Advisor: Dr. Sergiu Dascalu Committee: Dr. Valerie Fridland Dr. Fred Harris Dr. Yaakov Varol Dr....
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VISTED: A Visualization Toolset for Environmental Data Advisor: Dr. Sergiu Dascalu Committee: Dr. Valerie Fridland Dr. Fred Harris Dr. Yaakov Varol Dr. Yantao Shen Likhitha Ravi
Advisor: Dr. Sergiu Dascalu Committee: Dr. Valerie Fridland Dr. Fred Harris Dr. Yaakov Varol Dr. Yantao Shen Likhitha Ravi
Advisor: Dr. Sergiu Dascalu Committee: Dr. Valerie Fridland Dr.
Fred Harris Dr. Yaakov Varol Dr. Yantao Shen Likhitha Ravi
Slide 2
1. Introduction 2. Background 3. Requirements 4. Architecture
5. Research Plan 6. Conclusions
Slide 3
1. Introduction 2. Background 3. Requirements 4. Architecture
5. Research Plan 6. Conclusions
Slide 4
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
Slide 5
The projects 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
Slide 6
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?
Slide 7
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
Slide 8
Envisioned in the NSF EPSCoR project proposal 2008
Slide 9
CI outputs: Nevada Climate Change Portal (NCCP)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
Slide 10
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.
Slide 11
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.
Slide 12
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.
Slide 13
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?
Slide 14
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.
Slide 15
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.
Slide 16
1. Introduction 2. Background 3. Requirements 4. Architecture
5. Research Plan 6. Conclusions
Slide 17
Table 1: Matrix representing the features of visualization
tools #Tool Name Operating system support Visualization Techniques
Programming/ Scripting languages # of variables 1ArcGIS Microsoft
Windows, Linux,Sun Solaris Map (MXD), Globe, Geoprocessing,
Geocoding, Network Analysis,Geodata, Mobile VBA, VB,.NET, Java,
C++, COM, Python, VBScript, JavaScript, ASP, JSP, ColdFusion,
Java,.NET, JavaScript, XML, FLASH, PHP Multidimensio nal data 2
AVS/Expres s Windows, Mac OS X, Linux, Solaris, and HP-UX, IRIX and
Alph Tru64 2D line field plots, Gamma plot, 3D shaded,contour, and
arrow field plots, Animations, particle tracing using stream lines
and streak lines, isosurfaces, Volume Visualization C, C++, and
FORTRAN. 2D, 3D, univariate,mult ivariate data 3Ferret Unix
systems, and on Windows XP/NT/9x Geophysical formatting,
symmetrical processing. Ferret Scripts 3D, 4D, Multidimensio nal
data 4GGobi Windows, Mac, Unix Histogram, textured dot plot,
barchart, spineplot, Scatterplot, parallel coordinates, time series
plot Ggobi scripting 3D, Multivariate data 5Google Visualizatio n
API Windows, Mac, Unix pie chart, Scatterplot, Guage, geo chart,
bar chart, tree map, bubble chart, line graph, stack graph,, combo
chart, column chart, area chart, candlestick chart, word cloud
generator, and maps. Javascript2D
Slide 18
AVS/Express Terrain and Weather Wind Modeling Source:
http://www.avs.com/products/avs-express/gallery.html
Slide 19
ArcGIS Impacts of Sea Level Rise Climate change Source:
http://www.esri.com/library/ebooks/climate-change.pdf
Slide 20
Table 1: Matrix representing the features of visualization
tools # Tool Name Operating system support Visualization Techniques
Programming/ Scripting languages # of variables 6GrADS Linux, Mac
OS X, Windows, Solaris, IBM AIX, DEC Alpha, IRIX line and bar
graphs, scatter plots, smoothed contours, shaded contours,
streamlines, wind vectors, grid boxes, shaded grid boxes, and
station model plots FORTRAN, GrADS scripts 5-dimensional 7
Integrated Data Viewer (IDV) Windows, Linux, Solaris (SPARC and
x86), Mac OS-X Charts, maps, radar displays, gridded data displays,
isosurfaces, volume rendering, globe display, plan view, profiler
winds Java 3D, multi- dimensional data 8 Mathemati ca Windows, Mac,
Unix polar and spherical plots, contour and density plots,
parametric line and surface plots, and vector, stream plots,
candlestick charts, quantile plots, box whisker charts, Bode plots,
histograms, 2D and 3D bar charts, pie charts, bubble charts,
B-spline curves in 2D or 3D C++, Java,.Net, FORTRAN, CUDA, OpenCL
2D, 3D 9Matlab Linux, Microsoft Windows Line, area, bar, pie
charts, Histograms, Scatter/bubble plots, Animations, Direction and
velocity plots, isosurfaces, Volume Visualization C, C++, and
Fortran. 1D,2D, 3D visualizations 10 OpenDXWindows, Mac OS X,
Linux, Solaris, and Unix Animations, Direction and velocity plots,
isosurfaces, Volume Visualization C, FORTRAN and Visual Basic 2D,
3D, univariate,multiva riate data
Slide 21
Grads Temperature ForecastIDV view of Hurricane Charlie Source:
http://wxmaps.org/pix/temp5.html Source:
http://www.unidata.ucar.edu/software/idv/docs/userguide/index.html
Slide 22
Table 1: Matrix representing the features of visualization
tools # Tool Name Operating system support Visualization Techniques
Programming/ Scripting languages # of variables 11Prefuse Windows,
Mac, Unix Area chart, Bar chart, Pie chart, scatter chart, line
