1. Deploying OGC Web Services GeoScience Victoria’s Experience Alistair Ritchie, Senior Information Geologist GeoScience Victoria

2. Outline Background GeoScience Victoria services Application schema and technology used deegree web feature service overview Geoserver ‘web-service’ overview Comparison of deegree with Geoserver app-schema The future Observations

3. Background GeoScience Victoria (GSV) Victorian state geological survey Custodian of state’s geology and mineral exploration data Why use web services and community schema? Maintain a number of systems which change over time Need a stable standard interface to data Need a context in which to improve data quality History of community involvement Joined CGI interoperability working group in 2004 Joined EarthResourceML working group in 2007 Close collaboration with AuScope/ASRDC since 2008

4. GSV Services – app. schema GeoScience Markup Langauge (GeoSciML) Deliver detailed geological map data Deliver results of drilling activities and resulting sub-surface sampling Participated in the development of the language and web services Geology services used by OneGeology geological map of the world Boreholes services support the National Virtual Core Library Earth Resource Markup Langauge (EarthResourceML) Deliver descriptions of mineral deposits and associated mining activities Participated in the development of the language and web services Collaboration with AuScope to deploy Australian network of services

5. GSV Services - Technology deegree v2.* GeoSciML v2.0 – testbed and production services EarthResourceML v1.1 – production GeoSciML v2.0 (boreholes) – testbed and production services deegree v3.0 Very little experience – German demo serving GSV data Candidate for GeoSciML v3.0 testbed Geoserver app-schema EarthResourceML v1.1 – test services (soon to replace deegree) GeoServer web-service GeoSciML v2.0 – in development to replace deegree

6. deegree overview Java OCG Web Server Application Developed at the University of Bonn, Germany Use stable release - version 2 Conforms to OGC WFS 1.1 specification Supports GML 3.1 app. schema... almost... Only one namespace No support of XML attributes All complex types must be «features» (no «types» or «data types») Has an XSLT layer to overcome this Transform ‘private’ GML to GeoSciML (request/response) Implement data-type polymorphism

7. deegree overview > GeoSciML Request > GeoSciML Response Deegree WFS Virtual outputFormat Client Datastore > inFilter > outFilter > Private Schema

8. Geoserver web-service Web service datastore for app-schema Adds the OGC WFS interface to a SOAP web service Developed by an AuScope funded embedded software engineer Binds to a ‘generic’ SOAP web service Xpath mapping of nodes in SOAP service response to nodes in the target schema

9. Geoserver web-service > GeoSciML Request > GeoSciML Response GeoServer web-service Client Datastore (Hibernate) request mapping response mapping GSV WS (SOAP) > Private Schema

10. deegree–Geoserver comparison deegree 2.nGeoserver app-schema polymorphism++ flexibility+- documentation/support-+ query capability-+ configuration-+ performance+-

11. deegree–Geoserver comparison

12. XSLT makes deegree 2 a flexible testbed tool Deegree 3 - an unknown quantity but promising reviews Geoserver is a complete WFS 1.1/GML3.1.n package Geoserver’s performance is a major drawback

13. Future work GSV’s Geoserver wish list User interface WFS 2.0 support Deploy multiple service end-points from one Geoserver instance Improved Web Map Service integration Data mapping and transformation tools – no database views? WFS-T for app-schema datastores 3D support (response and request) Performance must improve

14. Observations Know your database Must be well designed and configured Don’t neglect spatial and aspatial indexes Know your servers WFSs are like any other web app – deploy accordingly A good system administrator is vital Honour the specifications Community schema and profiles Web service specifications Either 100% compliant or not at all

15. Observations The hard work is mapping data models Majority of the deployment time is taken up here 1.Mapping corporate data models to the community schema 2.Mapping local vocabularies to community vocabularies 3.Physically realising the mapping in the data source The hardest work is social Technology is no longer an impediment Corporate IT service providers can be

16. Observations Corporate IT support is crucial At the very least they provide the holes in firewalls Provide stable domains for URIs Machine to machine infrastructure – machines are stupid Links to services must not break Links between services must not break Government department domains are bad for service URIs Significant bureaucratic effort required to acquire alternative Start working with corporate right from the start

17. Questions?