A New Opportunity: Open Innovation for “Construction & Data Science”
The construction industry has been undergoing a digital transformation, with data science playing an increasingly important role in improving efficiency, reducing costs, and enhancing safety. However, to fully realize its potential, it’s essential to promote open innovation and collaboration between data scientists and construction experts.
For this purpose, the first open innovation workshop on “Construction & Data Science” was recently held in Zurich, Switzerland, bringing together 40 participants from both fields to explore the intersection of construction and data science.
To improve cooperation between the construction industry and data science, the workshop formulated central key findings:
- Focus on creating structured data sets across projects, teams, and companies and move away from managing data in CAD systems.
- Don’t wait for new standards to be defined, learn to combine information from different sources and standards by mapping it.
- Consider using other ways of pulling data from CAD tools, like Speckle or an IFC-based modeling tool like Blender.
- Engage in open source or open data projects and learn from others, especially in rapidly evolving technology.
Check out sites like www.opensource.construction/ to proactively work towards changing the status quo and improving the industry.
The summary is also nicely put together in the Linkedin post by opensource.construction’s President, Maximilian Vomhof.
The workshop aimed to identify potential problems and solutions in this area and to promote open innovation and collaboration between data scientists and construction experts. In this blog post, you will find a report on the insights gained from the workshop and highlight the importance of open innovation in these industries.
The workshop was organized jointly by opensource.construction, bauen digital Schweiz, and the data innovation alliance at Amstein + Walthert in Oerlikon. After a short introduction to the Databooster program, the passive part for the participants was over!
The workshop was structured according to the double diamond framework from design thinking, which consists of four stages: discover, define, develop, and deliver. After the four groups got to know each other, they explored the problem space at the intersection of construction and data science or data engineering. In this phase, the focus was on generating a wide range of ideas and potential solutions by asking “why” questions and understanding the workings of the construction industry as a data scientist – essentially, “falling in love” with the problem.
At this workshop, “love” was certainly in the air, with many questions generated. Of these, five problems were identified as most relevant:
- Optimized building scans
- Open-source door planning configurator
- Linked product data
- GIS data linked with building laws
- Open data environment for storing and linking element-independent information
In the second part of the workshop, powerful teams were formed around the ideas generated. They not only focused on potential solutions but also on related business cases, which added a practical, pragmatic dimension to the ideation process.
One of the solutions produced was standardization, particularly in the light of data formats. However, it was agreed that establishing standards and achieving consensus could take a long time – a luxury that the construction industry simply doesn’t have. It was essential to identify quick and effective solutions that could be implemented without major delay.
Despite the apero long being ready, the teams were still deeply engaged in finding innovative solutions that could be launched swiftly. The teams agreed to follow up on their ideas and continue pushing for change, possibly using the Innovation Booster Databooster, something we are particularly happy to hear.
In conclusion, we believe that the Innovation Booster Databooster initiative is a valuable resource for teams to develop and implement their solutions generated using the double diamond design thinking structure. We look forward to seeing how these ideas will shape the future of construction and data science!