User interaction is central to the data analysis process fostered by interactive visual analytic interfaces. However, in many current systems, user interaction is represented as an ephemeral action taken by a user that moves the system from one state to another. User interactions are quantitative bits of the analytic dialog between people, the system, and the data - and when modeled - can be tactfully integrated into visual analytic systems. We propose a library to help researchers and developers capture, interpret, and model interactions in web-based visual analytic tools. We introduce Interactive Analytics Library, a JavaScript library which enables developers to create data models of a user's interest based on their interactions with the system. By encapsulating interaction as an attribute of the data, managing weight vectors, and providing analytical models pre-tuned to generate results tailored to user interest, Interactive Analytics Library offloads responsibilities from developers of visual analytics so that they can focus more on the data representation and other front-end system components.
