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The temporal feature integrated temporal attributes into Odysseus. These can be useful to predict unknown or future values of an attribute that develops over time. The temporal feature brings a complete semantics for temporal processing and is the foundation for spatio-temporal processing in Odysseus. The temporal feature is closely related to the moving object algebra by Güting et al.

Temporal Attributes

Temporal attributes are attributes that not only have one value, but one value for each point in time for a certain time interval. In other words, a temporal attribute of a certain type is a function that for each point in time returns a value of its type. Take a temporal integer over the interval [0,5) as an example. It could be the function f(t) = 5 * t. Then, it has five values, one for each point in the time interval: 0→ 0, 1→ 5, 2→ 10, 3→ 15, 4→ 20.

Internally, for Odysseus, a temporal attribute looks just like a non-temporal attribute. For example, a temporal integer looks like an integer for Odysseus. Nevertheless, the temporal feature tricks Odysseus a little bit at this point. While the type in the schema stays an integer, the actual value is not an integer but a temporal integer. In the schema, a temporal attribute can be detected in the constraints, which is a key-value field each attribute has. Here, temporal is set to true.

Prediction Time Interval and Bitemporal Streams

The previously mentioned time interval for which a temporal attribute has the values is the Prediction Time Interval. It is an additional time interval in the metadata of a stream element next to the normal stream time interval. It needs to be activated in the metadata definition of a query:

metaattribute = ['TimeInterval',  'PredictionTimes'],

As you can see, the metadata is called PredictionTimes. That is because in fact the metadata holds a list of non-overlapping time intervals. That is due to the algebra behind this approach and is explained later on.

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