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OpenGeo

OpenGeo. Overview. Who is OpenGeo? Product How to Engage. In The Beginning. (The Open Planning Project). Towards OpenGeo. From a side project of TOPP To sustaining contract work And the push to grow. Grow!. Overview. OpenGeo is a product company

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OpenGeo

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  1. OpenGeo

  2. Overview • Who is OpenGeo? • Product • How to Engage

  3. In The Beginning (The Open Planning Project)

  4. Towards OpenGeo • From a side project of TOPP • To sustaining contract work • And the push to grow Grow!

  5. Overview • OpenGeo is a product company • We provide support and customer focused development for our products • We are 501(C)(3) corporation with a dot.org business model

  6. The OpenGeo Suite

  7. The Geo Stack

  8. The Rich Client

  9. GeoExt is built on OpenLayers and Ext.js • OpenLayers is the defacto standard for javascript mapping clients • Ext.js is a widely used javascript library for rich internet applications

  10. GIS-based Applications Create tools to let developers make rich GUI desktop-like applications that leverage GIS operations But designed for their users who may not know ‘GIS’ Many users get trained on GIS and then use the same 5 operations GeoExt plus Web Processing Service plus local storage (Gears or GeoServer) ‘ArcView 3 for the web’

  11. Through the Web Editing • Vector editing in a javascript client • Desktop application look and feel

  12. The Cache

  13. GeoWebCache Integration • Caches tiles as used by most common slippy map interfaces • Ideal for layers that rarely change • Delivers raster/KML tiles to: • OpenLayers • Google Maps/ Earth • Microsoft Virtual Earth • Speeds up data delivery by a factor or 10-100 GeoServer GeoWebCache Persistent raster/KML tile cache

  14. Scalability Already serving IGN France’s full infrastructure: 50 servers total, external ones serve on average 30,000 unique visitors a day No license fees makes things friendly for the cloud Burst tile creation - EC2 or other to process tiles in hours, not weeks Clustering and fail over best practices and advice

  15. ---------- ---------- --------- ---------- ---------- ---------- --------- ---------- ---------- ---------- --------- ---------- GeoServer GeoWebCache Shapefile.zip GML2 GML3 GeoRSS GeoJSON CSV/XLS Shapefile WFS 1.0 Vector files Raw vector data WFS 1.1 PostGIS DB2 Oracle MySql PNG, GIF JPEG TIFF, GeoTIFF SVG, PDF KML/KMZ WMS 1.1.1 DBMS ArcSDE WFS Styled maps WCS 1.0 GeoTIFF ArcGrid GTopo30 Img+World Servers GeoTIFF ArcGrid GTopo30 Img+world Mosaic MrSID JPEG 2000 ECW,Pyramid WCS 1.1 Raw raster data GWC KML superoverlays Google maps tiles Raster files 1.7.x

  16. KML SuperOverlays • Problem: you have a huge data set you want to display on Google Earth • the generated KML is simply too big • the features you want to display have a clear hierarchy • zoomed out, you want to display only the most important ones, • less important should appear progressively, as you zoom in, while leaving the important ones visible • of course, everything should happen in the most fluid way

  17. KML SuperOverlays • Solution • create a pyramid like structure • have Google Earth regions drive what is visible at each scale • use a tile cache to maximize delivery speed • This requires GeoServer 1.7.3 and above

  18. Versioning and Advanced Workflow

  19. Improved Presentation Options • Play with tiling, antialiasing, format and map size • Issue dynamic filters on your data

  20. Improved Format Support • Significant ArcSDE improvements • Fewer connections used during normal operation • Supports versioning, read and write against the default version • Uses native ArcSDE transactions on write • Full ArcSDE raster support • Oracle Spatial datastore rewrite, now fast and robust, full transactions • DB2 and SQL Server 2008 read and write (WFS-T)

  21. Standards Support • WFS Reference Implementation • WFS, WFS-T 1.0 • WFS, WFS-T and WFS Xlink 1.1 • WCS 1.0 compliant and 1.1 Reference Implementation • WMS 1.1.1 and full SLD • SLD is native style format • KML with Super Overlays • GeoRSS, GeoJSON, Shapefile, PDF, WMS-C, CSV, XLS

  22. REST Configuration • Prototype worked on during the last year • Allows full programmatic configuration using simple REST calls (e.g., mass configuring 100 layers, adding new data as it comes in, etc.). • Most programming languages have REST bindings, can script control of GeoServer • Will be further developed in the 2.0.x series

  23. SLD Visual Editor

  24. Forget Flat Rasters. . . • Support for N-dimensional coverages (3d + time) • Full WCS support, mapping slices using WMS time and elevation parametersBeing coded right now in a branch

  25. On Google Geo Search • Can publish data to be crawled by Google • Shows up in search results on Maps/Earth

  26. The Database

  27. By the Numbers (Annual) • Downloads • Source = 41,600 • Win32 = 70,000 • Web Site • Visits = 212,000 • Visitors = 136,000 • Subscribers • User List = 1,700 • Developer List = 270

  28. Performance • Published benchmarks against “leading brand” not allowed. • Anecdotally... • Vendor loaded PostGIS and “leading brand” with UK Ordnance Survey (500M objects) • “PostGIS was faster to load and query, easier to manage.”

