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VISTED : A Vis ualization T oolset for E nvironmental D ata

Likhitha Ravi. VISTED : A Vis ualization T oolset for E nvironmental D ata. Advisor: Dr. Sergiu Dascalu Committee : Dr . Valerie Fridland Dr. Fred Harris Dr. Yaakov Varol Dr. Yantao Shen. VISTED . Introduction Background Requirements Architecture Research Plan Conclusions.

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VISTED : A Vis ualization T oolset for E nvironmental D ata

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  1. Likhitha Ravi VISTED: A Visualization Toolset for Environmental Data Advisor: Dr. SergiuDascalu Committee: Dr. Valerie Fridland Dr. Fred Harris Dr. Yaakov Varol Dr. YantaoShen

  2. VISTED • Introduction • Background • Requirements • Architecture • Research Plan • Conclusions

  3. VISTED • Introduction • Background • Requirements • Architecture • Research Plan • Conclusions

  4. Nevada Climate Change Project • Cyberinfrastructure (CI) developments are part of an NSF EPSCoR project (2008-2013, cca $21.7 million) • Focused on climate change (CC) research, education, and policy making in Nevada • Six project components: • climate modeling (air) • water resources (water) • ecological change (land) • education • cyber infrastructure • policy, decision making and outreach

  5. Nevada Climate Change Project • The project’s major goals: • Create research capabilities to add value to the existing R&D resources • Establish unique positions in focused research fields • Increase inter-institutional and interdisciplinary collaborations

  6. Nevada Climate Change Project • Research focus: • The effects of regional climate change on ecosystem resources • Major interdisciplinary science questions: • How climate changes affect water resources and linked ecosystem services and human systems? • How will climate changes affect disturbance regimes (e.g., wildland fires, insect outbreaks, droughts) and linked systems?

  7. Nevada Climate Change Project • Cyber Infrastructure (CI) goals: • Facilitate interdisciplinary climate change research, education, policy, decision-making, and outreach by using CI to develop and make available integrated data repositories and intelligent, user-friendly software solutions

  8. Nevada Climate Change Project • Envisioned in the NSF EPSCoR project proposal 2008

  9. Nevada Climate Change Project • CI outputs: • Nevada Climate Change Portal (NCCP) • Software tools for climate change research, outreach and education: software frameworks • Integration and interaction across project and among CI groups within the 3-State Western Consortium: facilitator of collaboration

  10. NCCP • NCCP provides the climate data online to help researchers working on climate change all over the globe. • Why do we need data visualization? • Although most of the climate related data is easily available on the World Wide Web, it is a complex and demanding task to analyze very large datasets without the help of visualization.

  11. Data Visualization • Uses of visualization • Presenting the results in a comprehensible manner for decision makers, stakeholders and general public. • Evolution of climate models. • Verification of hypotheses. • Data exploration in order to find the trends and patterns.

  12. VISTED • VISTED mainly helps the climate researchers by visualizing the datasets over the web. • The users of the VISTED are researchers, educators, students, policy makers and general public.

  13. VISTED • Research Questions • What specific visualization techniques and displays can increase the efficiency of the environmental scientists? • What mechanism for integrating data extraction, conversion and visualization are most beneficial for the environmental scientists work? • What are the challenges facing researchers in the field of data visualization?

  14. VISTED • Significant features of VISTED • Data Visualization • Data Download • Data Extraction • Data Conversion • Capabilities of VISTED • Handling several input data formats such as Network Common Data Form (NetCDF), Comma-Separated Values (CSV), American Standard Code for Information Exchange (ASCII) and Hierarchal Data Format (HDF5). • Providing different kinds of visualizations such as line chart, bar chart, bubble chart, and many more.

  15. VISTED • New capabilities • A web based tool for climate researchers, students, educators and general public. • Uploading datasets from users machine. • Reading input from several data formats such as NetCDF, CSV, ASCII and HDF5. • Extracting NetCDF, CSV, ASCII and HDF5 datasets. • Converting into different data format. • Introducing new visualization techniques to the climate researchers.

  16. VISTED • Introduction • Background • Requirements • Architecture • Research Plan • Conclusions

  17. Table 1: Matrix representing the features of visualization tools

  18. Sample Visualizations AVS/Express Wind Modeling Terrain and Weather Source: http://www.avs.com/products/avs-express/gallery.html

  19. Sample Visualizations ArcGIS Climate change Impacts of Sea Level Rise Source: http://www.esri.com/library/ebooks/climate-change.pdf

  20. Table 1: Matrix representing the features of visualization tools

  21. Sample Visualizations Grads Temperature Forecast IDV view of Hurricane Charlie Source: http://www.unidata.ucar.edu/software/idv/docs/userguide/index.html Source: http://wxmaps.org/pix/temp5.html

  22. Table 1: Matrix representing the features of visualization tools

  23. Sample Visualizations R-Statistical Package Tableau Gallery Source: http://www.r-project.org/ Source: http://www.tableausoftware.com/learn/gallery

  24. Table 1: Matrix representing the features of visualization tools

  25. Sample Visualizations VisIt Gallery Vis Trails Gallery Source: http://www.vistrails.org/index.php/File:Screen_Shot_2012-01-12_at_2.50.19_PM.png Source: https://wci.llnl.gov/codes/visit/gallery.html

  26. Related Work • NASA(National Aeronautics and Space Administration) • * Provides data extraction. • * Data can be downloaded in several formats. • - No data interaction. • NOAA (National Oceanic and Atmospheric Administration) • * Supports data interaction. • * Provides data extraction. • - Data can be downloaded only in ASCII format. • Cal-adapt • * Supports data interaction. • - Cannot change visualization technique • - Does not support data conversion. • Many eyes • * Supports several visualization techniques. • * Allows users to upload data • -Supports only CSV and ASCII file formats.

