Taming Rich GML With stETL, A Lightweight Python Framework For Geospatial ETL
Channel: Andrea Ross
Date: 2013-09-28

Data conversion combined with model and coordinate transformation from a source to a target datastore (files, databases) is a recurring task in almost every geospatial project. This proces is often refered to as ETL (Extract Transform Load). Source and/or target geo-data formats are increasingly encoded as GML (Geography Markup Language), either as flat records, so called Simple Features, but more and more using domain-specific, object oriented OGC/ISO GML Application Schema's. GML Application Schema's are for example heavily used within the INSPIRE Data Harmonization effort in Europe. Many National Mapping and Cadastral Agencies (NMCAs) use GML-encoded datasets as their bulk format for download and exchange and via Web Feature Services (WFSs). 

See the full description here: http://2013.foss4g.org/conf/programme/presentations/156/