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WG5: 3D Scientific Visualization (Terrain Mapping)

Template for Scribes

SMALL GROUP DISCUSSION FORMAT: 30 min - 4:50 – 5:20.

Members of each group will self-introduce and share their responses to the questionnaire. Each group is led by a person who did a mini-presentation and appoints a scribe and reporter (please give or email scribe/reporter notes to the organizers after the report back).

  • Notes of Note: (don’t fit into the categories below, but Ned wanted to have on record)

  • FOSS4g conference upcoming to look into for open platforms

  • The idea of a multi-layer archive:

    • code
    • executable code
    • [older] operating systems to support archived code
    • [older] hardware that supports those OS

Role of information managers as living memory of data tools

  • Scribe Instructions:
    • The scribe in each group will compile 3 lists (use list_template):
    • List of the software used by the small group participants
    • JavaScript
    • R
    • Python
    • some more advanced members are also using resources in list below (#2):

List of tools and resources that participants know about (websites, etc.)

  • R
  • JavaScript
  • In Python, Map plot lib linked to JavaScript d- link is called MPLD3, by mike bostock
  • Bl.ocks
  • Tool tips that can drag around
  • Cross Filter (unconfirmed) - can use to translate large and older files into code - data processing step
  • Bostock-github see all his stuff
  • iPython notebook
  • JMP - as data analysis product
  • Google earth, Google earth engine - host Lidar
  • Html5/css3/javascript
  • Esri -ArcGIS
  • Osgo
  • Qgis- PostGIS (better for the open source web and cloud support)
  • Geo-Django- Python based and o-auth supported web framework
  • Role of information managers as living memory of data tools
  • Importing Lidar into arc
  • Need to have archives for code not just data- GITHUB!
  • Docker virtualizes code, OS - shipping platform - docker hub for sharing
  • Babel for translating ancient systems

List of data sources used (NASA, DEMs, etc.)

  • specific data sources beyond LTER not discussed
  • Questions for discussion (used to organize the group report):
    • What are the best aspects of the visualizations shown by presenters and by Ned in his keynote talk this morning?
    • Changes over time - Looking at land use change over time, and timing of peak runoff for instance
    • Communication between scientists and non-scientists
    • Would be huge in pin-pointing thresholds
    • aiding in the cognitive process of visualization in idling relationships
    • helping scientists do exploratory analysis of data, since humans can see trends visually much more easily than through number runs
    • working through graphics and visualizations departments at universities as a launching point

What are the limitations?

  • coding literacy
  • lack of existing template so that researchers at least know
  • what sorts of data and script to be providing/seeking out
  • how to compile data sets from days past that are either not digitized, or are in different formats that may not lend themselves easily to visualization software tools
  • price, depending on preferred program
  • disconnect between animation role in industry vs, where science is - hard to get grad students up to speed, and data managers overwhelmed

How could those visualizations be improved, i.e., with new features?

  • democratizing visualization tools and resources, although that has arguably already been done through R and Python
  • archiving code, executable code
  • creating a template of sorts that code illiterate users can plug data into to generate basic visualizations - a visualization “widget” of sorts
  • have a workshop/tutorial for scientists on nuts and bolts of getting started - perhaps at LTER ASM meetings - or try to get NSF to fund separate workshop

Software (other than that used by presenters) that might do the same thing: (unsure which of the resources mentioned in the lists at the top have this functionality)

What kind of data do you use and is it appropriate for visualization?

  • Data mentioned by breakout group:
  • Getting data visualized for large datasets (from data managers)
  • Science communication
  • Difference in variation in wood chemistry
  • Phytoplankton - may not work for his project, but very interested in science communication
  • Combining technology and code with biosciences
  • Using visualization for theory animations
  • Information management
  • how veg communities are changing in comparison to climate data
  • Lidar scans of streams, wants something better than arc scene

How did you get started with 3D visualization?

Mentioned by attendees: playing around with available softwares - R, Python, JavaScript, as well as earlier softwares that have since evolved Lter communications office, Sgi machines, main platforms used for modeli and animation in early days

Can you think of OTHER applications for visualization?

How might you use 3D visualization in your work?

  • Getting data visualized for large datasets (from data managers)

  • Science communication - education and outreach tool

  • Difference in variation in wood chemistry

  • Combining technology and code with biosciences

  • Using visualization for theory animations

  • Information management how veg communities are changing in comparison to climate data

  • Lidar scans of streams, wants something better than arc scene

  • Report back and discussion – 30 min. Each group presents highlights of their discussion.

Please send lists to Stafford@umn.edu, or give hardcopy to her at the end of the session!