Prof. Uğur Doğrusöz’s project on “Effective Analysis of Big Data Through Graph Visualization with A Unified Complexity Management Framework” received support form TÜBİTAK 1001 program.
Visualizing big data with graphs is an extremely valuable method for effective analysis of relational data as it makes analysis easier for human beings, bringing out broad relationships, uncovering patterns and emerging trends, and providing deeper insight for decision makers. Management of complexity of large graphs is a recurring requirement for today’s visual analysis software. Numerous complexity management techniques are available in graph visualization from simple operations such as filtering and hiding unwanted details, and clustering and collapsing clusters on demand.
Currently, there is no framework or data structure unifying various kinds of complexity management operations to be compatible and work together in sync. This project is to fill this void by building such a framework