Title: Time Series Cube Data Model,
Abstract: The purpose of this document is to create a data model and its serialization
for expressing generic time series data. Already existing IVOA data models are
reused as much as possible. The model is also made as generic as possible to be
open to new extensions but at the same time closed for modifications. This
enables maintaining interoperability throughout different versions of the data
model. We define the necessary building blocks for metadata discovery,
serialization of time series data and understanding it by clients. We present
several categories of time series science cases with examples of
implementation. We also take into account the most pressing topics for time
series providers like tracking original images for every individual point of a
light curve or time-derived axes like frequency for gravitational wave
analysis. The main motivation for the creation of a new model is to provide a
unified time series data publishing standard - not only for light curves but
also more generic time series data, e.g., radial velocity curves, power
spectra, hardness ratio, provenance linkage, etc. The flexibility is the most
crucial part of our model - we are not dependent on any physical domain or
frame models. While images or spectra are already stable and standardized
products, the time series related domains are still not completely evolved and
new ones will likely emerge in near future. That is why we need to keep models
like Time Series Cube DM independent of any underlying physical models. In our
opinion, this is the only correct and sustainable way for future development of
IVOA standards.