  29. Performance • Published benchmarks against “leading brand” not allowed. • Anecdotally... • Government ArcSDE instance hung when Oracle patch applied, so they brought up emergency PostGIS clone • “PostGIS saved our ass, and while we were on PostGIS the queries actually ran faster.”

  30. ETL Tools Graphical workbench Hundreds of formats Database connections Schema transformation Embedded scripting (TCL, Python) Spatial transformations Proprietary Command-line tool (ogr2ogr) Tens of formats Database connections Minimal schema transformation Embedded SQL engine Open source http://www.gdal.org/ogr http://www.safe.com/fme

  31. Supported Types • POINT • LINESTRING • POLYGON • MULTIPOINT • MULTILINESTRING • MULTIPOLYGON • GEOMETRYCOLLECTION • CIRCULARSTRING • COMPOUNDCURVE • CURVEPOLYGON • MULTICURVE • MULTISURFACE

  32. Supported Functions (Predicate) • ST_DWithin(geom, geom, radius) => boolean • ST_Intersects(geom, geom) => boolean • ST_Contains(geom, geom) => boolean • ST_Touches(geom, geom) => boolean • ST_Overlaps(geom, geom) => boolean • ST_Crosses(geom, geom) => boolean • ST_Covers(geom, geom) => boolean • ST_CoveredBy(geom, geom) => boolean • ST_Relate(geom, geom, pattern) => boolean • ...

  33. Supported Functions (Analytic) • ST_Distance(geom, geom) => real • ST_Distance_Sphere(geom, geom) => real • ST_Distance_Sphereoid(geom, geom, spheroid) => real • ST_Area(geom) => real • ST_Length(geom) => real • ST_Length_Spheroid(geom, geom, spheroid) => real • ST_Equals(geom, geom) => boolean • ST_IsValid(geom) => boolean • ...

  34. Supported Functions (Constructive) • ST_Union(geom, geom) => geom • ST_Intersection(geom, geom) => geom • ST_Difference(geom, geom) => geom • ST_SymDifference(geom, geom) => geom • ST_Buffer(geom, distance) => geom • ST_Centroid(geom) => geom • ST_ConvexHull(geom) => geom • ST_PointOnSurface(geom) => geom • ...

  35. Supported Functions (I/O) • ST_GeomFromText(wkt) => geom • ST_GeomFromWKB(bytea) => geom • ST_AsText(geom) => string • ST_AsGML(geom) => string • ST_AsKML(geom) => string • ST_AsGeoJSON(goem) => string • ST_AsSVG(geom) => string • ST_AsBinary(geom) => wkb-bytea • ...

  36. Used by • Mass market real estate information • MySQL couldn't do complex spatial joins fast enough • Now using PostgreSQL / PostGIS • http://blog.redfin.com/devblog/category/performance

  37. Used by • Mass market imagery web services • Oracle couldn't serve queries fast enough • Informix got too expensive as they grew • Now using only PostgreSQL / PostGIS • http://www.postgis.org/documentation/casestudies/globexplorer/

  38. Used by • Manage federal topographic database (over 100M features) • Tested Oracle, DB2, and PostGIS • Found no technical advantage to Oracle or DB2 • Proceeded using PostGIS, no procurement process required • http://www.postgis.org/documentation/casestudies/ign/

  39. Business

  40. OpenGeo.org

  41. Building the Open Geospatial Web Making Geospatial Information Open and Accessible By bringing Open Source Principles to Geo Working by building OS software that gets used by all In the context of a hybrid organization

  42. Software Business before Open Source Proprietary Software sold boxes of ‘software’ Customer thought they were just buying the code, but there is far more to software: Manuals, Support Bug fixes, new features Training, integration, custom solutions Software companies made huge profit margins

  43. Software Business after Open Source High quality code is now free A new class of Open Source companies has emerged There is a market for everything around the code Support, manuals, training, integration, additional development, services Profit margins on code are lower and lower Smart companies move up the value chain

  44. Towards the ‘dot-org’ Full Cost Recovery for OpenGeo Spin off like Mozilla Corporation Reinvest profit in similar ‘dot-orgs’ Make Capital viral like the GPL Require complete transparency Business built on Open Source principles

  45. The Full Solution OpenGeo Enterprise

  46. How to Engage • Basic Edition • Professional Edition • Enterprise Edition

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