Considerations for the construction of lichen databases
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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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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.

  • Desktop database systems

  • Do not scale well

  • Front-end application development

  • Free / cheap and fairly beginner friendly


SQL Server

  • Microsoft’s database engine for larger scale databases

  • Serving live data on the web possible


Oracle / Sybase

  • Enterprise size database systems

  • High cost and maintenance

  • Support for data exchange

  • Recommended if provided


General Database Design Consideration

  • Databases should be designed to serve the data best not a particular question


General Database Design Consideration

  • Avoid storing redundant information by designing several tables, linking information as necessary


General Database Design Consideration

  • Keep information as consistent as possible (e.g. spelling of collector names, description of places)

    • Authority tables

    • Input masks


General Database Design Consideration


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)


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


General Database Design Consideration

  • Develop a species checklist for your area or use an existing one to assure highest taxonomic accuracy possible


Annotations

Secondary Compounds

TLC Records

Types

Specimens

Exsiccati

Localities

Multiple Identifications

ASU’s Data Model

R. Schoeninger


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


Database Types and Implications for Use

  • Collections or taxonomic databases

  • Observation databases

  • Measurement databases


Collections or Taxonomic Databases

  • Based on collected specimens

  • Highest degree of taxonomic information

  • Information on distribution varies

  • No information on abundance


Observation Databases

  • Based on a sampling design for observations

  • Emphasis on absence/presence or abundance

  • Taxonomic value varies


Measurement Databases

  • Data on the ecology of a species

    • Laboratory measurements

    • Data from a literature search


Interoperability

Distributed

Databases

HTML

Search

Application

Registering

Service

&

Data

Discovery

Tool

&

Target

Manager

Meta data

Query

Results


Meta Data

  • Data about data

    • Taxonomic: NBII, ISO

    • Spatial: FGDC, ISO

    • Ecological: EML

    • Air management?


Standardization Efforts

  • Geo-referencing the data

  • Metadata standard

  • Keyword standard

  • Taxonomic thesaurus (ITIS)

  • Geographic thesaurus (Alexandria)


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