InsideInsights: Integrating Data-Driven Reporting in Collaborative Visual Analytics

Andreas Mathisen, Tom Horak, Clemens N. Klokmose, Kaj Groenbaek, Niklas Elmqvist.
In: Computer Graphics Forum. Wiley Online Library, 649--661, 2019.
EuroVis '19 / CGF Journal Article
 teaser

Abstract

Analyzing complex data is a non-linear process that alternates between identifying discrete facts and developing overall assessments and conclusions. In addition, data analysis rarely occurs in solitude; multiple collaborators can be engaged in the same analysis, or intermediate results can be reported to stakeholders. However, current data-driven communication tools are detached from the analysis process and promote linear stories that forego the hierarchical and branching nature of data analysis, which leads to either too much or too little detail in the final report.

We propose a conceptual design for integrated data-driven reporting that allows for iterative structuring of insights into hierarchies linked to analytic provenance and chosen analysis views. The hierarchies become dynamic and interactive reports where collaborators can review and modify the analysis at a desired level of detail. Our web-based _InsideInsights_ system provides interaction techniques to annotate states of analytic components, structure annotations, and link them to appropriate presentation views. We demonstrate the generality and usefulness of our system with two use cases and a qualitative expert review.

Video

InsideInsights from Andreas Mathisen on Vimeo.

Blog Post

We have also published a blog post about InsideInsights on Medium, explaining the main ideas for a general audience.

Source Code & Online Demo

The source code of the InsideInsights prototype is publicly available on Github: github.com/90am/insideinsights.

Bibtex

@Article{Mathisen2019,
   author    = {Andreas Mathisen and Tom Horak and Clemens N. Klokmose and Kaj Grønbæk and Niklas Elmqvist},
   title     = {InsideInsights: Integrating Data-Driven Reporting in Collaborative Visual Analytics},
   journal   = {Computer Graphics Forum},
   volume    = {38},
   number    = {3},
   year      = {2019},
   pages     = {649--661},
   publisher = {Wiley Online Library},
   doi       = {10.1111/cgf.13717},
}