1. New Zealand’s National Vegetation Survey Databank: improving access and interoperability Susan Wiser, Jerry Cooper, Nick Spencer & Larry Burrows Landcare Research PO Box 69, Lincoln 8152 New Zealand http://nvs.landcareresearch.co.nz

2. What is NVS? New Zealand’s primary repository for plot-based vegetation data 52,000+ unmarked relévés; 12,000+ relocatable permanent plots Data collected over last 50+ years; most permanent plots established in 1970s and 1980s Built on standardised data collection methods Archive is both physical and electronic Data contributed and used by –Conservation Department –Environment Ministry –Environmental Research Institutes –Territorial authorities –Universities

4. Examples of how NVS data is currently being used Traditional uses: –assess change in vegetation composition and structure Succession, natural disturbance impacts, exotic plant invasion, exotic animal impacts –Assess variation in composition across a region for conservation planning –Vegetation description Syntheses: –Use of forest structure data for national level estimates of C storage –Developing national-level models to predict occurrence of major tree species in relation to climate –Examining patterns of stand turnover with latitude

5. Focus of Recent Developments Improving awareness & accessibility Initiating developments that will –Facilitate exchange of data and tools with other vegetation databanking efforts –Allow ready integration with other kinds of data GIS layers Species attribute data Specimen vouchers

6. Drawbacks of old system Data stored in condensed ASCII format Data entry and analysis relied on DOS-based software Syntheses difficult

7. User needs analysis identified four types of end-users: Researchers raw data in simple formats precise metadata Biodiversity managers guidelines for consistent methods for data collection easy to use data entry and summary tools Policy makers national and international reporting legal and technical framework for interagency data transfer guaranteed secure storage and database maintenance Database to database users clean data from selected fields metadata and copyright rules attached data update mechanism

8. Vision: an integrated/interoperable information system accessible to any kind of user Data content standards (dictionaries & thesauri) Data structure standards (schemas, models) Legal agreements for data provision Awareness and use of emerging technologies (e.g. XML, web services) Incremental development to maintain flexibility and demonstrate achievements

9. Ongoing progress Relational database has been designed and implemented for metadata and plot data –Database in MS-SQL Server, MS-Access front end for editing, viewing, and exporting data

11. Ongoing Progress Relational database has been designed and implemented for metadata and plot data Website for information about NVS and data access

13. Ongoing Progress Relational database has been designed and implemented for metadata and plot data Website for information about NVS and data access Data ownership policies and protocols for data use

15. Ongoing Progress Relational database has been designed and implemented for metadata and plot data Website for data access and information Data ownership Online access to metadata

19. National Carbon Monitoring System Coomes et al. 2002. Designing systems to monitor carbon stocks in forests and shrublands. Forest Ecology and Management 164:89-108

20. Carbon Monitoring System and use of emerging technologies Remote data entry via Internet –Client application (we’ve used MS-DOT NET) –Not browser-based Can summarise and analyse data using web services XML approach to storing result sets, metadata, and audit trail reporting

21. Screen shot of CMS data entry/viewing interface

24. Carbon Monitoring System: Utility of Vegbank model Test of Vegbank data model for our purposes Many commonalities and parts of model we could adopt almost ‘as is’. We have adopted alternative solutions for Treatment of tagged individuals Spatial location information Certain types of physical data (e.g. soils) will sit in parallel tables Link to literature citations Taxonomy

26. Do data content and structure standards exist for vegetation data? Data dictionaries exist for several databases What about thesauri? Utility of XML schemas –Natural way of expressing relationships –Extensible –Rapidly becoming standard mechanism for describing and exchanging data –Open standard –Many emerging tools for reporting, querying etc. –Data can be validated against schema

27. Developing a schema for our metadata Aligned with data standards of Landcare Research, NZ E-government, and International Standards (e.g. ANZLIC, EML and ISO 19115

28. Acknowledgements Data entry and administration Michelle Breach Database design and programming Nick Spencer Jeremy Connell Web design Mark Fuglestad Plant ecologists Peter Bellingham Susan Wiser Larry Burrows Rob Allen Ian Payton Claire Newell Dept. of Conservation Liaison Elaine Wright Database integration and strategy Jerry Cooper Grant Hunter Funded by Foundation for Research Science & Technology Department of Conservation Terrestrial & Freshwater Biodiversity Information System