This morning, I suggested an edit to a question to change "dataset" to "unbalanced panel data" in the title and add a tag.

Soon after, I found a question asking about longitudinal data, and found that we also have a tag in use.

These are related terms, but there's not much consensus about how related; you get different answers from different contexts. (Here's an example.)

There doesn't seem to be much interest in strictly defining these terms on Cross Validated (and I don't think we could even if we wanted to) -- but how do we want to categorize these questions?

(For what it's worth, I tend to think of "time series" as being specific to 2D cases where the dependent variable is the date or time an observation was made and use "panel" and "longitudinal" interchangeably to refer to the more general case with many dimensions.)

  • $\begingroup$ How about temporal-data? The term "temporal" is commonly used in pure sciences to describe events that are dependent on time or occur in a certain time order. $\endgroup$
    – asheeshr
    Commented Jun 21, 2014 at 1:32

3 Answers 3


For what it may be worth, I would have said is the most commonly used term for this. I have never heard myself. has come up but it seems far less used. And I would say I work in "data science". Hence my vote for favoring the tag. I might even go so far as to call all of them synonymous on this site, but, maybe best to wait and see if usage shows they differ.


+1 to Sean Owen's answer. I also favor the tag.

is a common term in macroeconomics. The connotation is one of multiple time series measured over the same time, with interactions between the different series (possibly with lags). Example: a country's GDP, industrial production and joblessness, or multiple countries' GDPs.

apply more generally: multiple time series that may or may not be measured over the same time period and may or may not interact. Examples: circadian cortisol dynamics, where cortisol of different patients will be measured over different days, and we wouldn't expect the cortisol levels of patient A over day X to influence the cortisol level of patient B over day Y.

So: all these terms have slightly different connotations, especially for people in different disciplines. I'd recommend keeping them all for now. But is definitely the most general tag, and anything tagged or should probably also be tagged .

(I personally do time series forecasting and have dealt with all three types of temporal data.)


Since no other proposals are forthcoming, here is one to consider:

  • Keep all three of the tags mentioned above, but make and synonyms. This will help users who search for one term by showing content tagged with either term.
  • Wait until there are more questions under these tags to characterize the distinction between these and .

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