Tasks

\label{tasks}
While VA has always discussed applications in science, it began in intelligence, law enforcement, and emergency response [13]. It is telling that the visual analytics acronym VACCINE is actually a Department of Homeland Security project on command and control. Still, basic analysis processes are the same. The foraging and sense-making loops, the process of explore, enrich, and exploit, and 9 out of 10 of Amar et al.’s low-level components of analytic tasks apply in our qualitative observations [14][13][15]. Some important differences are worth a brief discussion. (1) Traditional analysts may get VA tool support for creating and assessing confidence in reasoning chains based on evidence with mixed reliability, while vaccine investigators ultimately rely on statistics. (2) Analysts often make written reports to decision makers, while outcomes for vaccine investigators may be less direct. A new collaboration, influence on a new study design or vaccine concept, or a new meta-analysis may be many steps removed from hypothesis generation. (3) Analysts work with independently produced data, often in teams. Vaccine investigators are used to working with data they produced themselves and which they may feel belongs to them. They choose trusted collaborations carefully to preserve their reputation and the novelty and integrity of their work. (4) Perhaps most importantly, vaccine investigators are not full-time analysts. Working with data across studies and assays on self-service interactive timescales is fundamentally new. As a result of such differences, our early research led us away from direct collaboration inside the tool, prompted us to add data contributors’ contact information and easy export for outside impact, and suggested that broad adoption required simplification, guidance, and smart default choices rather than paired analysis with a tool expert.
Scenario collection and iterative prototyping defined and prioritized our key tasks. While the concept of the DataSpace was new, investigators easily thought of questions to ask of such a system. Publications and staff who field requests for unplanned or meta-analysis were additional sources of questions. Our goal is to enable any investigator to conduct these tasks quickly and on their own:
Early on we found that even the most expert investigators are not used to some of the novel interpretation problems of combining complex data. Prototyping and task walkthroughs led to several key application principles: