Orange: from experimental machine learning to interactive data mining
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
prefuse: a toolkit for interactive information visualization
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GUESS: a language and interface for graph exploration
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
ASK-GraphView: A Large Scale Graph Visualization System
IEEE Transactions on Visualization and Computer Graphics
NodeTrix: a Hybrid Visualization of Social Networks
IEEE Transactions on Visualization and Computer Graphics
Jigsaw: supporting investigative analysis through interactive visualization
Information Visualization
C-GROUP: A Visual Analytic Tool for Pairwise Analysis of Dynamic Group Membership
VAST '07 Proceedings of the 2007 IEEE Symposium on Visual Analytics Science and Technology
Using Workflow Medleys to Streamline Exploratory Tasks
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
ManyNets: an interface for multiple network analysis and visualization
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Analyzing Social Media Networks with NodeXL: Insights from a Connected World
Analyzing Social Media Networks with NodeXL: Insights from a Connected World
The Network Lens: Interactive Exploration of Multivariate Networks Using Visual Filtering
IV '10 Proceedings of the 2010 14th International Conference Information Visualisation
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Social scientists and observational scientists have a need to analyze complex network data sets. Examples of such exploratory tasks include: finding communities that exist in the data, comparing results from different graph mining algorithms, identifying regions of similarity or dissimilarity in the data sets, and highlighting nodes with important centrality properties. While many methods, algorithms, and visualizations exist, the capability to apply and combine them for ad-hoc visual exploration or as part of an analytic workflow process is still an open problem that needs to be addressed to help scientists, especially those without extensive programming knowledge. In this paper, we present Invenio-Workflow, a tool that supports exploratory analysis of network data by integrating workflow, querying, data mining, statistics, and visualization to enable scientific inquiry. Invenio-Workflow can be used to create custom exploration tasks, in addition to the standard task templates. After describing the features of the system, we illustrate its utility through several use cases based on networks from different domains.