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I couldn't agree more, and I've talked to the folks at TimescaleDB about exactly this issue; it can be hard for folks familiar with the narrow definition to und

I couldn't agree more, and I've talked to the folks at TimescaleDB about exactly this issue; it can be hard for folks familiar with the narrow definition to understand how many more usecases a tool like Timescale can fit. More broadly I think this is an issue with a narrow definition of "time series", aside from the DB angle. When I was doing more forecasting and predictive modeling, I was constantly stymied by "time series" resources only considering univariate time series, where my problems were always extremely multivariate (and also rarely uniformly sampled...). When I've asked around for other vocabulary here, the options are slim. Panel data can work, but that has more to do with there being both a time and spatial dimension (e.g. group, cohort, user, etc.) than there being multiple metrics observed over time. It's also an unfamiliar term for data scientist folks without a traditional stats background. "Multivariate time series" might be technically correct, but that works much better in the modelling domain than the database domain.

jwatte 5y ago
I've found one source of vocabulary to come from research into the temporal relational algebra and temporal databases. For example: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.47.5437&rep=rep1&type=pdf https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.47... (This being a not fully settled / exploited area of computational science, there are plenty of alternative interpretations, too.) The main challenge here is that extending relational algebra ("key tuple maps to row") into time ("key tuple maps to function from time to row") essentially cross-products two different dimensions, creating a much bigger domain to process and reason about. Once you have the theory down, you can express some pretty handy relationships. For you functional folks, you can consider the TRA as the regular RA lifted into the time monad. Except the composition can also go cross-wise; TRA can also be considerd as the narrow timeline lifted into the relational monad. Fun times!

jwatte 5y ago

I've found one source of vocabulary to come from research into the temporal relational algebra and temporal databases. For example: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.47.5437&rep=rep1&type=pdf https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.47... (This being a not fully settled / exploited area of computational science, there are plenty of alternative interpretations, too.) The main challenge here is that extending relational algebra ("key tuple maps to row") into time ("key tuple maps to function from time to row") essentially cross-products two different dimensions, creating a much bigger domain to process and reason about. Once you have the theory down, you can express some pretty handy relationships. For you functional folks, you can consider the TRA as the regular RA lifted into the time monad. Except the composition can also go cross-wise; TRA can also be considerd as the narrow timeline lifted into the relational monad. Fun times!