Visualizing Visualization - University Corporation For Atmospheric Research

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Visualizing VisualizationKevin R. Tyle, University at Albany, SUNYUnidata Russell L. DeSouza Award Seminar

It started with a Big Splash (Apollo 11 Splashdown, 7/24/1969)Visualizing Visualization– Kevin Tyle

Outline1)2)3)4)5)6)7)Visualization Way Back WhenVisualization in the “Modern” EraInteractivity in ApplicationsInteractivity in the BrowserWxAtlasVisualizing the FutureAcknowledgmentsVisualizing Visualization– Kevin Tyle

Visualization Way Back WhenVisualizing Visualization – Kevin Tyle

1st US Wx Bureau Synoptic MapVisualizing Visualization – Kevin Tyle

“1st” Upper Air MapVisualizing Visualization – Kevin Tyle

1st US Operational NWP MapForecasts for 5 January 1949 (P. Lynch, BAMS 2008)Visualizing Visualization – Kevin Tyle

1st Satellite ImageVisualizing Visualization – Kevin Tyle

Radar Imagery (WSR-57)Hurricane Donna (1960)Visualizing Visualization – Kevin Tyle

That 70s (Animation) ShowUAlbany Synoptic Lab Assignment (1970s)Visualizing Visualization – Kevin Tyle

Visualization in the “Modern”Era

McIDASVisualizing Visualization – Kevin Tyle

WXPVisualizing Visualization – Kevin Tyle

GrADSVisualizing Visualization – Kevin Tyle

NCAR GraphicsVisualizing Visualization – Kevin Tyle

NCLVisualizing Visualization – Kevin Tyle

GEMPAKVisualizing Visualization – Kevin Tyle

Radar Imagery (WSR-88D)Visualizing Visualization – Kevin Tyle

Stepping I”N”to I”N”teractivity:N-AWIPS

NTRANSVisualizing Visualization – Kevin Tyle

NMAP(2)Visualizing Visualization – Kevin Tyle

NMAP(2)Visualizing Visualization – Kevin Tyle

NSHARPVisualizing Visualization – Kevin Tyle

Vis5DVisualizing Visualization – Kevin Tyle

IDVVisualizing Visualization – Kevin Tyle

OthersVisualizing Visualization – Kevin Tyle

Visualization Products: StaticGraphics

GEMPAKVisualizing Visualization – Kevin Tyle

NCLVisualizing Visualization – Kevin Tyle

PythonVisualizing Visualization – Kevin Tyle

PythonVisualizing Visualization – Kevin Tyle

Interactivity in the Browser

Jupyter / GeoviewsVisualizing Visualization – Kevin Tyle

Hint.wind.fm and its OffspringVisualizing Visualization – Kevin Tyle

Earth.nullschool.netVisualizing Visualization – Kevin Tyle

VentuskyVisualizing Visualization – Kevin Tyle

WMS / OpenLayers / LeafletVisualizing Visualization – Kevin Tyle

WMS / OpenLayers / LeafletVisualizing Visualization – Kevin Tyle

”Nullschool” with winds on DTVisualizing Visualization – Kevin Tyle

WxAtlas: Leveraging Databases

WxAtlasVisualizing Visualization – Kevin Tyle

WxAtlasLarry Gloeckler (UAlbany DAES) and AVAIL (UAlbany Geography & Planning)Visualizing Visualization – Kevin Tyle

The Future

Alexa / SiriVisualizing Visualization – Kevin Tyle

Alexa / SiriVisualizing Visualization – Kevin Tyle

Alexa / SiriVisualizing Visualization – Kevin Tyle

GPU VisualizationLeigh Orf’s Tornado Visualization: http://orf.media/Visualizing Visualization – Kevin Tyle

Acknowledgments

Lance Bosart & Dan KeyserVisualizing Visualization – Kevin Tyle

Gary LackmannVisualizing Visualization – Kevin Tyle

Scott JacobsVisualizing Visualization – Kevin Tyle

David KnightVisualizing Visualization – Kevin Tyle

Steve Chiswell “Chiz”Visualizing Visualization – Kevin Tyle

Yuan Ho, Don Murray, Jeff McWhirterVisualizing Visualization – Kevin Tyle

Larry Gloeckler & AVAILVisualizing Visualization – Kevin Tyle

Ross LazearVisualizing Visualization – Kevin Tyle

Mohan RamamurthyVisualizing Visualization – Kevin Tyle

Tom YoksasVisualizing Visualization – Kevin Tyle

Gilbert SebensteVisualizing Visualization – Kevin Tyle

Daryl HerzmannVisualizing Visualization – Kevin Tyle

Russell DeSouzaVisualizing Visualization – Kevin Tyle

And one final admonition beforewe adjourn

And one final admonition beforewe adjourn Always remember to run gpend!!

Thank you!!!Questions?

Extra Slides

okay, so I've looked a little deeper and here's how it breaks down: 65% raw gridded data - 700GB/1.07TB 33% indexes - 350GB/1.07TBthe remaining 2% comprises header tables, coefficient tables, and sequencesso the large majority makes up just raw gridded dataand. "also . is any of the grid info transmitted in JSON? Or is it all just read infrom postgres?"yes, the data is pulled from the database and serialized to a JSON formattedstringwe use the simplejson library to do that, and 'dumps' methodi.e., simplejson.dumps(data)the serialized JSON string looks like:{'header': {'lo1': 0, 'la1': 90, 'dx': 2.5, 'dy': 2.5, 'nx': 144, 'ny': 73}, 'data':[long list of all data values to be plotted]}in other words, it's just a JavaScript object of key, value pairskeys are 'header' and 'data', and values are either another object of key, valuepairs, or a list containing the actual datathe data structure is analogous to nested dictionaries in Pythonthat's how JS handles dataand that's how Cambecc formats his data -- he runs the grib files through thegrib2json converter and produces exactly what I showed above

Visualizing Visualization Kevin R. Tyle, University at Albany, SUNY Unidata Russell L. DeSouza Award Seminar . . yes, the data is pulled from the database and serialized to a JSON formatted string we use the simplejson library to do that, and 'dumps' method i.e., simplejson.dumps(data)