OpenGeo 1

Overview Who is OpenGeo? Product How to Engage

In The Beginning (The Open Planning Project) Founded by Mark Gorton in 2001 Makes his money with Hedge Funds, Brokerage Firm, Limewire Wants to improve New York City with better urban planning In to technology and open source (limewire was released as OS after he read Cathedral and Bazaar) (The Open Planning Project)

From a side project of TOPP To sustaining contract work Towards OpenGeo From a side project of TOPP To sustaining contract work And the push to grow Up until this point GeoServer had just been one of TOPP's projects, kept up since people were using it, it was doing good in the world. There were three people working on it, and since TOPP had the core developers they would be contracted by people who wanted to improve the software. My goal was to be completely self sustaining by doing contracts Near the middle of 2007 we got really close, and told the good news to our funder. Who responded: 'Great! You should hire more people.' I protested: 'But I'm just about to reach my goal of sustainability, more people will cost more'. Mark responded: 'Well it will be more sustainable in the long run'. To which I could say nothing. Grow!

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

The OpenGeo Suite What we've done is assemble what we believe are the best of breed components for web-based geospatial work. We provide support and improvements on them, and we invest heavily in making each of them the best, and in making the whole work seamlessly. It's an open suite, interoperating with Open Standards, and working great with proprietary solutions as well. We don't believe in locking you in, we want it to work with your existing system. You can flexibly migrate over PostGIS can be used as backend by ArcSDE 9.3, and most every desktop and server GIS can read it directly or with a plugin GeoServer works with every major data format. Outputs all standards plus KML for Google Earth, pdf, geojson GeoWebCache outputs to WMS, Google Earth, Virtual Earth, Google Maps OpenLayers works with Google Maps, Virtual Earth, Yahoo! Maps, other tiles, plus WMS, GeoWebCache. New support to read ArcIMS and ArcGIS Server directly Is it good? Talked to some guys from GBIF the other day, working with a partner who had been spending months on an ArcGIS Server client. In one day Javier set up a GeoServer/PostGIS/OpenLayers that was clearly better. Way faster, nicer interface.

The Geo Stack At this point we could have just hired ten more developers to work on GeoServer and have it be a huge package solution. This would be awesome for GeoServer, but would likely kill the growing community, by sucking all the air towards TOPP. But we decided the best way was to leverage existing Open Source communities to improve the whole story around GeoServer. Hiring key developers in great projects to help steer them towards where we wanted to go. Our philosophy is to keep each piece architecturally independent, using open standards, to grow the maximum community around it. That way our investment can go much further than if we tried to grow communities on our own.

The Rich Client While OpenLayers provided the map, we wanted to extend the interface to give a rich desktop type feel A number of OL developers had found Ext.js, and made rich mapping applications with it. We decided to help grow a community, forming GeoExt with Camp to Camp and others Our goal is to be able to provide rich GIS functionality, but in applications that anyone can use. No need to buy a GIS and then train someone on it when you can just make a web application that has the five GIS features they need in an intuitive interface * No need for a ‘buffer’ operation when you can have a ‘show all radio towers within 5 miles of this stream’

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

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’

Through the Web Editing Vector editing in a javascript client Desktop application look and feel Around this time OpenLayers had emerged as clearly the best of the web mapping clients clients. And GeoServer could use a facelift - servers without nice clients are just a bunch of XML. Hired Tim Schaub, one of the top three contributors to the library. Work with WMS, WFS, WFS-T, Google Maps, Virtual Earth, GeoRSS Easy to swap out base map providers, not locked in Tiled Mapping Advanced editing, versioning Very flexible API, used as the basis of web apis for IGN France and Ordnance Survey in UK. Great to develop against

The Cache Next we needed something to accelerate our maps, dividing in to tiles. Started just recommending TileCache, but hard to install with GeoServer. Jython was just too slow. Built GeoWebCache on JtileCache, a Google Summer of Code Project Have reached 1.0.1, and has a growing community. Features Integrated with GeoServer Expose layers on Google Earth, Virtual Earth, Google Maps, OpenLayers Very fast, different backend options for scalable caches Metatiling, Built in seeder, accessible from web, restful configuration interface Next improvements will be to cache dymanic maps efficiently But we keep it architectually independent, and it has its own community, people use it with MapServer and others.

Persistent raster/KML 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

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

GeoServer Features Best standard implementations (WMS 1.1.1, WCS 1.0, 1.1 (RI), WFS 1.0 (RI), 1.1 (RI), SLD, Filter, WFS-T (RI), KML, GeoRSS) Great Google Earth support (funded by Google) Versioning features Integrated Security Web 2.0 output - GeoRSS, GeoJSON, KML - on Google Earth and Maps, Virtual Earth Web admin console 64-bit, built on java, scalable with J2EE Fast Restful API for programmatic configuration of services PostGIS, Oracle, DB2, ArcSDE (raster and vector), MySQL, Shapefiles, GeoTiff, ArcGrid, JP2K, MrSID, ECW

GeoWebCache GeoServer 1.7.x ---------- --------- GeoWebCache GeoServer Shapefile Shapefile.zip GML2 GML3 GeoRSS GeoJSON CSV/XLS WFS 1.0 Vector files Raw vector data PostGIS DB2 Oracle MySql WFS 1.1 PNG, GIF JPEG TIFF, GeoTIFF SVG, PDF KML/KMZ DBMS WMS 1.1.1 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 Raster files GWC KML superoverlays Google maps tiles 1.7.x

Problem: you have a huge data set you want to display on Google Earth 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

This requires GeoServer 1.7.3 and above 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

Versioning and Advanced Workflow The GeoWeb node should easily encourage participation on datasets Some may choose to use versioning and open their layers for all to edit, like butterfly parks Others may keep it closed, but let users comment and spot bugs, which go through extensive workflow process like emergency roads Should be easy to configure the workflow, to encapsulate the norms of different communities.

