I am one of the six Principal Investigators for the proposed Clique: Graph & Network Analysis Strategic Research Cluster (SRC). I lead the Visulisation workpackage within the Clique cluster. On the 11th of September along with my collaborators, industry partners and collaborating academic participants we had our full day site visit from an international review panel appointed by the SFI. As you can appreciate both the pre-proposal and full proposal required considerable effort to develop. After the pre-proposal and then full international postal reviews (which were very complete and detailed) we were one of the very few groups to be called to a site visit to present our cluster proposal.

The cluster program requires substantive engagement with local SMEs and larger corporations. CLIQUE has this with a great set of complementary industry partners. For this SRC this engagement is crucial as our partners have access to the voluminous data and applied research questions. These and other issues can give rise to insightful questions but yet basic research challenges. The entire process is very rigourous with substantial international peer-review at each stage. The site visit itself was an amazing opportunity to present our proposal to a panel of academic and industrial researchers leaders. I went first (No pressure!) after our cluster lead Pádraig Cunningham presented the cluster overview. Their questions and feedback were welcome, challenging and engaging! Clearly, the research problems identified here, when solved in Ireland can yield both high quality research outputs for us and significant industry impact.

In CLIQUE, we believe that research in data analysis in the coming years will be transformed by access to large-scale data resources. An area of particular importance in data analysis is the study of collections of entities and the links between them. This research cluster will address the development of computational techniques for the analysis and visualisation of such network data. The research will be driven by the requirements of network analysis in social networks and biological networks. While these are two quite different application areas, at a data level the problems have similar structure and the practice of applying techniques developed in one area to the other is well established. In particular the transfer of techniques developed for social network analysis to biological networks has had a huge impact in recent years.