How Data Workers Cope with Uncertainty: A Task Characterisation Study

論文URL:http://dl.acm.org/citation.cfm?doid=3025453.3025738

論文アブストラクト:Uncertainty plays an important and complex role in data analysis, where the goal is to find pertinent patterns, build robust models, and support decision making. While these endeavours are often associated with professional data scientists, many domain experts engage in such activities with varying skill levels. To understand how these domain experts (or "data workers") analyse uncertain data we conducted a qualitative user study with 12 participants from a variety of domains. In this paper, we describe their various coping strategies to understand, minmise, exploit or even ignore this uncertainty. The choice of the coping strategy is influenced by accepted domain practices, but appears to depend on the types and sources of uncertainty and whether participants have access to support tools. Based on these findings, we propose a new process model of how data workers analyse various types of uncertain data and conclude with design considerations for uncertainty-aware data analytics.

日本語のまとめ:

専門家意外のデータ科学者が、値の欠如などからなるデータの不確実性をどのように分析し、対処するかを調査しています。調査の結果、不確実なデータに対し、「無視」「理解」「最小化」「利用」の4パターンの対処を取ることが判明しました。

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