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Title: Knowing what to look for: A Fact-Evidence Reasoning Framework for Decoding Communicative Visualization
Despite the widespread use of communicative charts as a medium for scientific communication, we lack a systematic understanding of how well the charts fulfill the goals of effective visual communication. Existing research mostly focuses on the means, i.e. the encoding principles, and not the end, i.e. the key takeaway of a chart. To address this gap, we start from the first principles and aim to answer the fundamental question: how can we describe the message of a scientific chart? We contribute a fact-evidence reasoning framework (FaEvR) by augmenting the conventional visualization pipeline with the stages of gathering and associating evidence for decoding the facts presented in a chart. We apply the resulting classification scheme of fact and evidence on a collection of 500 charts collected from publications in multiple science domains. We demonstrate the practical applications of FaEvR in calibrating task complexity and detecting barriers towards chart interpretability.  more » « less
Award ID(s):
1928627
PAR ID:
10297542
Author(s) / Creator(s):
;
Date Published:
Journal Name:
2020 IEEE Visualization Conference (VIS)
Page Range / eLocation ID:
231 to 235
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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