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Metadata for New Zealand's National Vegetation Plot Databank. Nick Spencer and Susan Wiser Landcare Research New Zealand. What is NVS?. NVS (National Vegetation Survey) – New Zealand’s largest archive facility for plot-based vegetation data . http://nvs.landcareResearch.co.nz. - PowerPoint PPT Presentation
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Metadata for New Zealand's National Vegetation Plot
Databank
Nick Spencer and Susan WiserLandcare Research
New Zealand
What is NVS?• NVS (National Vegetation Survey) – New Zealand’s
largest archive facility for plot-based vegetation data
http://nvs.landcareResearch.co.nz
NVS - coverage
• Best in grassland and indigenous forest
• Collection intensity has varied over 50+ years
• 14 000 permanent and52 000 relevé plots
• NVS has many uses
Why metadata management?
• In the past – good for organising data
• Expanding content and function – makes metadata critical – e.g. Kyoto protocol reporting
• Metadata system redeveloped to meet new demands
What is metadata?
• Metadata is ‘information about information’
• Who, What, Where, When, Why and How …
Consequence of missing metadata• Knowledge about a dataset is lost overtime
From Michener et al (1997)
Time
Time of publication
Specific details are lost rapidly e.g. Dates
General details are lost through time
Death of investigator and loss of remaining records
Retirement or career change makes access difficultAccident may
destroy data or documentation
Info
rmat
ion
Con
tent
Why is metadata useful?
• Search and locate datasets
• Assess suitability of use
• Reduces the effort required to use data– metadata leads to better information efficiency (Michener et al 1997)
Caveat...
• A balance needed– more metadata means less research (Michener et al 1997)
Recent developments
• Goals
– Comprehensive
– Standards based
– Versatile
• Approach
– 1. XML based storage structures (‘Schema’)
What is XML? • eXtensible Mark-up Language
• Similar to HTML – but consists of user-defined tags to structure textual information
• Promotes universal data access– Machine and human-readable – Open standard – Written in plain-text (ASCII)
Recent developments
• Goals
– Comprehensive
– Standards based
– Versatile
• Approach
– 1. XML based storage structures (‘Schema’)
Recent developments
• Goals
– Comprehensive
– Standards based
– Versatile
• Approach
– 1. XML based storage structures (‘Schema’)
– 2. Separate the metadata and data systems (see the demonstration following this talk)
Developing the schema
• Looked to external metadata standards and profiles
ISO 19115 – Geographic metadata standardsDC – Dublin CoreEML – Ecological Metadata Language
• Adopted universal elements
Our Metadata Schema • 34 primary metadata elements + 105 distinct sub-
elements
• 68% match with source standards
• Grouped broadly as
– Identity (title, Id)– Content (information types, methods)– Context (location, time, purpose)– Admin (ownership, access, availability, status)
Notable features of our schema• Resources or related material
– Internal (e.g. a child)– Managed (e.g. photographs) – External (e.g. bird counts)
• Metadata containers and versioning
Version 2
Version 1
MetadataContainer
Metadata 1
Metadata 2
Outcomes
• Improved accessibility and consistency
• XML document approach
– Portable, flexible and extendable– Readily reformated for different uses
(e.g. web, text, apps)
• But…
– Few mandatory metadata elements– Relational database structured XML– XML tools and languages are less familiar
c.f. SQL (20+ year standard)
Acknowledgements
Data entry and administration Michelle Breach
Dept. of Conservation Liaison Elaine Wright
IT strategists and developers Jerry Cooper Nick Spencer Mark Fuglestad
Funded byFoundation for Research Science & Technology
Department of ConservationTerrestrial & Freshwater Biodiversity Information System
Plant ecologists Peter Bellingham Susan Wiser Larry Burrows Rob Allen