A Novel Micro-service Based Platform for Composition, Deployment and Execution of BDA Applications

Big Data are growing at an exponential rate and it becomes necessary the use of tools and technologies to manage, process and visualize them in order to extract value. In this paper a micro-service based platform is presented for the composition, deployment and execution of Big Data Analytics (BDA) application workflows in several domains and scenarios is presented. ALIDA is a result coming from previous research activities by ENGINEERING. It aims to achieve a unified platform that allows both BDA application developers and data analysts to interact with it. Developers will be able to register new BDA applications through the exposed API and/or through the web user interface. Data analysts will be able to use the BDA applications provided to create batch/stream workflows through a dashboard user interface to manipulate and subsequently visualize results from one or more sources. The platform also supports the auto-tuning of Big Data frameworks deployment properties to improve metrics for analytics application. ALIDA has been properly extended and integrated into a software solution for the analysis of large amounts of data from the avionic industries. A use case within this context is then presented.

A big data intelligence marketplace and secure analytics experimentation platform for the aviation industry

The unprecedented volume, diversity and richness of aviation data that can be acquired, generated, stored, and managed provides unique capabilities for the aviation-related industries and pertains value that remains to be unlocked with the adoption of the innovative Big Data Analytics technologies. Despite the large efforts and investments on research and innovation, the Big Data technologies introduce a number of challenges to its adopters. Besides the effective storage and access to the underlying big data, efficient data integration and data interoperability should be considered, while at the same time multiple data sources should be effectively combined by performing data exchange and data sharing between the different stakeholders. However, this reveals additional challenges for the crucial preservation of the information security of the collected data, the trusted and secure data exchange and data sharing, as well as the robust data access control. The current paper aims to introduce the ICARUS big data-enabled platform that aims provide a multi-sided platform that offers a novel aviation data and intelligence marketplace accompanied by a trusted and secure analytics workspace. It holistically handles the complete big data lifecycle from the data collection, data curation and data exploration to the data integration and data analysis of data originating from heterogeneous data sources with different velocity, variety and volume in a trusted and secure manner.

A Secure Experimentation Sandbox for the design and execution of trusted and secure analytics in the aviation domain

The aviation industry as well as the industries that benefit and are linked to it are ripe for innovation in the form of Big Data analytics. The number of available big data technologies is constantly growing, while at the same time the existing ones are rapidly evolving and empowered with new features. However, the Big Data era imposes the crucial challenge of how to effectively handle information security while managing massive and rapidly evolving data from heterogeneous data sources. While multiple technologies have emerged, there is a need to find a balance between multiple security requirements, privacy obligations, system performance and rapid dynamic analysis on large datasets. The current paper aims to introduce the ICARUS Secure Experimentation Sandbox of the ICARUS platform. The ICARUS platform aims to provide a big data-enabled platform that aspires to become an 'one-stop shop' for aviation data and intelligence marketplace that provides a trusted and secure 'sandboxed' analytics workspace, allowing the exploration, integration and deep analysis of original and derivative data in a trusted and fair manner. Towards this end, a Secure Experimentation Sandbox has been designed and integrated in the ICARUS platform offering, that enables the provisioning of a sophisticated environment that can completely guarantee the safety and confidentiality of data, allowing to any interested party to utilise the platform to conduct analytical experiments in closed-lab conditions.