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.
Highlights
Data-Cube cyber-infrastructures have gained a great deal of attention recently in the Satellite Imagery management domain
The DG Joint Research Centre (JRC) of the European Commission has recently developed a Data-Cube infrastructure based on the JRC Earth Observation Data and Processing Platform (JEODPP)5 to integrate and analyze the combination of satellite and in situ EO for the generation of a set of indicators relevant for the SDG (Sustainable Development Goals) 2030 Agenda (Soille, Burger, Rodriguez, Syrris, & Vasilev, 2017)
For the Digital Earth realm, it is possible to recognize a set of promising opportunities and specific challenges stemming from the introduction of Data-Cube solutions
Summary
Data-Cube cyber-infrastructures have gained a great deal of attention recently in the Satellite Imagery management domain. Data cubes (aka data hyper-cubes) have been introduced in the Business Intelligence domain in the 1990s, as a dimensional model approach to implement the Data Mart and Dashboard concepts and develop Data Warehouse architectures. In such a context, a Data-Cube infrastructure commonly refers to a cyber-system that manages at least a cube of data. In the database engineering and computer science disciplines, another term related to data cube is commonly utilized: the OLAP (Online Analytical Processing) cube This refers to a multidimensional array of data (Gray, Bosworth, Layman, & Pirahesh, 1996) ready to be analytically processed online (Dubler & Wilcox, 2002) using a well-defined computer-based technique to analyze data and look for insights.
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