Kirsten’s notes from May 1, 2015 session with Margaret Burnett

Attending Susan Stafford, Jenny Orr, Judy Cushing, Margaret Burnett, Mike Bailey, Patrick Wingo, Nik Molnar-Stevenson, Chris Schultz,


Objective–>For Margaret to look at vis software and prioritize changes to user interface

Comment 1: Margaret’s current research question: Gender Mag (how problem solving software–> when it’s not genera inclusive;)

Judy’s commentary on context: for experts.

–> usefulness of visualizations are important,

–> collaborators want to inherit the software

–> software will live in the public domain, we want to make this software more usable by folks, in general

–> our collaborators are thinking about making the visualizations, themselves, accessible by their non-scientist stakeholders, as well as their own scientist collaborators

–> scientists want to run the models and have the visualizations show in real time what’s happening in the models

Margaret’s questions: the collaborators are scientists (they are not here though), are they here?

Characterized example user (Dominique)

—–> Dominique will inherit this; integration of domain sciences; terrestrial ecosystems, etc.

—–> Questions about Dominique–> what did she do when she didn’t know? She asked (i.e., is she a tinkerer or tinker?)

—–> Active User (learning about content, not about the actual tool)

—> asks about risk aversion and Dominique

—> asks about problem solving (information gathering style, what is it? –> depth first information processor; comprehensive information style first (gather information about a lot hypothesis)

IMPORTANCE of thinking about users in particular…

Introduction to demo for the ViSTAS development

–> JUDY: 3 separate applications (VISTAS, taking files in and visualizing them, versus the vis engine and put it into another program)

2D information on a 3D surface (the topography can be readily seen); for stakeholders–> recognizing the place

 Jenny’s demo: VALCEX

–> wind data; wind speed and direction at various places above the point

–> the advantage of the web is that it’s all accessible to folks

–> points out problems in interface; rotate, zoom in, etc.

–> shows the actual two stations being visualized, loads data; (Speeding up the loading is an issue).

Margaret asks: “If you have a collaborator who hasn’t used the tool, what button will they push? Will they know what to push?

Jenny replies: “No, there needs to be some direction and explanation from an expert user; feedback is important

Margaret asks: “How are you recording these issues?”

NIK: source code depository and issue tracker (GIRA);


Margaret: questions: why is start from the beginning the third thing in the list?

questions: what types of questions are the users trying to answer? (e.g., change over time, direction, pattern detection)

Recommendations on VALCEX


–> arrows need to be seen (group discusses arrows issues)

–> fixing the blue axes to a different color or outline them

–> for active learners, it hooks them to get to the task at hand

–> Jenny requests a time line (change the log so that it’s more visible)

–> recommend a way to create an anchor of what’s been seen before, instead of need to “memorize” what was seen before.

–> keep using the “active learner” as an example user, that will help to test potential changes

Nik’s Demo: Stand-alone VISTAS application

–> general enough, that it has some flexibility; but it’s a bit more complex because one has to configure vis that one wants to see

–> (documentation or training is necessary)

–> concept of a project is a way to structure

(Nik walks through and volleys questions)

Recommendations on stand-alone VISTAS application

–> visualization could exist without project (start without having a project)

–> bypass thinking about organizing files, and the program can automate the organization

–> change to ‘ADD DATA’ (instead of add data to project)

–> Jenny suggests–opening screen with 3 or 4 steps walking the user through the process; splash screen with “open recent projects”

–> questions whether user needs to know the difference between the types of data necessary for building the visualization; recommends doing a 1a, 1b approach on splash page so that the user doesn’t have to wonder what to load next (check them off till all the data is in there).

–> Margaret draws on the board linear steps and buttons; with potential for moving throughout the steps iteratively; (using back, ‘more data’, and next)

–> questions (once vis is on the screen) — think out loud : does the vis that pops up answer the question I’m asking?

–> inaccuracy versus exaggerated (to be able to see, needs to be exaggerated; Margaret doesn’t like this)

–> needs a way to show overview or composite of all data so that memorizing is not necessary (e.g., volume extrusion or line graph)

–> Margaret (asks “what just changed?”) states: “a lot times, people ask ‘what just changed?'” People need some sort of feedback (transitions, needing to see what happened before–eye to see what’s changing)

Susan summarizes: some of the things that need to be fixed are consistent among all the programs;

Margaret: “if we can think about the problem these folks want to solve, that’s what tells us ‘when we’re there.'”

Patrick’s Demo: ENVISION

description of ENVISION USE–> stakeholder engagement; communication tool

–> difficulty with white on light blue

Recommendations about ENVISION

–> WHO WE CARE ABOUT: the scientist and the stakeholders

–> what’s the use? discovery or engagement?

–> rename “path preset” to something like fly through (Margaret questions naming)

–> How does the user know what he/she is looking at? (disorientation of user; the legend needs to be built into the visualization; ON THE LIST)

–> Questions use of the word “tree”

–> Susan: using this to communicate with another audience; questions –> scientific audience (how does this work?)


