Would storing time series data in a Knowledge Graph be a good idea ? What could be the benefits of doing so ?
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It depends on the queries you want to do on the time series data, but I suspect the answer is NO.
Typical queries on time series data include the following:
- moving averages; e.g. 30 day average of stock prices
- median
- accounting functions; e.g. average growth rate, amortization, internal rate of return and so on.
- statistical functions; e.g. autocorrelation, and correlation between two series.
- pattern finding; i.e. find a time series (or multiple time series) that has a similar pattern to this time series
In general time series data have a greater need for aggregation of a collection of data rather creating a graph of the data. This will likely cause any time series related queries to have poor performance on a graph like database.
A factor to consider is that the amount of data stored for time series can be way bigger than that for of a typical knowledge graph depending on the sample rate of the time series data.
Here are some of the references that brought me to this conclusion:

Henriette Harmse
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