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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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relational database platforms
Relational Database Platforms
  • Excel
  • MS Access, Paradox,etc.
  • SQL Server
  • Oracle / Sybase
excel
Excel
  • Not recommended for long-term storage
  • No data-typing enforcement
ms access paradox etc
MS Access, Paradox, Etc.
  • Desktop database systems
  • Do not scale well
  • Front-end application development
  • Free / cheap and fairly beginner friendly
sql server
SQL Server
  • Microsoft’s database engine for larger scale databases
  • Serving live data on the web possible
oracle sybase
Oracle / Sybase
  • Enterprise size database systems
  • High cost and maintenance
  • Support for data exchange
  • Recommended if provided
general database design consideration
General Database Design Consideration
  • Databases should be designed to serve the data best not a particular question
general database design consideration1
General Database Design Consideration
  • Avoid storing redundant information by designing several tables, linking information as necessary
general database design consideration2
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 consideration4
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 consideration5
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 consideration6
General Database Design Consideration
  • Develop a species checklist for your area or use an existing one to assure highest taxonomic accuracy possible
asu s data model

Annotations

Secondary Compounds

TLC Records

Types

Specimens

Exsiccati

Localities

Multiple Identifications

ASU’s Data Model

R. Schoeninger

asu s data model1
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
Database Types and Implications for Use
  • Collections or taxonomic databases
  • Observation databases
  • Measurement databases
collections or taxonomic databases
Collections or Taxonomic Databases
  • Based on collected specimens
  • Highest degree of taxonomic information
  • Information on distribution varies
  • No information on abundance
observation databases
Observation Databases
  • Based on a sampling design for observations
  • Emphasis on absence/presence or abundance
  • Taxonomic value varies
measurement databases
Measurement Databases
  • Data on the ecology of a species
      • Laboratory measurements
      • Data from a literature search
interoperability
Interoperability

Distributed

Databases

HTML

Search

Application

Registering

Service

&

Data

Discovery

Tool

&

Target

Manager

Meta data

Query

Results

meta data
Meta Data
  • Data about data
    • Taxonomic: NBII, ISO
    • Spatial: FGDC, ISO
    • Ecological: EML
    • Air management?
standardization efforts
Standardization Efforts
  • Geo-referencing the data
  • Metadata standard
  • Keyword standard
  • Taxonomic thesaurus (ITIS)
  • Geographic thesaurus (Alexandria)
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