COVIAN · Comparative Visual Analytic techniques for Relational Information Visualisation
FP6 — Marie Curie Actions (Human Resources and Mobility)
- Duration
- 2006-01-01 → 2007-12-31
- EU contribution
- €80,000
- Participants
- 1
- Scheme
- IRG
Lines connect the coordinator with its partners.
Results in brief
Final Activity Report Summary - COVIAN (Comparative Visual Analytic techniques for Relational Information Visualisation)
Information visualisation is the visual representation of data to enable viewers, using their cognition and perception, to gain insight into the data and its causal relationships. Unlike scientific visualisation, which graphically displays physical phenomena, information visualisation as a field of research tackles the problem of visually displaying and interacting with abstract data that has no physical form. The contributions from this project include new clustering methods and hybrid layout techniques for large-scale graph drawing, case studies in software visualisation, and novel and personalised visualisation methods. Important outcomes include interactive structural clustering of graphs based on multi-representations, visualisation of variability in software product line engineering and underlying relation based measure of semantic similarity for gene ontology annotations in bioinformatics. This research has led to follow on projects with industry in visualisation with the Lero Irish Software Engineering Research Center and with Clique the network analysis and visualization research cluster.
Data: CORDIS, © European Union
Project objective
The basic hypothesis of this project is that relational information visualisation approaches, embodied in graph drawing techniques for the exploration and navigation of large graphs are not sufficient and that a hybrid approach which incorporates multiple views of the data should be taken. The scale and complexity of the relational data sets that people in domains such as biochemical engineering, software development and financial modelling are attempting to study, understand and reason about has motivated t his work. Societies continued reliance on information and communications technologies has resulted in organizations generating, gathering, and storing raw data" at a rate growing by 120% every year. Recent research suggests that the human race has created about 1 exabyte (1018) of data to date and that the next exabyte of data could be generated within the coming 3 years.The ability for even a mid-sized organization to store tens to hundreds of terabytes of data is within reach. Massive storage technologies are rapidly outstripping our ability to effectively analyse, explore, and understand such voluminous data. Our aims in this project include, the exploration of hierarchical compound graphs suitable for visualisation and exploration on different levels of abstraction and across different viewing paradigms, exploration of different space decomposition techniques suitable for our widely cited FADE paradigm, the study of fast approximate force directed layout algorithms in comparison with structure and city-plot layout techniques, the extension of our visual pr's abstraction technique from the node-link visualisation to both structure and city-plot views and an in-situ experimentation with our hybrid visualisation approach in a real world software engineering environment."
Original text from CORDIS.
Participants
- NATIONAL UNIVERSITY OF IRELAND, DUBLIN · DUBLINCoordinatorIreland
Links
Data: CORDIS, © European Union