Analytics

Combining Data Visualization with Machine Learning to Make Sense of Large Social Media Data

Funder: Microsoft Azure Research Award Date: 2018-2019 Funding: US$20,000 In this project we utilise the Microsoft Azure to analyse over 1.5 billion tweets using an updated SAVI (Social Analytics VIsualisation) system.

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Provenance Sensemaking Services Visual Analytics

Organiser of the Dagstuhl Seminar on “Provenance and Logging for Sense Making”

Dagstuhl seminar is a series of Computer Science seminars hosted at the Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH in Germany. It is an invitation only seminar and a selected group of leading international experts on a certain topic spend a week in the Dagstuhl castle discussing the solutions to the most challenging research problems related […]

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Papers Provenance Sensemaking Visual Analytics

Analytic Provenance as Constructs of Behavioural Markers for Externalizing Thinking Processes in Criminal Intelligence Analysis

Chapter 10 of the book Community-Oriented Policing and Technological Innovations (2018) Studying how analysts use interaction in visualization systems is an important part of evaluating how well these interactions support analysis needs, like generating insights or performing tasks. Analytic Provenance commonly known as interaction histories contains information about the sequence of choices that analysts make […]

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Papers Provenance Sensemaking Visual Analytics

Analytic provenance for criminal intelligence analysis

Chinese Journal of Network and Information Security (2018) In criminal intelligence domain where solution discovery is often serendipitous,it demands techniques to provide transparent evidences of top-down and bottom-up analytical processes of analysts while sifting through or transforming sourced data to provide plausible explanation of the fact.Management and tracing of such security sensitive analytical information flow […]

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Machine learning Papers Sensemaking Visual Analytics

Evaluating interactive visualization of multidimensional data projection with feature transformation

Multimodal Technologies and Interaction 2017 There has been extensive research on dimensionality reduction techniques. While these make it possible to present visually the high-dimensional data in 2D or 3D, it remains a challenge for users to make sense of such projected data. Recently, interactive techniques, such as Feature Transformation, have been introduced to address this. […]

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Funding Services Visual Analytics

Member of the EPSRC Peer Review College

EPSRC stands for ‘Engineering and Physical Sciences Research Council’. It is the main funding body for UK research in the areas including engineering, mathematics, and physics. Computer Science is one of the EPSRC research areas. All the funding applications to EPSRC are reviewed by its Review College members.