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Considerations for the Construction of Lichen Databases

Considerations for the Construction of Lichen Databases. Data Management. Relational Database Platforms. Excel MS Access, Paradox, etc. SQL Server Oracle / Sybase. Excel. Not recommended for long-term storage No data-typing enforcement. Excel. MS Access, Paradox, Etc.

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Considerations for the Construction of Lichen Databases

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  1. Considerations for the Construction of Lichen Databases Data Management

  2. Relational Database Platforms • Excel • MS Access, Paradox,etc. • SQL Server • Oracle / Sybase

  3. Excel • Not recommended for long-term storage • No data-typing enforcement

  4. Excel

  5. MS Access, Paradox, Etc. • Desktop database systems • Do not scale well • Front-end application development • Free / cheap and fairly beginner friendly

  6. SQL Server • Microsoft’s database engine for larger scale databases • Serving live data on the web possible

  7. Oracle / Sybase • Enterprise size database systems • High cost and maintenance • Support for data exchange • Recommended if provided

  8. General Database Design Consideration • Databases should be designed to serve the data best not a particular question

  9. General Database Design Consideration • Avoid storing redundant information by designing several tables, linking information as necessary

  10. General Database Design Consideration • Keep information as consistent as possible (e.g. spelling of collector names, description of places) • Authority tables • Input masks

  11. General Database Design Consideration

  12. General Database Design Consideration • Take advantage of data-typing • Dates in date fields • Numbers in number fields • Don’t mix letters and numbers if possible (collection number, lat long)

  13. General Database Design Consideration • For any kind of descriptive information (e.g. substrate) consider developing and keyword taxonomy (e.g. bark, coniferous tree, Juniperus deppeana) • The better the keywords the more efficient the information retrieval

  14. General Database Design Consideration • Develop a species checklist for your area or use an existing one to assure highest taxonomic accuracy possible

  15. Annotations Secondary Compounds TLC Records Types Specimens Exsiccati Localities Multiple Identifications ASU’s Data Model R. Schoeninger

  16. ASU’s Data Model • Authority tables • Species check list (accepted names, synonyms, authors) • List of ecological keywords • List of substrates • List of collectors and determiners • List of localities

  17. Database Types and Implications for Use • Collections or taxonomic databases • Observation databases • Measurement databases

  18. Collections or Taxonomic Databases • Based on collected specimens • Highest degree of taxonomic information • Information on distribution varies • No information on abundance

  19. Observation Databases • Based on a sampling design for observations • Emphasis on absence/presence or abundance • Taxonomic value varies

  20. Measurement Databases • Data on the ecology of a species • Laboratory measurements • Data from a literature search

  21. Interoperability Distributed Databases HTML Search Application Registering Service & Data Discovery Tool & Target Manager Meta data Query Results

  22. Meta Data • Data about data • Taxonomic: NBII, ISO • Spatial: FGDC, ISO • Ecological: EML • Air management?

  23. Standardization Efforts • Geo-referencing the data • Metadata standard • Keyword standard • Taxonomic thesaurus (ITIS) • Geographic thesaurus (Alexandria)

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