An ever-increasing number of people and organizations find themselves awash in data with a desire to better understand it and communicate it to others. Virtually every domain has been affected by our increasingly powerful ability to monitor and record any kind of data that might be relevant. Widespread computational resources, memory, and networking make the acquisition of data arguably easier than it ever has been.
Unsurprisingly, a strong desire to better understand the data and communicate to others has accompanied this widespread access. In domains such as business, health, science, and engineering, people seek easier ways to extract knowledge and insight from their data. They also need to present the data and their findings to others in a comprehensible and effective manner. Many such "data scientists" desire easier ways to gain a broad understanding of data from their world and to communicate it to others.
Visualization is one technique that can be particularly effective for data analysis and presentation. The ability to represent data and its attributes in a visual manner often allows people to more easily grasp important characteristics of the data and to reach conclusions about its value. Similarly, people frequently prefer to represent data visually when explaining it to others.
Unfortunately, to create an information visualization today, a person either needs to be a programmer and use libraries and toolkits developed for that purpose or use (typically commercial) systems that provide limited visual representations. Neither solution is appropriate for data scientists who are not programmers but seek to design custom visualizations for the unique aspects of the data they explore.
This project is defining a theoretically-motivated framework for supporting visualization creation amongst these data-holders who lack programming skill. More specifically, we focus on the design and specification of interactive visualizations because the interactive aspects of visualizations are particularly challenging to create without the use of programming.
This research is supported by NSF Award IIS-1320537 (CGV: Small: Creating Information Visualizations without Programming).