1. BioNet: Improving the web based data discovery and mapping experience Paul Flemons Centre for Biodiversity and Conservation Research Australian Museum

2. Data Sharing Initiatives OZCAM – Online Zoological Collections of Australian Museums a clone of the Australian Virtual Herbarium standards based and a true distributed data model audience – taxonomists and research scientists focused on accessing data www.ozcam.gov.au – application is password protected www.ozcam.gov.au

3. Data Sharing Initiatives BioNet (Biodiversity Information Network) – collaboration of NSW Government Natural History and Natural Resource agencies focused on creating a fast application for use by State Government planners, scientists, and natural resource managers a quasi distributed data model focused on speed and useability of the application

4. BioNet New South Wales (NSW) Government Biodiversity Information Network – the partners:- Australian Museum – Fauna - specimen based collections databases NSW National Parks and Wildlife Service – Fauna and Flora observations databases Sydney Royal Botanic Gardens - Flora – specimen based databases NSW Fisheries – Aquatic Fauna - observations database

5. BioNet What we wanted: Fast and user friendly data discovery and web mapping application, server side and browser independant Infrastructure that is:- Extensible – new partners easily included Custodians retain control of their data whilst serving it Secure from outside interference Modular in its development Uses standards where applicable

6. BioNet Our Approach – pragmatic and user focused Provide each partner with secure access to their own discrete hardware and software resource at a secure ISP Enables involvement of partners who otherwise would not be able to be involved Lack resources Security concerns Ensures each partner has complete control over their data and what they provide to the network Locate application and all data sources within this same ISP Improves database query speed Improves background layer access speed

7. BioNet Our Approach Use offline automated processes to :- Filter and validate data against the fauna Master Names List Run spatial queries to populate database fields enabling fast querying of standard geographical and administrative areas for species Assist collaborators in managing their data

8. INTERNETINTERNET Application and Map Server Cold Fusion, ArcIMS, ArcSDE BioNet Infrastructure In Situ Databases Data Filter Firewall RBG Collections Flora MNL Local Copies of Databases Fauna and Flora Observations Fish Observations AM Fauna Collections Fauna MNL RBG Collections Flora MNL Fauna and Flora Observations Fish Observations AM Collections Fauna MNL Secure Access ISP SQLServer

9. BioNet Future development Interface improvements Modelling Embrace standards and protocols as they mature Open source? Include distributed data sources where relevant Develop other applications as desired using the same mapping and data discovery code with different network data models Continue to focus on the users needs and developing applications that enhance the users productivity and the outcome for biodiversity conservation