Ecore's success stems from its power to describe deep semantic structure more concisely than Java. The downside are the tools. Certainly Ecore's structured editor is simple and effective and its graphical editor is rich and elegant but both are cumbersome compared to traditional text-based tools. The Xtext framework beckons with a solution: a textual syntax for Ecore. Going one step further, we leverage Xbase to define a concise textual notation for describing behavior and exploit it to implement constraints, derived features, operations, and data type conversion. We call this new language Xcore.

This presentation will explore Xcore's capabilities and demonstrate its powerful tools in action. They provide an experience reminiscent of JDT, as you'd expect, given their roots in Xtext. We'll also show how Xcore can be interpreted dynamically and compiled to Java statically, how it can leverage existing models currently represented as Ecore and GenModel, and how it's possible to convert between the combination of the two traditional forms and the new uniform textual representation. You'll leave this talk with an excellent understanding of some amazing new technology that will be available in the Juno release.

Leo Hsu and Regina Obe are PostGIS spatial database consultants and are showing the latest coolest stuff in PostGIS 2.0.

Raster support is the new big feature of PostGIS 2.0. You can now store georeferenced, multiband, multiresolution, with nodata value raster coverages in the popular spatial database. A raster coverage is typically stored as a table of many tiles. You can load rasters in any format supported by GDAL and the list of raster tables is available to applications in a table named raster_columns. You can do raster/vector analysis doing intersections as you are used to do them with vector data stored in PostGIS. You can also do raster analysis in the raster way with a set of map algebra functions working one pixel at a time, on the neighborhood of a pixel, on two rasters, with expressions or custom user PL/pgSQL functions. All analysis takes nodata values into account unless specified. You can edit rasters pixel by pixel, many pixels at a time, using raster coordinates or georeferenced geometries. You can also convert PostGIS rasters to geometries or to any raster format supported by GDAL. You can also dump those rasters in the filesystem using the GDAL driver or display them in QGIS or svSIG. With raster, topology, routing and 3D capabilities, PostGIS is becoming a complete in-the-database GIS driven with the SQL language.