Paths Explored, Paths Omitted, Paths Obscured: Decision Points & Selective Reporting in End-to-End Data Analysis

TL;DR

This paper investigates how researchers make and omit decisions during data analysis, highlighting the influence of methodological, theoretical, and practical factors, and proposes visualization tools and design opportunities to improve transparency and robustness.

Contribution

It provides an empirical analysis of decision-making in data analysis through literature review and interviews, and introduces visualization methods for communicating decision processes.

Findings

Researchers base decisions on methodological and theoretical concerns.

Exploration of alternatives is driven by search for desirable results and other factors.

Visualizations can effectively communicate decision pathways in analysis.

Abstract

Drawing reliable inferences from data involves many, sometimes arbitrary, decisions across phases of data collection, wrangling, and modeling. As different choices can lead to diverging conclusions, understanding how researchers make analytic decisions is important for supporting robust and replicable analysis. In this study, we pore over nine published research studies and conduct semi-structured interviews with their authors. We observe that researchers often base their decisions on methodological or theoretical concerns, but subject to constraints arising from the data, expertise, or perceived interpretability. We confirm that researchers may experiment with choices in search of desirable results, but also identify other reasons why researchers explore alternatives yet omit findings. In concert with our interviews, we also contribute visualizations for communicating decision processes throughout an analysis. Based on our results, we identify design opportunities for strengthening end-to-end analysis, for instance via tracking and meta-analysis of multiple decision paths.