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Funding Highlights Networks Provenance Sensemaking Visual Analytics

2012-2013, Co-Investigator, Data Intensive Visual Analytics (DIVA), £220,000

This is jointly funded by the UK Research Council EPSRC (Engineering and Physical Sciences Research Council) and Defence Science and Technology Laboratory (dstl).

diva-screenshot

Besides the Middlesex University, there are three other partners in the research consortium: City University (principle investigator), Loughborough University, and Defence Science and Technology Laboratory (dstl).

The project aims to design and develop novel Visual Analytics techniques to address the data quality and uncertainty issues commonly encountered in Social Media analysis. Examples of such issues include the reliability of data source, errors and missing data, artefacts introduced by the analysis algorithms, and human bias in the decision making process. An important part to the solution will be the ‘provenance’, which is the detailed information of the entire decision making life cycle from data collection to reasoning and sense making. Provenance is expected to play a key role in identifying and tracking the data quality and uncertainty issues mentioned previously.

The initial application will be Human Terrain Analysis that provides Army troops with social insights into local population by integrative analysis of social media (e.g., Twitter) together with a range of other intelligence information (e.g., demographics). The results of Human Terrain Analysis will allow the ground troops to choose the appropriate engagement strategy with local communities and avoid any unnecessary confrontation and loss of life. The research outcomes are expected to later extend to other domains such cyber security, finance, and public health.

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Bioinformatics Highlights Journal Networks Papers Visual Analytics

Journal of Proteome Research (Impact Factor 5.46), to appear

Simone S. Li, Kai Xu, Marc R. Wilkins, “Visualisation and analysis of the complexome network of Saccharomyces cerevisiae”, Journal of Proteome Research (Impact Factor 5.46), to appear. PDF

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Conference Highlights Papers Visual Analytics

Paper in CHI 2011!

B. L. William Wong, Raymond Chen, Neesha Kodagoda, Chris Rooney, Kai Xu, “INVISQUE: intuitive information exploration through interactive visualization”, in Proceedings of the International Conference on Human Factors in Computing Systems (CHI) 2011, 311-316. PDF

INVISQUE now has its own website: http://www.invisque.com/

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Bioinformatics Data & Knowledge Highlights Journal Papers

Service Oriented Computing and Applications, 2011

Kai Xu, Qi Yu, Qing Liu, Ji Zhang, Athman Bouguettaya, “Web Service management system for bioinformatics research: a case study”, Service Oriented Computing and Applications, Volume 5, Issue 1 (2011), Page 1-15. PDF

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Bioinformatics Conference Highlights Networks Papers Visual Analytics

Graph Drawing 2009

Kai Xu, Rohan Williams, Seok-Hee Hong, Qing Liu, and Ji Zhang, “Semi-Bipartite Graph Visualization for Gene Ontology Networks”, Proceedings of the 17th International Symposium on Graph Drawing (GD’09), 244-255, September 2009. Chicago, USA. PDF

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Data & Knowledge Highlights Journal Papers

The VLDB Journal, 2008

Ke Deng, Xiaofang Zhou, Heng Tao Shen, Qing Liu, Kai Xu, and Xuemin Lin, “A multi-Resolution Surface Distance Model for k-NN Query Processing”, The VLDB Journal, 17(5):1101-1119, 2008. PDF

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Bioinformatics Conference Highlights Networks Papers Visual Analytics

The Sixth International Asia-Pacific Symposium on Visualization (APVIS’07)

Kai Xu, Andrew Cunningham, Seok-Hee Hong, and Bruce H. Thomas, “GraphScape: integrated multivariate network visualization”, Proceedings of the 6th International Asia-Pacific Symposium on Visualization (APVIS’07), 33-40, Februray 2007. Sydney, Australia. PDF

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Data & Knowledge Highlights Journal Papers

IEEE Transaction on Knowledge and Data Engineering (TKDE) 2006

Kai Xu, Xiaofang Zhou, Xuemin Lin, Heng Tao Shen, and Ke Deng, “A Multiresolution Terrain Model for Efficient Visualization Query Processing”, IEEE Transaction on Knowledge and Data Engineering (TKDE), 18(10):1382-1396, 2006. PDF

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Bioinformatics Conference Highlights Networks Papers Visual Analytics

Asia-Pacific Symposium on Information Visualisation 2006

Tim Dwyer, Seok-Hee Hong, Dirk Koschutzki, Falk Schreiber, and Kai Xu, “Visual analysis of network centralities”, Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation (APVIS’06), 189-197, February 2006. Sydney, Australia.

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Awards Highlights Networks Visual Analytics

Graph Drawing Contest – History of the World Cup Competition

2006 – Winner of Graph Drawing Contest – History of the World Cup Competition, Karlsruhe, Germany.

This is a visualization of the final stage of the FIFA World Cup since it inception in 1930. All the countries that ever entered World Cup final stage are included and grouped according to continent. The nodes appearing shows the countries entered that specific world cup and its size reflects its perform.

This is a visualization of all the games played at the final stage of the FIFA world cup since its begining at 1930 till 206. Each World Cup is shown in a plane. Each country is a node and there is an edge pointing from team A to team B is A beats B in a game. The node size indicates the country performance that year. The countries are arranged into concentric circles according to their overall performance in the entire world cup history: the centre has the highest centrality (i.e., best performance) and the out most circle has the countries with the worst performance. Countries are also grouped into continents (UEFA, CONCACAF, etc), which is indicated by the colour.