November | 2008 | ∫  ∪  ∧∴  ∋  ∈  ⊇  ∧

I have put together preview for visually shaking maps where you don’t get just map layer names, but also preview of layers ! Somehow I couldn’t find any page on internet that would allow you to display layers from GetCapabilities WMS as image thumbnails. I’ve kept this idea for a long time and actually it started with yahoo pipes year ago – why not to visually display GetCapabilities as RSS feed with image thumbnails referenced as media type in the feed ? after little experimenting I realized that the value is in combination of position and WMS information, so the use case is “I am here on this place and hey WMS servers, give me all you know about this place…”

That lead me to the prototype of the site codenamed ‘MapBinder’ that allows you to visually combine WMS layers. Before you jump there, let me put here some credits to projects and people who enabled that – first it isOpenLayers 2.7 plus some sandboxed content that implemented GetCapabilities..I don’t remember exact location, then it is blog on tydlevidle.cz that implemented extension to read mapy.cz (mapy.cz is proprietary web based geoengine for maps like google but is using different projection). The last piece I found on some reference on geocaching.cz where someone pointed on conversion.js JavaScript by Tomas Ebenlendr. I forgot to mention that MapBinder is now synced with mapy.cz since it would be hard to overlay mapy.cz with JTSK-based projection, I have decided that reprojection will be done by user’s brain – having side by side maps – everyone can benefit from the content even they do not overlay.

Map Binder can be found on page: updated 07/2025 :https://www.sumbera.com/lab/wms25/wms25.html

. Feel free to save it and examine it. I believe that from this point desktop and web readers of WMS layers will display thumbnails for better user experience :).

I have heard first time the term “Appliantization” from Justin Lindsey a CTO of Netezza at Netezza User Conference 2008, September, Orlando. I must admit I love this term, especially since I was involved with virtual appliance concept for geospatial. At Intergraph I was evaluating Netezza Performance Server with gaining fascinating results – truly the peroformance runs in ranges you read in Netezza marketing materials – that is 10-100 times faster than equivalent general purpose database. Gartner put Netezza into leaders sections in their magic quadrant for 2008, Netezza has quite good support for spatial types and spatial operations in their database and with UDXes you can turn the machine into domain focused Data Warehouse Appliance.

More about Netezza Spatial : http://www.netezza.com/data-warehouse-appliance-products/spatial-analytics.aspx

But let’s start from the beginning…

“One size fits all” approach doesn’t fit for high performance.

Computing Appliances are equipment with a specialized laser focus on solving targetted IT problems. In contrast to general purpose hardware and software solutions, computing appliances leverage a high level of coherence or fidelity between wired hardware and software pieces. Appliances hide the technical complexity of a system and expose the simplicity of the system. According to the Gartner definition an appliance is “a prepackaged or preconfigured balanced set of hardware, software, service and support, sold as a unit with built-in redundancy for high availability.”

Recently in the data warehouse market, new appliances have emerged with support for geospatial data, processing and present revolution (and disruptive) technology. These new appliances provide a performance boost by tackling the way large amounts of geospatial data can be effectively processed. These performance boosts are reaching orders of magnitude in comparison to general purpose database counterparts like Oracle.

Geospatially empowered Data Warehouse Appliances (DWA) with Massively Parallel Processing (MPP) architecture can scale out into the hundreds of terabytes, have capabilities to perform spatial queries in seconds instead of minutes or hours, and provide to the user new levels of experience with the affordable instant geospatial analytics.

With a huge volume of geospatially related data, there are many technical reasons to tune and assemble hardware with software and encapsulate all the complexity together into a self-contained ‘simple’ appliance with standard endpoints for interfacing. These self-contained appliances are easier to maintain and manage keeping the total cost of ownership lower than their general purpose counterparts.
2008 will be known as the year of “Appliantization.” In the data warehousing domain, appliances such as Netezza NPS, Oracle Exadata or Microsoft’s code-named project “Madison” (confluence of DataAllegro and SQL Server) are enabling technologies for high performance spatial analysis.

Simplicity is managed complexity and computing appliances just do this