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...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2021-09, Vol.143, p.105096, Article 105096
1. Verfasser: Baumann, Peter
Format: Artikel
Sprache:eng
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Zusammenfassung: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 Coverage standards exist, however, their fundaments appear in places technically outdated, imprecise, and not suitable for the full spectrum of data.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. •A unifying model for spatio-temporal coverages, i.e.: regular and irregular grids, point clouds, and general meshes.•Scientific underpinning of candidate standard ISO 19123-1 Coverage Fundamentals.•Foundation for spatio-temporal coverage services, such as OGC Web Coverage Service (WCS) and Web Coverage Processing Service (WCPS).
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2021.105096