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

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)

WFS Reference Implementation WFS, WFS-T 1.0 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 24

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

SLD Visual Editor

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

On Google Geo Search Can publish data to be crawled by Google Shows up in search results on Maps/Earth 28

The Database The final major piece came at the beginning of the year, with Paul Ramsey joining OpenGeo. PostGIS was always our preferred database, as it's clearly the gold standard in the Open Source Geo world. We only want to provide support if we are actively contribute and employ at least one core developer. Paul has already pushed out a number of great PostGIS improvements. Features Simple features for SQL Built on Postgresql - acid compliance, referential integrity, stored code, triggers Spatial indexes All common spatial operators - buffer, union, intersection, bbox, etc

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

Published benchmarks against “leading brand” not allowed. 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.”

Published benchmarks against “leading brand” not allowed. 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.”

ETL Tools Graphical workbench Command-line tool (ogr2ogr) 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.safe.com/fme http://www.gdal.org/ogr

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

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 ...

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 ...

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 ...

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 ...

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/p erformance

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/

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/

Business Our funding has been primarily an investment from Mark Gorton, who continues to put money in as he sees the potential for us to reach a point of sustainability - recovering all our costs. We are set up in a not for profit structure, so he will never see financial returns. But by pushing us towards sustainability his money goes much farther in the world. Once we reach profitability the investment will go back to TOPP, to start other initiatives to help the world

OpenGeo.org To get to full cost recovery, our next step is to transition from a services / consulting company to a 'product' company. We plan to compete head to head with expensive proprietary solutions. Creating a premium brand, turning the open source assumptions on their head by focusing on the fact that you get applications tailored to your needs, and direct contact with core developers. Hiring traditional biz dev and sales, doing marketing and PR, to sell a product that we define and improve

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 As a mission driven organization, our goal is to play a key role in creating the Open Geospatial Web We feel the best way to accomplish the most impact for the least amount of investment is to create a hybrid organization, combining the best of the for profit and non-profit worlds Our software is built with values of openness We emphasize the latest advances, google earth, etc, but always stay rooted in the standards. Focus on data and users, not metadata, building the infrastructure bottom up instead of top down as most traditional SDIs have The core goal of OpenGeo is not to make profit, but to make great software to advance the Open Geospatial Web. We just compete in the market providing services so that we can build more software.

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

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

Full Cost Recovery for OpenGeo Spin off like Mozilla Corporation 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 Once we get to full cost recovery, our plan is to spin off OpenGeo as it's own company, fully owned by The Open Planning Project. This will include profit sharing for employees, so they can share in the success of what they built And for practical reasons, we don't want our best employees going to do a start up on the same software because the organization is making tons of money and they aren't OpenGeo will also then be in a position to 'incubate' other similar types of organizations, for example transit or land use planning, that will start as OpenGeo projects, but then spin off to have their own control, making money in the market to support themselves. TOPP will take any profit and start other, new social ventures that are structured similarly. A long term goal of mine is to make this type of structure a new type of entity in the world. Drawing inspiration from Open Source Software, applying the principles to running a business Should have a higher level of transparency Open Books, you can read all our team coordination lists Any profit made by a dot-org has to be invested in other dot-orgs Using capital like the GPL used copyright law - to create a 'logic of the wedge', where any success is encoded to engender future success. I believe this type of structure is more appropriate to creating and maintaining Open Source software than a for profit company or a non-profit foundation - employ the core developers and find a business model that works for them.

OpenGeo The Full Solution Enterprise Next step is to launch OpenGeo Enterprise, a full solution that large enterprises can purchase to support their full deployments It will be based completely on open source software, contributing back as much as possible. The benefit to them will be a package solution, we will custom tailor the packaging to their needs, provide a professional face to the OS world. Our aim is to leverage Mark's investment to grow to an organization size where we can complete a 'win-win-win' situation for all involved OS Software wins, as developers are employed full time to work on improving the code Institutional customers win, with access to a one stop shop to support their deployments Open Source Users win, as there is a sustainable funding stream Core developer win, by getting to do what they love.

How to Engage Basic Edition Professional Edition Enterprise Edition

Basic Edition Core Support for OpenGeo Enterprise Unlimited bug fixes 20% discount on services rate 1 day response time, email support during business hours $15,000 / year

Professional Edition Core Support for OpenGeo Enterprise Unlimited bug fixes 120 service hours (Upgrades, Training, Configuration, Installation, Performance, Core Development) Oracle, ArcSDE, SQL Server support 25% discount on services rate 1 day response time, email & phone support during business hours $30,000 / year

Enterprise Edition Core Support for OpenGeo Enterprise Unlimited bug fixes 250 service hours (unrestricted) Oracle, ArcSDE, SQL Server support Clustering and security support 40% discount on services rate 4 hour response time, email & phone support 24/7 $70,000 / year