Detailed Record


Visualization and Automation in Data Science: Exploring the Paradox of Humans-in-the-Loop


Abstract We explore the interplay between automation and human involvement in data science. Emerging from in-depth discussions at a Dagstuhl seminar, we synthesize perspectives from Automated Data Science (AutoDS) and Interactive Data Visualization (VIS) – two fields that traditionally represent opposing ends of the human-machine spectrum. While AutoDS seeks to enhance efficiency through increasing automation, VIS underscores the critical value of human involvement in providing nuanced understanding, creativity, innovation, and contextual relevance. We explore these dichotomies through an online survey and advocate for a balanced approach that harmonizes the speed and consistency of effective automation with the indispensable insights of human expertise and thought. Ultimately, we confront the essential question: what aspects of data science should we automate?
Authors Jen Rogers , Marie Anastacio , Jürgen Bernard ORCID , Mehdi Chakhchoukh ORCID , Rebecca Faust ORCID , Andreas Kerren ORCID , Steffen Koch ORCID , Lars Kotthoff University of WyomingORCID , Çağatay Turkay ORCID , Emily Wall ORCID
Journal Info Institute of Electrical and Electronics Engineers | 2024 IEEE Visualization in Data Science (VDS) , pages: 1 - 5
Publication Date 10/14/2024
ISSN
TypeKeyword Image article
Open Access closed Closed Access
DOI https://doi.org/10.1109/vds63897.2024.00005
KeywordsKeyword Image