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Resource ID: #818
Subject: 494
Source: 2198Christopher Groskopf, Ryann Grochowski Jones, Aaron Williams, Stuart Thompson
Affiliation: Quartz, ProPublica, The Washington Post, The Wall Street Journal
Date: 2016



While a data journalist's toolkit is becoming more and more complex, the responsibility to disclose and explain our methods remains a bit murky. How do we explain to a lay audience our usage of models or machine learning techniques? What if there is an error in a library we used to perform our analysis? What do readers need to understand about our techniques to properly interpret the results of our analysis? Should we publish source/raw data? These are a few of the questions we will raise and attempt to answer — with your help. Audience participation will be an important part of this session. Let's figure out some transparency best practices for data journalists.

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