The Challenge

To optimise the cost-effectiveness of CO2-reduction projects, non-residential building-owners need to share relevant data more easily but safely with their project partners (such as consultants, construction and installation companies). Recent research (TNO, 2021) is showing that there is a growing gap between energy label predicted norm and the measured (real) energy consumption in practice.

Especially in developing more ambitious CO2-reduction projects, sharing complete and up-to-date data on measured energy consumption in relation to key construction features is a crucial success factor for optimising a maximum CO2-reduction per euro investment.

Data about the buildings, energy-label and measured energy-consumption are available from multiple sources. Within these 3 data-domains, data-formats are standardised. However, sharing data within and across these data-domains is not yet standardised. Data-providers are using different protocols for processing data-sharing requests, using different identification, authentication and authorization processes. Also, data-providers offer multiple data-exchange formats. This lack of standardisation and coordination, causes data-sharing to be relatively inefficient. The current market practice is prone to errors, for instance data being shared based on outdated or incorrect authorizations. Innovation is needed for Data Service Providers, Data Consumers and Entitled Parties to have better and more efficient checks on the trustworthiness of exchange data requests, based on clear access policies (data sovereignty).

The Solution

The Dataspace Measured Energy Consumption in Non-Residential Buildings (DMEC-NRB) objective is to eliminate the data-sharing barriers in the current market. The experiment will facilitate sharing of data using the standard NGSI-LD API to create digital twins. As explained earlier, developing more ambitious CO2-reduction projects for non-residential buildings increasingly requires complete and up-to-date data on the measured energy consumption in relation to key construction features. With this data, Data Service Consumers (such as installation companies and consultancy firms) can create digital twins of non-residential buildings, modelling the desired energy / CO2 reduction in various renovation scenarios for their clients (Entitled Parties). These digital twins are conditional to developing cost-effective CO2-reduction projects with reliable business-cases.

Business projections – scalability

480,000 non-residential buildings towards CO2-neutrality in 2050. ​​Dataspace management subsidised by Dutch government.