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Exploring the depths of the global earth observation system of systems

Articolo
Data di Pubblicazione:
2017
Abstract:
Big Earth Data-Cube infrastructures are becoming more and more popular to provide Analysis Ready Data, especially for managing satellite time series. These infrastructures build on the concept of multidimensional data model (data hypercube) and are complex systems engaging different disciplines and expertise. For this reason, their interoperability capacity has become a challenge in the Global Change and Earth System science domains. To address this challenge, there is a pressing need in the community to reach a widely agreed definition of Data-Cube infrastructures and their key features. In this respect, a discussion has started recently about the definition of the possible facets characterizing a Data-Cube in the Earth Observation domain. This manuscript contributes to such debate by introducing a view-based model of Earth Data-Cube systems to design its infrastructural architecture and content schemas, with the final goal of enabling and facilitating interoperability. It introduces six modeling views, each of them is described according to: its main concerns, principal stakeholders, and possible patterns to be used. The manuscript considers the Business Intelligence experience with Data Warehouse and multidimensional "cubes" along with the more recent and analogous development in the Earth Observation domain, and puts forward a set of interoperability recommendations based on the modeling views.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Machine learning; GEOSS; data management; neural networks; word embedding
Elenco autori:
Nativi, Stefano; Santoro, Mattia
Autori di Ateneo:
NATIVI STEFANO
SANTORO MATTIA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/341267
Pubblicato in:
BIG EARTH DATA
Journal
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URL

http://www.tandfonline.com/doi/abs/10.1080/20964471.2017.1401284
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