Characterizing Differences Across Time Series Datasets

Characterize the specific differences in characteristics across various time series datasets.

Background

Time series datasets from different domains (e.g., energy, economics, weather, and health) often exhibit distinct properties such as sampling frequency, periodicity, noise characteristics, and non-stationarity. Understanding these differences is crucial to building models that generalize across domains or are tailored effectively to domain-specific traits.

The authors explicitly defer a systematic treatment of these dataset-specific differences, identifying it as a concrete item for future work.