A general conceptual framework for multi-dimensional spatio-temporal data sets

In the era of ubiquitous data collection and generation, demands are high to make these data accessible as widely as possible, with as little effort and as much power and flexibility as ever possible. On Earth data, this holds in particular for pixel data and point clouds, some of the main Big Data today. Coverages represent a unifying concept for space/time-varying data, especially for spatio-temporal gridded data, nowadays often called datacubes. Coverage standards exist, however, their fundaments appear in places technically outdated, imprecise, and not suitable for the full spectrum of data. Due to this lack there is a danger of missing interoperability goals and impeding future-directed Big Earth Data services. We introduce the conceptual coverage model of the forthcoming ISO 19123-1 standard. It is generic, supporting all spatio-temporal dimensions in a unified manner, and is compatible with the existing coverage implementation standards of OGC and ISO. We demonstrate feasibility through concrete service examples.

Automated summary

In the era of ubiquitous data collection and generation, demands are high to make these data accessible as widely as possible with as much power and flexibility as possible. The concept of coverages represent a unified way to handle space/time-varying data, but existing standards may be technically outdated and imprecise.