DigiBUILD project


O1. To introduce an innovative stakeholder inclusion framework for co-creating and co-design use cases.

DigiBUILD will leverage the European Bauhaus initiative, aiming to demonstrate how data, models and analytic services in the building sector offers tangible, positive experiences in our daily life. Focus is on putting people first in developing technology.

O2. To increase the data quality along the data life-cycle by creating a federated Data Lake with enriched dynamic data with embedded Building Business Intelligence.

A federated Data Lake will be created to improve the different data quality dimensions.

A dynamic data repository will be the core of the Data Lake where timeseries and contextual building data will be merged by using standard Data Models, semantics and ontologies. By merging multiple and heterogeneous data from buildings, Business Intelligence analytics will be developed through the concept of Data Marts to obtain more relevant data.

To guarantee the security and privacy in the data gathering process at field level, blockchain and DTL technologies will be deployed to address trustworthy, safety and security requirements.

O3. To establish the grounds for an Energy Efficient Building Data Space.

DigiBUILD will use a federated Data Lake, building linked data and Building Business Intelligence to encourage the development of the emerging Data Space and translate the cross-sector IDSA (International Data Space) architecture into GAIA-X technological connectors, towards a decentralised sovereignty preserving data management.

O4. To increase interoperability by leveraging standards-based Data Models.

Three levels of interoperability (southbound, northbound and semantic interoperability) will be reached by leveraging and harmonising a number of ongoing semantic interoperability and standardisation efforts. Through their combination and integration, a minimal set of interoperability specifications and open standardisable interfaces will be deployed to facilitate building-centred data exchange.

O5. To deploy AI-based data analytic services for high-quality data-driven energy management, energy efficient buildings and comfort.

DigiBUILD will deploy AI-based services for high-quality data-driven energy management, energy-efficient buildings and IEQ, based on the static / dynamic data and enriched with semantic information (i.e. metadata), as well as to support policy making and effective implementation of EU policies.

DigiBUILD will adapt recent comfort and well-being measurement technologies to increase monitoring performance and ability to predict human preferences.

O6. To deploy system-level reusable, configurable, interoperable Digital Building Twins for better-informed planning of building infrastructure and investment decision-making for designing future buildings and building processes.

DigiBUILD will deploy Digital Building Twins, as a common semantic data representation that runs on the edge/cloud, aimed to support the design, construction, operation & maintenance, refurbishment and decommissioning phases.

O7. To demonstrate and validate the DigiBUILD applicability, effectiveness and value for the monitoring of the building stock performance along a variety of real-life pilots.

DigiBUILD will deploy, demonstrate and validate from environmental, economic and social perspective, the proposed reference framework and the underlying technologies of TRL-8 along 9 pilots and 10 real-life use cases, in 3 pilot clusters (see Demonstration actions).

O8. To develop and validate people-powered data collaboratives and sharing-economy business models, as well as to make data accessible to everyone with data democratisation, supporting the related EU initiatives.

DigiBUILD will leverage the piloted technological achievements and the respective business validation to nurture a high-level durable many-fold impact.

DigiBUILD will define all stakeholders involved in the building value chain, and carefully design and plan dissemination, communication and industrial clustering activities, tailoring information to each stakeholder category based on the information needs of each, and the level of involvement.

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