Time Series Data / Overview

Time series data are used to analyze data trends over time and create visualizations. This documentation includes the following sections:

Time Series Background

Time series data in simple terms are lists of measurements or calculated values including:

  • timestamp
  • data value
  • data flag(s)

Additionally, a time series includes properties that describe the time series, including:

  • location identifier (for example, the station identifier)
  • data source (originating agency or system)
  • data type (for example Rain, Streamflow, WaterLevel).
  • missing data value
  • data units
  • data interval
  • other useful properties

Time series can have either "irregular" or "regular" data interval. Irregular time series correspond to data values that are reported or calculated at irregular times, such as event-driven data. Regular time series correspond to data values that are reported at a regular interval, such a every hour.

The timestamp for time series values adheres to the following conventions:

  • Instantaneous values have timestamp corresponding to the measurement time.
  • Accumulated, mean, or other values calculated over an interval, have a timestamp that corresponds to the end of the calculation interval, for example:
    • 15-minute data with timestamp ending in 15 means that value corresonds to the interval from minutes > 0 and <= 15.
    • Daily data values correspond to the day of the timestamp (time is irrelevant although some tools may show a time).

Time Series in NovaStar

Many time series in NovaStar are initially measured as raw sensor values, which are converted to engineering units, and may be further processed into derived values. For example water level may be measured using a pressure transducer sensor, converted into elevation or depth, and is further converted into an estimated flow value.

TODO smalers 2016-12-28 need to explain more about available data types and how to use the web service API