graph, Tree map, network diagram and animations Java2D 12R Windows,
Mac OS X, Linux and Unix Graphs, traditional statistical tests,
time series analysis, linear & nonlinear modeling,
classification, clustering C, Python, Perl 3D 13S-PLUS Windows,
Linux, UNIX, Solaris Graphs, linear & nonlinear modeling,
classification, clustering FORTRAN,C, S3D 14SPSS Windows, Mac, and
Linux Tables, graphs, linear regression, cluster analysis, and
non-parametric tests Java, Python, SaxBasic 2D
15TableauWindowsScatterplot, matrix chart, bar chart, area chart,
bubble chart, stack graph, pie chart, link map and spatial maps No
programming or scripting required 2D, univariate, multivariate
data
Table 1: Matrix representing the features of visualization
tools #Tool Name Operating system support Visualization Techniques
Programming / Scripting languages # of variables 16UV-CDATMac,
Linux multi-view visualization, Direction and velocity plots,
isosurfaces, Volume Visualization, and parameter space exploration
Python, C/C++,Java, FORTRAN 3D, multi- dimensional data 17VisTrails
Windows, Mac, Linux multi-view visualization, Direction and
velocity plots, isosurfaces, Volume Visualization, and parameter
space exploration Python 3D, multi- dimensional data 18VisIt
Windows, Mac, Linux, Unix, AIZ, Solaris, Tru64, IRIZ Contour 3D,
Pseudo color plot, Contour 3D, volume plot, vector plot, subset
plot, molecule plot, parallel axis plot Python 3D, multi-
dimensional data 19Visualizati on toolkit (VTK) Windows, Mac, Unix
scalar, vector, tensor, texture, volumetric methods, implicit
modeling, polygon reduction, mesh smoothing, cutting, contouring,
and Delaunay triangulation C++3D
Slide 25
Vis Trails Gallery VisIt 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
Slide 26
NASA (National Aeronautics and Space Administration) NASA *
Provides data extraction. * Data can be downloaded in several
formats. - No data interaction. NOAA ( National Oceanic and
Atmospheric Administration) NOAA * Supports data interaction. *
Provides data extraction. - Data can be downloaded only in ASCII
format. Cal-adapt Cal-adapt * Supports data interaction. - Cannot
change visualization technique - Does not support data conversion.
Many eyes Many eyes * Supports several visualization techniques. *
Allows users to upload data -Supports only CSV and ASCII file
formats.
Source:
http://www-958.ibm.com/software/analytics/manyeyes/page/create_visualization.html
Many Eyes
Slide 31
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
Slide 32
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
Slide 33
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.
Slide 34
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 Isosurface techniques, direct volume rendering,
slicing techniques, 3D bar charts and realistic renderings.
Multi-Dimensional scatterplot matrices, parallel coordinates, star
coordinates, maps, and autoglyphs
1. Introduction 2. Background 3. Requirements 4. Architecture
5. Research Plan 6. Conclusions
Slide 37
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
netCDF format. 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.
Slide 38
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.
Slide 39
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.
Slide 40
Slide 41
Technologies HTML5 D3 JavaScript Library C# IDE Visual studio
2012
Slide 42
D3D3 is the winner! * Provides several visualization
techniques. * Provides data interactivity. Source:
https://github.com/mbostock/d3/wiki/Gallery
Slide 43
1. Introduction 2. Background 3. Requirements 4. Architecture
5. Research Plan 6. Conclusions
Slide 44
Slide 45
Modeling Output Modeling Output
Slide 46
Slide 47
NetCDF File
Slide 48
Slide 49
Activity diagram
Slide 50
Slide 51
Slide 52
Slide 53
1. Introduction 2. Background 3. Requirements 4. Architecture
5. Research Plan 6. Conclusions
Slide 54
Exploration of the current state-of-the art methods and
technologies/tools used for the presentation and visualization of
environmental data. Research and design of a new web-based software
toolset for processing and visualizing transect data (these
activities will lead to advanced data processing capabilities for
the NCCP). Development, experimentation, and integration of the new
processing and visualization software into the Nevada Climate
Change Portal.
Slide 55
Task 1: Survey existing methods and supporting tools used for
the presentation and visualization of environmental data. Identify
strengths and limitations. Outputs: survey report. Task 2:
Elaborate conceptual design and operational approach (method) for a
new web-based software toolset dedicated to presenting and
visualizing NCCP environmental data. Outputs: conceptual design
document; documented method. Task 3: Create software specification
and architectural design of the new software toolset. Outputs:
Software requirements specification document; design document
(high-level sign, detail-level design, data design, user interface
design, interface design). Task 4: Implement web-based software
solution. Outputs: Implemented software; documented code.
