Data Stream Data Types

Scalar Data Streams

Scalar Data Streams are used to store scalar quantities that are fully described by a numerical value alone having a single variable per observed phenomenon. Examples of scalars are Temperature, Rainfall, Evapotranspiration, Sap Flow, etc. To ensure scalars are interpretable, units are crucial.

where,

• results : a list of results sent or subscribed to by Senaps, the below example contains
• t : Time in ISO 8601 Date-Time eg "2015-11-12T00:00:00.000Z"
• v : A dictionary of scalar values and it's identifying name or code eg "Temperature" : 1.0

{  
  "results" : [  
    {  
      "t" : "2015-11-12T00:00:00.000Z",  
      "v" : {  
        "Temperature" : 1.0  
      }  
    }  
  ]  
}

Scalar Data Streams are not limited to IoT sensor data and can be used to store any univariate time series data. A great example of this is pulling the BOM Forecast data (ADFD) for that given sensor, this can be visualized in the Eratos Viewer in tandem with the real recorded values on the ground.

Geolocation Data Streams

Geolocation Data Streams store geo-located trajectory information in the form of x, y, z coordinates and are typically used to store GPS data for example.

where,

• results : a list of results sent or subscribed to by Senaps, the below example contains
• t : Time in ISO 8601 Date-Time eg "2015-11-12T00:00:00.000Z"
• v : A dictionary of points (p) containing the longitude and latitude coordinates of the given sensor
• coordinates : Longitude, Latitude, Elevation

{
  "results" : [
    {
      "t": "2015-11-12T00:00:00.000Z",
      "v": {
        "p": {
          "type": "Point",
          "coordinates": [
            150.369105,
            -31.742179,
            415.8
          ]
        }
      }
    }
  ]

Vector Data Streams

Vector Data Streams, like Scalar Data Streams, store scalar values as a list and provide a way to store multiple time-aligned observations in a single multivariate time series.

where,

• results : a list of results sent or subscribed to by Senaps, the below example contains
• t : Time in ISO 8601 Date-Time eg "2015-11-12T00:00:00.000Z"
• v : A dictionary of vectors that contain lists of scalar values and it's identifying name or code eg "Temperature_vec" : [1.0, 2.0, 3.0, NULL, 5.0, 6.0, NULL, 8.0, 9.0, 10.0]

{
  "results" : [
    {
      "t" : "2015-11-12T00:00:00.000Z",
      "v" : {
        "Temperature_vec" : [1.0, 2.0, 3.0, NULL, 5.0, 6.0, NULL, 8.0, 9.0, 10.0]
      }
    }
  ]
}

Document Data Streams

Document Data Streams are a flexible Data Stream type that can contain Json documents or Strings.

where,

• results : a list of results sent or subscribed to by Senaps, the below example contains
• t : Time in ISO 8601 Date-Time eg "2015-11-12T00:00:00.000Z"
• v : A dictionary of json documents (j) or plain text strings (d) eg:
  "j" : {"a_key": "a_value"}
  "d" : "meaningful string"

{
  "results" : [
    {
      "t" : "2015-11-12T00:00:00.000Z",
      "v" : {
        "j" : {"Person_Count": 4,
              "Female_Count":3,
              "Male_Count":1},
        "d" : "This is the start of something amazing"
      }
    }
  ]
}

Image Data Streams

Image Data Streams are a Data Stream type that supports the following mime types:
"image/tiff", "image/jpeg" and "image/png". Furthermore, The image file must be Base64 encoded in the imageData property during upload, and retrieved as binary with mime type set for displaying on the web or saving to file for example.

where,

• results : a list of results sent or subscribed to by Senaps, the below example contains
• t : Time in ISO 8601 Date-Time eg "2015-11-12T00:00:00.000Z"
• v : A dictionary of mime types (m) and imageData Property (d)
• m: The image mime type: "image/tiff", "image/jpeg" and "image/png".
• d The imageData property that must be Base64 encoded

{
  "results": [{
    "t": "2018-01-03T00:00:00.000Z",
      "v": {
        "m": "image/jpeg",
        "d": "[insert base64 encoded image binary data here]"
      }
    }
  ]
}

Interpolation Type

The interpolation type for a Datastream is a standard metadata object that describes the statistical nature of the data within the stream. Operations can behave differently depending on the interpolation type.