Allen School professor Jeffrey Heer received a Test of Time Award at the 2022 IEEE Visualization & Visual Analytics Conference this week, marking the third consecutive year that his work has been recognized with the honor.
Heer, the co-director of the Interactive Data Lab, co-authored the winning paper, “Enterprise Data Analysis and Visualization: An Interview Study,” which provided key insights into understanding how data analysts operate and the challenges they encounter in their workflows. The paper was published in IEEE Transactions on Visualization and Computer Graphics in 2012 when Heer and two of his co-authors were researchers at Stanford University. The team presented its findings at the IEEE Conference on Visual Analytics Science and Technology (VAST).
The Test of Time Award recognizes papers published at previous conferences that have had a lasting impact both within and beyond the field of visualization over the ensuing decade.
“We’re thrilled that our colleagues still find our work relevant 10 years later,” said Heer, who holds the Jerre D. Noe Endowed Professorship at the Allen School. “While research ‘style’ probably plays a part, I think we were also in the right time and place as societal interest in data and analysis heated up. I also think it helps that our work has had interdisciplinary teams spanning human-computer interaction, data management, cognitive science and other disciplines, bringing more varied perspectives.”
As the team members investigated tools to aid data analysis, they were particularly interested in what Heer referred to as “the messy early stages of data cleaning and preparation.” While they had hands-on experience themselves, they wanted to gain a deeper understanding of the different types of analysts, the issues they encountered and the infrastructure that supported them.
To tackle this problem, the team launched a qualitative study, interviewing participants across a range of sectors, including health care, retail, social networking, finance, media, marketing and insurance. Among the insights they uncovered included analyst archetypes, how analysts collaborated with one another and with other business units and challenges they met in the analysis process.
“The study helped prioritize our thinking around the varied backgrounds of people working with data, including different levels of statistical and software development expertise, and how organizational dynamics shapes how the work gets done,” Heer said. “Both are important to consider if new tools are going to be usable and effective in practice.”
Heer credited first author Sean Kandel, his former Ph.D. student at Stanford and fellow co-founder of Trifacta, with leading the project. Kandel was the chief technical officer of Trifacta, which develops data wrangling software and a popular data preparation platform used by Google, NASA and others. Trifacta was acquired by Alteryx in February.
Co-author Andreas Paepcke is the director of data analytics and senior research scientist at Stanford. Co-author Joseph M. Hellerstein is the Jim Gray Professor of Computer Science at UC Berkeley and a co-founder of Trifacta. Hellerstein was at UC Berkeley at the time of the study.
Heer previously earned Test of Time Awards at VIS for his work on data-driven documents and narrative visualization. Since joining the Allen School faculty in 2013, he has been recognized with the Association for Computing Machinery’s ACM Grace Murray Hopper Award, the IEEE Visualization Technical Achievement Award and Best Paper Awards at the ACM Conference on Human Factors in Computing (CHI), EuroVis and IEEE InfoVis conferences. Last year, Heer was elected to the CHI Academy by the ACM Special Interest Group on Computer-Human Interaction (SIGCHI) for his substantial contributions in the areas of data visualization, data wrangling, text analysis, language translation and interactive machine learning.
Congratulations to Jeff and his co-authors!