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01.09.2022

Big Data, AI and IoT Reference Architecture: The BD4NRG case

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BD4NRG reference architecture for big data driven energy applications 

With the release of the final BD4NRG Reference Architecture, we happily present the latest updates for the BD4NRG architectural model spanning the entire scope of the project, harmonising existing approaches in the field, and integrating the needs of the energy value chain. It is also connected to considerations of interoperability and security issues.  

The structure of the BD4NRG reference architecture is based on the layers of the BRIDGE RA, fitted to the project’s requirements and including concepts from other approaches such as IDSA, GAIA-X and FIWARE. In addition to the four main layers, it includes a pillar including aspects which are relevant throughout the entire system. 

The Data Sources Layer focuses on identifying and understanding the Big Data provided by numerous sources, including energy sensors and meters, data monitoring and acquisition platforms such as SCADA systems or Building Energy Management systems, databases, platforms and cross-domain information such as environmental information. Essentially, this layer includes all the data generating hardware, applications and platforms as described in the Component Layer of the BRIDGE architecture. 

The Data Interoperability Layer focuses on identifying the communication interfaces with the data sources and corresponding data formats, as well as on providing a set of data and information models which could be followed or used for data transformation, aiming to ensure interoperable data exchange and use. This layer integrates the “Communication” and “Information” layers of the BRIDGE architecture.  

The Functional Layer includes two sublayers: the “Innovative Data Analytics Toolbox” sublayer, complemented by a “Marketplace” sublayer above it. “Innovative Data Analytics Toolbox” includes the different analytics functionalities being developed within the BD4NRG project, which will be traded via the marketplace. The “Marketplace” sublayer provides the interface between the functionalities provided by BD4NRG and the “Business Actors & Ecosystems” using it. This includes taking care of tasks like Smart Contracts, Transaction Tracking, and Facilitating Payment. The sublayer is split into “User Functionalities” for the platform’s participants to directly interface with, and “Governance Functionalities” providing support for the Marketplace itself.  

The Business Actors and Ecosystems Layer identifies stakeholders who participate in the data analytics ecosystem and corresponding energy data spaces. They include data providers and analytics services users / data consumers, analytics applications providers and providers of data space enablers and related platforms. Note that an organization or business role in the energy ecosystem can have one or more roles in data space, for example a TSO can be a data provider and a consumer of analytics services at the same time.  

The Reference Architecture’s right-hand-side pillar contains three sections, all stretching across the whole system.  “Data Space Governance” requires agreements to be established among Business Actors & Stakeholders. “Data Sovereignty & Trust” is supported by necessary tasks such as Identity Management or Data Provenance, as well as concrete modules such as a Vocabulary Hub and a Metadata Broker, covering the integration of FIWARE and IDSA. Finally, three “Data Space Levels” (Cloud / Edge / Fog) are named, which may apply differently to different parts of the system. 

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