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Open AccessFeature PaperArticle

Using Visual Exploratory Data Analysis to Facilitate Collaboration and Hypothesis Generation in Cross-Disciplinary Research

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Department of Computer Science, University of Idaho, 875 Perimeter Drive, MS 1010, Moscow, ID 83844-1010, USA
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Department of Geology, Southern Illinois University Carbondale, 1263 Lincoln Drive, Carbondale, IL 62901, USA
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Department of Geosciences, University of Arizona, 1040 E. 4th Street, Tucson, AZ 85721, USA
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Tetherless World Constellation, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA
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Geophysical Laboratory, Carnegie Institution for Science, 5251 Broad Branch Road, NW, Washington, DC 20015, USA
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State Key Laboratory of Geological Processes and Mineral Resources & Faculty of Earth Resources, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
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Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2017, 6(11), 368; https://doi.org/10.3390/ijgi6110368
Received: 6 October 2017 / Revised: 11 November 2017 / Accepted: 15 November 2017 / Published: 16 November 2017
Massive open data resources are changing the way that people do science. To make use of those data resources, data science methods and technology can be leveraged by stakeholders of various disciplines. The objective of this paper is to present our experience of using visual exploratory data analysis as a method to facilitate collaboration and hypothesis generation in geoscience research. The research team consisted of both geoscientists and computer scientists. A use case-driven, iterative approach was applied to create a collaborative and communicative environment. Through several rounds of use case analysis and technological development, a data visualization pilot system was created for studying the co-relationships between chemical elements and mineral species. The exploratory data analyses conducted in those use case studies led to several research hypotheses for future work. This research illustrates the usefulness of exploratory data analysis for hypothesis generation in a data science process. Although the presented project is in geoscience, the discussed method and experience can also be translated into other disciplines. View Full-Text
Keywords: exploratory data analysis; data visualization; data science; geoinformatics; mineral ecology exploratory data analysis; data visualization; data science; geoinformatics; mineral ecology
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Ma, X.; Hummer, D.; Golden, J.J.; Fox, P.A.; Hazen, R.M.; Morrison, S.M.; Downs, R.T.; Madhikarmi, B.L.; Wang, C.; Meyer, M.B. Using Visual Exploratory Data Analysis to Facilitate Collaboration and Hypothesis Generation in Cross-Disciplinary Research. ISPRS Int. J. Geo-Inf. 2017, 6, 368.

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