  27. Sample Visualizations NASA Source: http://mynasadata.larc.nasa.gov/

  28. Sample Visualizations NOAA Source: http://www.climate.gov/#climateWatch

  29. Sample Visualizations CAL- Adapt Source: http://cal-adapt.org/temperature/decadal/

  30. Sample Visualizations Many Eyes Source: http://www-958.ibm.com/software/analytics/manyeyes/page/create_visualization.html

  31. Strengths • Less learning time • No programming knowledge required • ArcGIS, Tableau, Graphpad, Many eyes • Programming/Scripting knowledge required • AVS/Express, VisTrails, VisIt, VTK, Ferret, UV-CDAT, GrADS, IDV, R, SPSS, Jquery visualize, D3 • Open Source • Ferret, GrADS, IDV, R, UV-CDAT, VisTrails, VisIt • Supporting several input formats • ArcGIS, GrADS, VisIt, Ferret, NCL • Supporting several visualization techniques • VisTrails, UV-CDAT, VTK, IDV, Many eyes • Supporting large and complex datasets • AVS/Express, IDV, VisIt, VTK, Ferret

  32. Limitations • Degrading performance while working with large datasets • VisTrails, VisIt, XmdvTool, IDV • Poor data modeling capabilities • VTK, Tableau, • Not supporting data interaction • ArcGIS, VTK • Supporting limited operating systems/ browsers/ hardware • UV-CDAT, OpenDX, Many eyes, Ferret

  33. Discussion • None of the tools fulfill the needs of climate researchers completely. • Switching among the tools could be easier if there is a standard input data format. • Support of interactive 3D/4D visualizations. • Support of several devices such as touch pads, display walls, mobile devices, and desktops. • Handling erroneous data and missing data values.

  34. A Simple Taxonomy of Visualization Techniques • One-Dimensional • histograms, normal distributions • Two-Dimensional • line graphs, bar charts, area charts, pie charts, maps, scatterplots, and stream line and arrow visualizations. • Three-Dimensional • Isosurfacetechniques , direct volume rendering, slicing techniques , 3D bar charts and realistic renderings. • Multi-Dimensional • scatterplot matrices, parallel coordinates, star coordinates, maps, and autoglyphs

  35. Visualization techniques Source: http://www-958.ibm.com/software/analytics/manyeyes/page/Visualization_Options.html

  36. VISTED • Introduction • Background • Requirements • Architecture • Research Plan • Conclusions

  37. Functional Requirements • VISTED shall allow user to select a climate variable. • VISTED shall allow user to select a combination of climate variables. • VISTED shall allow user to select a time period. • VISTED shall allow user to select a particular location. • VISTED shall accept input data in netCDF format. • VISTED shall allow user to download data in netCDFformat. • VISTED shall accept input data in CSV format. • VISTED shall allow user to download data in CSV format. • VISTED shall accept input data in binary format. • VISTED shall allow visualization of datasets that are loaded from users system.

  38. Functional Requirements • VISTED shall allow user to download data in binary format. • VISTED shall allow user to view the selected data. • VISTED shall provide the links for the navigation across the website. • VISTED shall provide some sample visualizations to the users. • VISTED shall allow user to choose a visualization technique. • VISTED shall allow user to view data as time series graphs. • VISTED shall allow user to pick a location from the map. • VISTED shall provide users with frequently asked questions and answers.

  39. Non-functional Requirements • VISTED shall be platform independent. • VISTED shall support many browsers • VISTED shall be developed using competitive technologies like HTML5, jQuery, and CSS3. • VISTED shall be extensible and reusable. • VISTED shall be fault tolerant. • VISTED shall have high performance. • VISTED shall have high reliability. • VISTED shall support devices like tablets and mobile phones.

  40. Use case diagram of VISTED

  41. Technologies • Technologies • HTML5 • D3 JavaScript Library • C# • IDE • Visual studio 2012

  42. Technology D3is the winner! * Provides several visualization techniques. * Provides data interactivity. Source: https://github.com/mbostock/d3/wiki/Gallery

  43. VISTED • Introduction • Background • Requirements • Architecture • Research Plan • Conclusions

  44. System level diagram of VISTED

  45. Modeling Output

  46. NetCDF Files

  47. NetCDF File

  48. Array Data

  49. Activity diagram

  50. Flowchart of VISTED

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