Abstract
Scientific data analysis and visualization (DAV) tools are a critical component of the software ecosystem. The growth in data volumes in various scientific domains is resulting in technical innovations in DAV tools. Usability of these tools is becoming extremely critical to facilitate next-generation scientific discoveries. Usability heuristics is a widely applied approach to inspect software usability. We expand Nielsen’s heuristics to include two additional criteria: analytical-reasoning and customized-experience to capture the usability dimensions of DAV tools. We evaluated three tools to test the proposed heuristics and demonstrate its fit to DAV tools of varying features. The contribution of our work is threefold: (i) identify DAV usability heuristics, (ii) develop a framework to inspect DAV tools, (iii) conduct a comprehensive evaluation of the usability of selected DAV tools. We also provide a discussion on the heuristics framework for DAV tools and future work.
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Acknowledgements
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research under Award Number(s) DE-AC02-05CH11231, program manager Lucy Nowell.
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Swaid, S., Maat, M., Krishnan, H., Ghoshal, D., Ramakrishnan, L. (2018). Usability Heuristic Evaluation of Scientific Data Analysis and Visualization Tools. In: Ahram, T., FalcĂŁo, C. (eds) Advances in Usability and User Experience. AHFE 2017. Advances in Intelligent Systems and Computing, vol 607. Springer, Cham. https://doi.org/10.1007/978-3-319-60492-3_45
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