SCENZ-Grid The implementation of a Science Collaboration and Computation Environment Niels Hoffmann Landcare Research

Manaaki Whenua / Landcare Research is New Zealand's foremost environmental research organisation. Our research focuses on three key areas: Sustaining and restoring biodiversity; Sustaining land environments; Sustaining business and living. Three themes relate to these three areas: Climate change mitigation and adaptation Maori sustainability Invasive species and disease impacts

Sustaining biodiversity & restoration Sustaining land environments Sustaining business & living Climate change Maori sustainable futures Weeds, pests and diseases Capability and collaboration Landcare Research Manaaki Whenua Key outcomes Cross-cutting outcomes Underpinning strengths

Data and Computational pressure NOW – 25m national data density NEAR FUTURE – sub 5m national data density / (peri-)urban sub 1m LIDAR data density Modelling environment NOW – essentially batch oriented & 2.5D DESIRED – interactive 4D, with real-time visualisation feedback Managed data NOW – preserve the data, memorise the model DESIRED – keep the model for on-demand re-use

science : collaboration : environment SCENZ-Grid proposes that we can Do science research on-line together Share each other’s data – not duplicate it Collaboratively develop & use shared models / workflows Use shared compute resources Connect researchers directly to consumers : policy / managers / educators / public spatial : computation : engine

Dublin Core / RDF Repository Web Services Doc Img Geo Name Search Consume Query Tag Comment Create Workflow OAI-ORE SPARQL

A personal home page with links to relevant work for organising and retrieving a large variety of digital resources

Detailed view of a resource – in this case a modelling workflow, that can be edited by maybe changing the inputs or logic and then re-used

Databases Content (WMS, WFS, WCS) Functionality (WPS) DesktopWeb

PostGIS / SqlServer2008 GeoServer GeoWebCache 52North Geoprocessing ArcGIS / UdigOpenLayers GeoExt

Why WPS ? Distributed Architecture Interoperability Modeling approach (as opposed to data centric outcome) (Grid-) Computing

Why 52North ? Build upon robust OS Libraries (JTS, Geotools, xmlBeans, Servlet API) Pluggable framework for algorithms Support for raster processing Support for Grid-Computing

Currently using Unicore Middleware Planning a migration to Globus Middleware to integrate with BeSTGRID Landcare repository Sextante repository

WPS Geoserver 104 Intel Xeon cores 2.8GHz each 386GB RAM 2.6TB storage ~1.16 TFLOPS Air cooled Gb Ethernet nterconnects 4.2kW power

Spatially query across datasets from multiple organisations. Qmap: Geology from GNS NZFSL: Soil Data from Landcare Research What kind of relationships exist between soil type and bedrock. What is the association between groundwater quality and soil. Investigate relationships between ecology, ground water and soil.

Regolith: Layer between Bedrock and Soil Erosion modelling Groundwater flow modelling WPS Algorithm to combine 2 datasets based on a similarity matrix User interface to enable experts to adapt the similarity matrix

Establish the ‘similarity’ of the datasets Different origin of attributes Different classification Similarity Matrix quantify where the classifications match Expert to decide similarity based on documentation

QMAP WMS NZFSL WMS Lookup WS Portal User WPS User Interface View Portlet WebService WorkFlow Engine WPS Web Services Data: WMS Business Logic: SOAP

Lookup WS WPS User

Thank You, Any questions? Slide Credits: Chris McDowall, Aaron Hicks science : collaboration : environment spatial : computation : engine