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Relational databases as a tool to manage environmental data at the research plot scale. Tyler Erickson Institute of Arctic and Alpine Research University of Colorado Deborah Donahue Data Manager, Snow Hydrology Research Group Donald Bren School of Environmental Science and Management
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Relational databases as a tool to manage environmental data at the research plot scale Tyler Erickson Institute of Arctic and Alpine Research University of Colorado Deborah Donahue Data Manager, Snow Hydrology Research Group Donald Bren School of Environmental Science and Management University of California
Q: Why Relational Databases? A: To Manage Large Data Sets
Storage Choices • Field notes • Good for data collection • Difficult to share
Storage Choices • Field notes • The bookshelf
Storage Choices • Field notes • The bookshelf • The file cabinet
Storage Choices • Field notes • The bookshelf • The file cabinet • Etc.
Distributable Storage Choices • Text data files • Most flexible; easy to set up & distribute • Difficult for analysis
Distributable Storage Choices • Text data files • Spreadsheets • Good for analysis • Inflexible distribution
Distributable Storage Choices • Text data files • Spreadsheets • Database • Best for large high-dimensional datasets; flexible distribution • Work intensive to set up & maintain
Distributable Storage Choices • Text data files • Spreadsheets • Database • GIS • Best for spatial data • Uses a relational database
It’s 4pm and you are somewhere near Granby, Colorado… Do you know where your data are?
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Data in Need of a Database • Data Characteristics • Large volume • Constant format • Need for sharing
Designing a Database Data Modeling • Identifying related entities • Sample locations, spatial extent, sampling methods, recorded data, data quality, topography… • Determining relationships between entities
Relationships CARDINALITY: Defines the numeric relationships between occurrences of the entities • One-to-One • (one member to one home address) • One-to-Many • (one region/state/province to many members) • Many-to-Many • (many members to many papers)
Other Examples • EPA • http://www.epa.gov/storet/
Other Examples • EPA • USGS Surface Water • http://waterdata.usgs.gov/nwis/sw
Other Examples • EPA • USGS Surface Water • Snotel • http://www.wrcc.dri.edu/snotel.html
Summary • Relational databases can be overkill for small data sets. • Relational databases are a good choice for large data sets with a consistent format, that need to be distributed to many users.
Acknowledgments • NASA-EOS • Mammoth MountainEnergy Balance Monitoring Sitehttp://neige.bren.ucsb.edu/mmsa/