#12 Earth Datacubes: Concepts. Standards, Services
Datacubes are emerging in Earth science as an enabling paradigm for offering massive spatio-temporal Earth data in an analysis-(and visualization-) ready way by combining individual files into single, homogenized objects, thereby easing access, extraction, analysis, and fusion. Essentially, datacubes unify spatio-temporal sensor, image (timeseries, simulation, and statistics da ta under a common modelling and servicing paradigm, independent from the variety of raster encodings utilized. Also, the datacube paradigm serves to homogenize across dimensions, allowing unified wrangling of 1 -D sensor data, 2-D imagery, 3-D x/y/t image timeseries and x/y/z geophysics voxel data, and 4-D x/y/z/t climate and weather data. On the side, there is a close relationship to statistical datacubes as common in OL AP, for example. In OGC and ISO standardization, coverages provide the unifying concept for spatio-temporal datacubes, with the streamlined service model of Web Coverage Service (WCS) including Web Coverage Processing Service (WCPS), OGC’s geo datacube analytics language. A large, continuously growing number of open – source and proprietary tools support the coverage standards. In parallel, in 2019 the SQL standard has been enhanced with datacube functionality. In this comprehensive tutorial, which is suitable for newcomers and remote sensing experts alike, we present the concept of datacubes and their contribution to analysis-ready data mentioning, e.g., the CARD4L initiative, relevant standards established in various bodies, as well as interoperability successes and issues existing. We inspect implementations and discuss their individual shortfalls and benefits. Based on the OGC reference implementation, rasdaman, live demos accessing existing services and reallife examples which participants can recap and modify on their Internet-connected laptop will play a key role. Slides will be made available to participants, including extensive link lists.
Introduction to datacubes: concepts, benefits
Datacube standards in OGC, ISO, INSPIRE
OGC / ISO Coverage data & service model
Getting hands dirty: how to model common raster types as coverages
Datacube technology survey
Datacube architecture deep dive: the OGC datacube reference implementation, rasdaman Outlook: Spatio-temporal Machine Learning boosted by datacubes
Wrap-Up & discussion
Half day or full day
Expected Target Audience and Number:
We expect about 40 participants, stemming from diverse areas:
Students who want to get a glance at latest developments in Earth science service technology Experts in remote sensing who want to keep abreast of recent developments
Data providers seeking to enhance the quality of their o fferings to better serve existing and attract new users, based on open standards
Service developers seeking guidance on the implementation of standards
Scientists seeking more efficient and less time consuming methods of understanding Big Data
After this workshop, participants will be able to:
Describe the concept of spatio-temporal datacube services and their added value for data providers and users.
Correlate the terms homogenized data, analysis -ready data, and datacubes.
Summarize the state of standardization in datacubes, centered around the notion of spatio- temporal coverages
Model common raster data types as coverages
Formulate common datacube tasks as OGC WCS / WCPS requests
Understand core implementation considerations for achieving flexibility and scalability, and differences between various datacube engines
Interact with sample standards-based datacube services in 1-D through 4-D scenarios.