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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. - PowerPoint PPT Presentation
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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
ASU’s Data Model
SpecimensTLC Records
Secondary Compounds
Multiple Identifications
Types
Localities
Exsiccati
Annotations
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
RegisteringService
&Data
Discovery Tool&
TargetManager
HTML Search
Application
Meta data
Query
Distributed
Databases
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)