The Property Data Lab

By standardizing the management of data and making it available for the development of AI-based and innovative digital services, the project aims to advance the real estate industry.

The goal of the Property Data Lab was to establish an ecosystem and create a national platform to share property data between actors in the real estate industry.

The purpose is to contribute to a more standardized way of managing data between different stakeholders and to make data available to those who wish to develop new innovative digital services based on AI and smart analysis algorithms.

The project started with about 20 participants but expanded to over a hundred participants in the ecosystem. An important objective of the data lab has been to establish common data models and APIs within the industry, which we have worked on successfully during the project, including with the RealEstateCore ontology. The project has also, together with several ecosystem participants, conducted advanced labs/hackathons with data from properties.

PROJECT SETUP AND EXECUTION
The project was carried out as planned, with a strong focus on establishing an active ecosystem in combination with several technical efforts (data models, platforms, sharing). At an early stage, however, we entered a pandemic that forced us to transition to a completely digital project, which changed the setup, especially for larger workshops and study visits that could no longer be held physically. However, we quickly adapted to running our working groups and workshops entirely digitally, and were also able to carry out several hands-on exercises.

EXPECTED LONG-TERM EFFECTS 
The result of the project is an established ecosystem with several active working groups within the real estate industry. The Property Data Lab has already contributed to several other innovation projects, including a UDI and another data lab.

Throughout the project period, a number of workshops and lab sessions were held where we trained and discussed information models (REC), platforms, and conducted hands-on exercises. Today, many commercial platform projects are underway at various organizations — we will continue to contribute to standardized data models and APIs.