Deliverable 5.8 iAOS Platform and Tools

• Main Authors: Caumont, Hervé, Schewe, Ingo, Ors, Fabien
• Format: Report
• Language: English
• Published: Zenodo 2020
• Subjects: Arctic; INTAROS; Observing Systems; Cloud Platform
• Online Access: https://doi.org/10.5281/zenodo.7244206

The “Integrated Arctic Observation System” (INTAROS) is a 5-year project funded by Horizon 2020 under the Blue Growth Programme. The overall objective of INTAROS is to build an efficient integrated Arctic Observation System (iAOS) by extending, improving and unifying existing systems in the different regions of the Arctic. Within INTAROS, WP5 (Data integration and management) is tasked with designing and implementing evolution of the cloud platform and tools for the iAOS. This document defines version 2 of the iAOS cloud platform and tools. The cloud platform has the objective to integrate multidisciplinary and distributed data repositories and provide a set of tools for data analysis, transformation and visualization. The cloud platform offers services to access observations and derived parameters, including the new observations from WP2-3-4. In addition, it offers seamless integration with geo-statistical methods for interpolation of spatiotemporal datasets, and services to store the generated datasets in iAOS enabled repositories The cloud platform offers scalable allocation of data storage and computer power for integrative data processing and analysis. Selected applications established in WP6 will use the services and tools provided by the platform, and thereby demonstrate the usefulness and functionality of the platform. These applications will showcase the benefit of enhanced integration of data from Arctic observing systems. Examples of services developed using the cloud platform are presented in D5.7. Processing Services for iAOS v1. The iAOS cloud platform provides tools to users with essential functionality for data discovery view, data download, data transformation (e.g. sub-setting, projection, interpolation), and facilitate for development and streamlining data processing workflows. The platform tools address the challenges of Big Data (Volume, Velocity, Variety, Veracity, Value). The cloud platform architecture is supported by a federated cloud infrastructure to facilitate the management of the ...