(In?)Extricable Links between Data and Visualization: Preliminary Results from the VISTAS Project

Cushing, Judith Bayard; Hayduk, Evan; Walley, Jerilyn; Zeman, Lee; Winters, Kirsten M.; Bailey, Mike; Bolte, John P.; Bond, Barbara; Lach, Denise; Thomas, Christoph; Stafford, Susan G.; Stevenson-Molnar, Nik

doi:10.1007/978-3-642-31235-9_45

Cited by 2 publications

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“…InfoVis tends to deal with interactive displays of abstract data that do not have natural mappings to 2D or 3D space, such as counts of insects, cone production, or vegetation cover collected over time (Spence 2007). SciVis concerns data that has a natural mapping to two-or three-dimensional space and the visualizations usually involve the physical properties of the data, such as rendering of multiple layers of trees in a forest from LiDAR data (Spence 2007, Cushing et al 2012. This paper describes the development and initial application of the tool to three large, longterm data sets: cone production (Jones and Franklin 2012), stream chemistry (Johnson and Fredriksen 2012), and forest structure (Harmon and Franklin 2012) collected as part of the H.J.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Interactive visual analysis promotes exploration of long‐term ecological data

et al. 2013

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Abstract. Long-term ecological data are crucial in helping ecologists understand ecosystem function and environmental change. Nevertheless, these kinds of data sets are difficult to analyze because they are usually large, multivariate, and spatiotemporal. Although existing analysis tools such as statistical methods and spreadsheet software permit rigorous tests of pre-conceived hypotheses and static charts for simple data exploration, they have limited capacity to provide an overview of the data and to enable ecologists to explore data iteratively, and interactively, before committing to statistical analysis. These issues hinder how ecologists gain knowledge and generate hypotheses from long-term data. We present Ecological Distributions and Trends Explorer (EcoDATE), a web-based, visual-analysis tool that facilitates exploratory analysis of long-term ecological data (i.e., generating hypotheses as opposed to confirming hypotheses). The tool, which is publicly available online, was created and refined through a user-centered design process in which our team of ecologists and visualization researchers collaborated closely. The results of our collaboration were (1) a set of visual representation and interaction techniques well suited to communicating distribution patterns and temporal trends in ecological data sets, and (2) an understanding of processes ecologists use to explore data and generate and test hypotheses. We present three case studies to demonstrate the utility of EcoDATE and the exploratory analysis processes using long-term data on cone production, stream chemistry, and forest structure collected as part of the H.J. Andrews Experimental Forest (HJA), Long Term Ecological Research (LTER), and US Forest Service Pacific Northwest Research Station programs. We also present results from a survey of 15 participants of a working group at the 2012 LTER All Scientists Meeting that showed that users appreciated the tool for its ease of use, holistic access to large data sets, and interactivity.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Interactive visual analysis promotes exploration of long‐term ecological data

et al. 2013

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Software for scientists facing wicked problems lessons from the VISTAS project

Cushing

Winters

Lach

2015

Proceedings of the 16th Annual International Conference on Digital Government Research

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The Visualization for Terrestrial and Aquatic Systems project (VISTAS) aims to help scientists produce effective environmental science visualizations for their own use and for use in presenting their work to a wide range of stakeholders (including other scientists, decision makers, and the public). The need for better visualization tools for environmental science is well-documented, but little prior work has been done to determine what kinds of visualizations work and with whom. The VISTAS research and development project has applied social science methods to this question, and has identified issues relevant to visualization software development, particularly where the application area involves wicked problems such as climate change. This paper presents visualization problems of scientists whose presentations of scientific results might be enhanced if they and software developers were consciously aware of the nature of so-called wicked problems and the considerations of non-scientist secondary users. While VISTAS focuses on visualization software, we believe results are generalizable to software in general. The primary lesson learned from our work is that extending the scope of the domain context will likely provide scientists with software that is more effective and relevant to nonscientist stakeholders, but that doing so can be time consuming and more costly unless the nature of the underlying science problem is recognized and characterized early in the product cycle.

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(In?)Extricable Links between Data and Visualization: Preliminary Results from the VISTAS Project

Cited by 2 publications

References 8 publications

Interactive visual analysis promotes exploration of long‐term ecological data

Interactive visual analysis promotes exploration of long‐term ecological data

Software for scientists facing wicked problems lessons from the VISTAS project

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