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Formatting Your Time Series Data

Formatting data to be published in the Hydrologic Information System is fundamental to the systems ability to effectively share data. For users who take advantage of CUAHSI's hosting services, guides and templates are available at Hydroserver.cuahsi.org once CUAHSI has set up a database for you. Users who wish to host their database on their own server should browse the HydroServer Suite documentation on the Legacy Tools page.

The specifics of Observations Data Model (ODM) are documented in the Water Resource Research paper, A Relational Model for Environmental and Water Resources Data and the ODM Design Specifications Document. Download the Data Formatting Template attached below and contact Help@cuahsi.org with any questions.

The Observations Data Model (ODM) is the underlying data structure for the data published through the CUAHSI HIS. The purpose for such a database is to enable data storage that optimizes data retrieval for integrated analysis of information collected by multiple investigators. A generalized diagram of this schema can be seen below. Fundamentally, the information model describes an observation as it relates to:

  1. Site: latitude and longitude
  2. Property measured: such as alkalinity or discharge
  3. Method: method used to make the measurement
  4. Source: the collecting agency
  5. Quality Control level: level of review of the data (the data can be in raw form)

The ODM is intended to provide a standard format to aid in the effective sharing of information between investigators and to allow analysis of information from disparate sources within a single study area or hydrologic observatory in addition to sources across hydrologic observatories and regions. The observations data model is designed to store hydrologic observations and sufficient ancillary information (metadata) about the data values to provide traceable heritage from raw measurements to usable information allowing them to be unambiguously interpreted and used. A relational database format is used to provide querying capability to allow data retrieval supporting diverse analyses.

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