Slide 56
Task 5: Integrate web-based software toolset into the Nevada
Climate Change Portal and prepare user manual. Outputs: Integrated
software, executable through the NCCP; tutorial and user manual.
Task 6: Perform usability tests on the data portal and process
results. Output: usability test report. Task 7: Based on user
feedback, revise and improve web-based software toolset for data
presentation and visualization. Output: improved web-based,
NCCP-integrated software toolset for environmental data
presentation and visualization. Task 8: Disseminate research and
development results. Outputs: Journal or conference paper; one or
two poster presentations.
Slide 57
As per GRA tasks Performed survey on existing data
visualization tools and techniques for environmental data. (Task 1)
Gathered the requirements and created the concept and specification
document. (Task 2) Created the detail design of the software
toolset. (Task 3) Designed the initial prototype of the toolset.
(Task 4)
Slide 58
In addition to GRA tasks Wrote chapters 2 and 5 of the
dissertation. Presented a paper at CATA-2013 in March 2013.
Likhitha R., Qiping Y., Dascalu M. S., Harris F. C. Jr., A Survey
of Visualization Techniques and Tools for Environmental Data, CATA,
March 2013. Presented a poster in NSF EPSCOR Annual Climate Change
Conference in March 2013. Likhitha R. An overview of visualization
approaches for environmental data, Tri-State EPSCoR Climate Change
Workshop, March 2013. Coauthor on another paper and poster. Qiping
Y., Michael M. Jr., Dascalu S., Harris F. C. Jr., Likhitha R.,
Community Metadata ISO 19115 Adaptor, CATA, March 2013. Richard k.,
Michael M. Jr., Eric F., Sohei O., Likhitha R., Ivan G., Jigarkumar
P., Adrew D., Ershad S., Shahram., Dascalu., Harris F. C. Jr.,
Communicating Climate Change on the Web: The Nevada Climate Change
Portal, Tri- State EPSCoR Climate Change Workshop, March 2013.
Slide 59
To do Get additional input from scientists. Finalize proposed
approach and web-based solution. (Task 4) Integrate with NCCP.
(Task 5) Perform user tests. (Task 6) Revise VISTED and compare
with related toolsets. (Task 7) Disseminate research. (Task 8)
Finalize and defend dissertation. (Task 9)
Slide 60
1. Introduction 2. Background 3. Requirements 4. Architecture
5. Research Plan 6. Conclusions
Slide 61
The main goal of the VISTED is to help the climate researchers
in visualizing datasets using new capabilities. It provides a new
approach and supporting tools. It gives users the flexibility in
choosing the data of their interest. The toolset allows users to
upload files for the visualization.
Slide 62
Main contributions New approach that integrates data
extraction, conversion, and visualization (with possible extensions
for data analysis). Associated web-based toolset for data
manipulation and visualization. Support provided for several data
formats. Flexible data extraction capabilities. Mechanisms for
efficient visualization of climate data.
Slide 63
I would like to thank all my committee members. Dr. Sergiu
Dascalu Dr. Valerie Fridland Dr. Fred Harris Dr. Yaakov Varol Dr.
Yantao Shen I am also thankful to CSE R&D faculty Mr. Eric
Fritzinger Dr. Richard Kelley
Slide 64
Nevada Climate Change Portal, available at
http://www.sensor.nevada.edu/NCCP/. Graphical Forecasts, Nation
Oceanic and Atmospheric Administration, available at:
http://graphical.weather.gov/. UNR Valley Road Weather Station,
Western RegionalClimate Center,, available at:
http://www.wrcc.dri.edu/weather/unr.html. Snow Pack: Decadal
Averages Map, Cal-adapt ExploringCalifornias Climate Change
Research, available at: http://caladapt.org/snowpack/decadal/.
Pavlopoulos G. A., Wegener A., and Schneider R., "A survey of
visualization tools for biological network analysis",
BioDataMining, November 2008. Aigner W., Bertone A., and Miksch S.,
"Comparing Information Visualization Tools Focusing on the Temporal
Dimensions," 12th International Conference on Information
Visualization, pp. 69 - 74, July 2008 Mozzafari E. and Seffah A.,
"From Visualization to Visual Mining: Application to Environmental
Data", IEEE Confererence on Advances in Computer-Human Interaction,
pp.143-148, February 2008. Aigner W., Miksch S., Schumann H., and
Tominski C.,Visualization of Time- Oriented Data, Springer, May
2011.
Slide 65
ArcGIS - Mapping and Spatial Analysis for Understanding Our
World, ESRI, available at:. ArcGIS QGIS Faceoff, blog.donmeltz.com,
available at:. AVS/Express Data Visualization Software,
AVS/Express,. GrADS Home Page, Grid Analysis and Display System,.
Unidata | IDV, Unidata,. UV-CDAT, UV-CDAT, available at:.
VisTrailsWiki, VisTrailsWiki, available at:. VisIt Visualization
Tool, visIt, available at. VTK - The Visualization Toolkit,
Visualization Toolkit, available at