JUDY: problem: how to integrate into an existing package the features that VISTAS has (overlaying the 2D data onto a 3D visualization); manipulate by a scientist, etc.

“The UI task is to add the visualizing with the technical interface of ENVISION”


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Presentation at International Symposium of Society and Natural Resources

Presentation by K. Winters

PDF of presentation

Abstract The VISTAS (VISualization of Terrestrial and Aquatic Systems) project addresses cross-discipline research integration on many levels. At one level, one that is product-oriented, it provides a foundation for future integration of diverse data and models across disciplines through the research and development of software tools for visualizing complex data that span multiple spatial and temporal scales. At another level, it incorporates process-oriented integration using social science methods to track and analyze the practices of researchers from diverse disciplines (ecology, computer science, and social science). At yet another level, it supports communication-oriented integration, examining what data visualizations might be best-suited for communication ‘horizontally’—across scientific disciplines, as well as ‘vertically’—across use-types, such as in a policy or management context versus a purely scientific context.

The VISTAS survey presentation will provide a brief overview of the VISTAS project, and then focus on findings from our recent survey of over 24,000 visualizations found in peer-reviewed literature and juried presentations. The aim of the survey was to advance insight on problem solving within the context of transdisciplinary research. The practice of peer review is relatively consistent across disciplines, and when peer-reviewed media are surveyed, it can provide a snapshot of the current practices of research scientists, including their use of data visualization. Our survey was a way to gauge the “current state of data visualization” and to build a definition of what constitutes “good” data visualization (defined as both sophisticated and effective) in the field of ecology. The survey methods were quantitative and qualitative, inductive (for definition building) and deductive (for definition confirmation) in nature. The survey findings direct not only our team’s understanding of how some sub-disciplines within the field of ecology vary, but also inform the development of VISTAS software for visualizing multiple researchers’ data. This presentation will share a bird’s-eye view of how our research team’s work might inform transdisciplinary integration and will showcase findings from the extensive survey and analysis of peer-reviewed literature and conference proceedings.


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New Bibliographies

In early spring, 2014, two new bibliography areas have been added to the VISTAS Bibliography:  Social Science Inquiry and Arts and Animation.  These pages are maintained by Kirsten Winters and Dani Witherspoon, respectively.

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Valley Circulation Experiment at HJ Andrews Forest

On October 14-15, 2011, VISTAS Research Assistants  and Evergreen MES students Jerilyn Walley and Evan Hayduk participated in launching Christoph Thomas’ VALley Circulation EXperiment (VALCEX) at HJ Andrews Forest.  Jerilyn will conduct her master’s thesis research using VALCEX.  For further information, see Christoph’s announcement of the VALCEX launch!

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VISTAS Presentation at H.J. Andrews Symposium

The VISTAS team presented a poster on the initial progress of our project at the annual symposium for the H.J. Andrews Experimental Forest, held on the campus of Oregon State University in Corvallis, Oregon. We were genuinely excited to hear all the feedback and comments from our fellow presenters and attendees, and are looking forward to some future collaborations.

Cushing, J., Bailey, M., Bolte, J., Bond, B., Lach, D., Smith, A., Stafford, S., Stavely, S., Stevenson-Molnar, N., Stieglitz, M., Thomas, C. From Data to Knowledge in Grand Challenge Environmental Science Research: the VISualization of Terrestrial-Aquatic Systems (VISTAS). Poster presentation, H.J. Andrews Experimental Forest 12th LTER Symposium (2011)

View a pdf of the VISTAS poster here.


In this Petabyte Age, digital information increases at a prodigious rate – due to new remote sensing, national environmental observatories, research networks such as Long Term Ecosystem Research sites, etc. Increasingly, scientists use massive data sets to predict natural phenomena. The sheer amount of data presents challenges, but this data deluge is but one complicating factor. Grand challenge environmental science problems such as climate change, lack of species diversity, and reduced ecosystem functioning, have complex, highly distributed, and heterogeneous data spanning time and spatial scales.  Because cross-scale analytical methods are not well understood, visualizing natural phenomena might help scientists develop intuition and hypotheses – helping formulate and communicate insights about patterns and processes in complex systems.

The VISTAS Project develops software and visualizations to enable better understanding and communication about Grand Challenge Environmental Science. It will:

  1. Conduct Ecology Informatics research to enable visual analytics and implement proof of concept software, devising visualizations and animations where the same natural phenomena are seen at different spatial and temporal scales.
  2. Co-develop VISTAS with environmental scientists at the HJ Andrews LTER who will use VISTAS in studies spanning spatial and temporal scales from plot (m2) to basin (64km2).
  3. Apply social science methods to study the co-development and usability of VISTAS – devising social science methods for developing scientific software and for determining which visualizations work, for whom, and why.

We also convene The Northwest Computer Science Consortium to Enhance the Study of Climate Change to advise grantees and enlist the CS community in R&D to enable Environmental Science Grand Challenges.

If successful, the project’s greatest impact will be in environmental science research, but our long term vision includes using visual analytics to improve evidence-based practice of natural resource management.

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