Stare Towards Integrative Analysis with Minimized Data Wrangling Hassle
| Autor: | James Gallagher, Niklas Griessbaum, Michael L. Rilee, Kwo-Sen Kuo, James Frew |
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| Rok vydání: | 2020 |
| Předmět: |
Scheme (programming language)
010504 meteorology & atmospheric sciences Process (engineering) business.industry Search engine indexing Big data 010502 geochemistry & geophysics 01 natural sciences Data science Variety (cybernetics) Encoding (memory) Scalability business computer 0105 earth and related environmental sciences Data transmission computer.programming_language |
| Zdroj: | IGARSS |
| Popis: | Analysis incorporating geoscience data from different data sources entails dealing with their immense variety and volume. Until now, combining, for example, two or more different swath datasets from spaceborne observations has been a tedious, laborious process, limiting the scalability of potentially impactful integrative analyses. With the technologies developed in the NASA-funded SpatioTemporal Adaptive Resolution Encoding (STARE) project, we have made strides towards enabling scalable integrative analysis of diverse, voluminous geoscience data. Using STARE as a consistent geo-spatiotemporal indexing scheme to unify different data sources according to spatiotemporal colocation, spatiotemporal data co-alignment can thus be maintained on distrib-uted/parallel/Cloud resources to minimize costly and often unnecessary data transfer and communication, and to drastically improve scalability. |
| Databáze: | OpenAIRE |
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