
Abstract
Data driven decision making has become the gold standard in science, industry, and public policy. Yet data alone, as an imperfect and partial representation of reality, is often insufficient to make good analysis decisions. Knowledge about the context of a dataset, its strengths and weaknesses, and its applicability for certain tasks is essential. In this work, we present an interview study with analysts from a wide range of domains and with varied expertise and experience inquiring about the role of contextual knowledge. We provide insights into how data is insufficient in analysts workflows and how they incorporate other sources of knowledge into their analysis. We also suggest design opportunities to better and more robustly consider both, knowledge and data in analysis processes.
Citation
Haihan Lin,
Maxim Lisnic,
Alexander Lex
Here’s what you need to know about my data: Exploring Expert Knowledge’s Role in Data Analysis
(to be published) Proceedings of 2025 IEEE VIS Conference, 2025.
IEEE VIS 2025 Honorable Mention