Here’s what you need to know about my data: Exploring Expert Knowledge’s Role in Data Analysis

data_hunch_interview screenshot

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, Derya Akbaba, Miriah Meyer, Alexander Lex
Here’s what you need to know about my data: Exploring Expert Knowledge’s Role in Data Analysis
Preprint, doi:10.31219/osf.io/dn32z, 2023.

BibTeX

@article{2023_preprint_data_hunch_interview,
  title = {Here’s what you need to know about my data: Exploring Expert Knowledge’s Role in Data Analysis},
  author = {Haihan Lin and Maxim Lisnic and Derya Akbaba and Miriah Meyer and Alexander Lex},
  booktitle = {Preprint},
  doi = {10.31219/osf.io/dn32z},
  year = {2023}
}

Acknowledgements

We would like to thank our interviewees for their time and participation in the study, and the Visualization Design Lab for the fruitful discussions and feedback. ChatGPT was used to rephrase and improve the grammar of parts of this manuscript. We gratefully acknowledge funding from the National Science Foundation (OAC 1835904), and from the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation.