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Exploratory computing: a challenge for visual interaction

The advent of the Big Data challenge has stimulated research on methods to deal with the problem of managing data abundance. Many approaches have been developed, but for the most part, they attack one specific side of the problem: e.g. efficient querying, analysis techniques that summarize data or reduce its dimensionality, data visualization, etc. The approach proposed in this poster aims instead at taking a comprehensive view: first of all, it supports human exploration as an iterative and multi-step process and therefore allows building upon a previous query on to the next, in a sort of "dialogue" between the user and the system. Second, it aims at supporting a variety of user experiences, like investigation, inspiration seeking, monitoring, comparison, decision-making, research, etc. Third, and probably most important, it adds to the notion of "big" the notion of "rich": Exploratory Computing (EC) aims at dealing with datasets of semantically complex items, whose inspection may reach beyond the user's previous knowledge or expectations: an exploratory experience basically consists in creating, refining, modifying, comparing various datasets in order to "make sense" of these meanings. A crucial challenge of EC lies at the user interface level (data visualization, feedback, relevance of the results, interaction possibilities): how to convey, in an effective manner, all the possible turn-takings of this "dialogue" between the user and the system.