Data visualization heuristics for the physical sciences

Chad M. Parish, Philip D. Edmondson

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Data visualization – that is, the graphical representation of numerical information – is foundational to the scientific enterprise. A broad literature base is available providing rules, guidelines, and heuristics for authors of scientific literature to assist in the production of scientific graphics that are readable and intuitive. However, most of the available recent publications are in the bio-, psycho-, or climate sciences literature. In this paper, we address this deficiency and provide data visualization heuristics tuned to the specific needs of the physical sciences, and particularly materials sciences, community. We enumerate six general rules and provide examples of bad and improved data graphics, and provide source code to illustrate the generation of the improved figures. The six rules we enumerate are: (1)Generate figures programmatically; (2)Multivariate data calls for multivariate representation; (3)Showing the data beats mean ± standard deviation; (4)Choose colormaps that match the nature of the data; (5)Use small multiples; and (6)Don't use vendor exports naïvely.

Original languageEnglish
Article number107868
JournalMaterials and Design
Volume179
DOIs
StatePublished - Oct 5 2019

Bibliographical note

Publisher Copyright:
© 2019 The Authors

Funding

This work was supported by U.S. Department of Energy , Office of Science, Fusion Energy Sciences, under contract number DE-AC05-00OR22725 . We thank Drs. Tyler Gerczak and Kurt Terrani for the data used in Fig. 4 , from [ 35 ]. We thank Dr. Stuart Wright, EDAX, for discussions regarding Ref. [ 36 ] and weighted standard deviation calculations. The atom probe tomography data was sponsored by the Light-Water Reactor Sustainability Program of the Office of Nuclear Energy. We also thank Dr. Anne S. Berres and Dr. Bruce E. Wilson, ORNL, for critiquing the manuscript. The sample in Fig. 5 was courtesy Prof. W. Fahrenholtz and Prof. G. Hilmas, Missouri University of Science and Technology. The FEI Talos F200X S/TEM instrument ( Figs. 7–8 ) provided by US DOE, Office of Nuclear Energy, Fuel Cycle Research and Development and the Nuclear Science User Facilities. Atom probe tomography research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility.

FundersFunder number
Fuel Cycle Research and Development
U.S. Department of Energy
Office of Science
Office of Nuclear Energy
Fusion Energy SciencesDE-AC05-00OR22725

    Keywords

    • Data analytics
    • Data presentation
    • Microscopy
    • Scientific publication
    • Visualization

    Fingerprint

    Dive into the research topics of 'Data visualization heuristics for the physical sciences'. Together they form a unique fingerprint.

    Cite this