Mathias Funk from Eindhoven University of Technology joins forces with 4TU.ResearchData to improve the FAIRness of design data.
Mathias Funk is an Associate Professor from the Department of Industrial Design at TU/e. As part of the Future Everyday group, his research explores the interplay between emerging technologies and designing for people’s everyday life.
Mathias is focussed on using data in design, and particularly, ‘data-enabled design’; an approach that involves the remote capture of data about user behaviours and preferences using sensors. Such contextual data can be used to inform and inspire the design process, and to create and validate design interventions.
Data in modern design
Mathias emphasises the importance of data in modern-day design and design research. “Our world is becoming increasingly more tech-driven. As humans become plugged-in to the ‘Internet of Things’ for their daily routine, there’s a growing demand for devices that can process and generate data in a highly sophisticated manner.”
“Such intelligent devices can have embedded sensors and capabilities to seamlessly exchange data with other devices and services. They may rely on complex algorithms that encode the relationship between inputs and outputs,” says Mathias.
He continues to explain that these devices remain a ‘black box’ for many. “Design students often consider artificial intelligence and machine learning to be like a form of magic sauce. They understand that interactive devices use and produce data, but what happens in between remains a mystery to them.”
There is a lack of understanding of how devices process data and what is possible when data is used in design. This is largely due to technological and methodological barriers in collecting, processing and representing data in a design, and the limited presence of FAIR data in design disciplines. Traditionally, design data is qualitative, difficult to scale-up and stored in proprietary ways meaning that data is inaccessible to the research community.
Shaping the future of design research
Determined to make a change, Mathias is developing Data Foundry with a small team at the Industrial Design department.
Data Foundry is an online infrastructure for prototyping and designing with data. Researchers can collect, store, process and export data from various remote devices in real-time.
Mathias hopes that Data Foundry will improve data literacy, the FAIRness of design data and help researchers to understand how intelligent devices interact with and through data.
“Data Foundry offers design researchers a unique opportunity to learn about remote data collection and processing beyond the low-scale qualitative,” explains Mathias. “Researchers can interact with their data as soon as it is captured and, therefore, gain a better understanding of a context or a designed experience.”
Mathias adds that Data Foundry also serves as a research data management system that helps to promote data reuse. “Data from a variety of sources is collected in a common, unified format using over ten different dataset types, and is described using metadata, making it easier for researchers to understand, combine and reuse each other’s data.”
He hopes that the unified infrastructure for data collection will encourage a transparent and collaborative way of working whereby students, educators and researchers build trust and develop creative ideas together.
A collaboration with 4TU.ResearchData
Since its inception in late 2018, Data Foundry has been piloted in various Industrial Design courses, including the Data-enabled Design Master’s degree course, and is to be part of the curriculum of upcoming courses on data, sensors, and machine learning.
Currently, Data Foundry supports more than 250 design projects at TU/e. Whilst infrastructure components still need to take the test of time, the next step is to ensure that finalised datasets from closed projects are transferred to a trusted data repository for their long-term preservation, access and sharing. Mathias has decided to join forces with 4TU.ResearchData to make this happen.
The objective is that once a project is closed in Data Foundry, its data and meta-data can be automatically imported to 4TU.ResearchData, an international repository that boasts more than 8,400 datasets in science, engineering and design disciplines. Datasets will be assigned a DOI and described using rich metadata to make them more accessible to the wider research community.
This year, technical team members from Data Foundry and 4TU.ResearchData will work towards establishing standards for interoperability between the two infrastructures so that the exchange of finalised data and metadata is easy, safe and efficient.
Mathias believes that many heads are better than one when it comes to shaping the future of design research.
There are thousands of flavours of FAIR data and it’s impossible to tackle them all working in isolation. With 4TU.ResearchData, a consortium initiative of three Dutch technical universities, we can capitalise on the strength and knowledge of many experts. Let’s see how we can share data and do more.
As the new year brings exciting prospects, we look forward to keeping you updated on the latest developments from Data Foundry and 4TU.ResearchData. If you’d like to learn more about this collaboration, get in touch. To learn more about Data Foundry, head to the documentation, use-cases and Development Blog. Or, see Mathias’s profile.
Written by Connie Clare (4TU.ResearchData)
Cover image illustrated by Connie Clare (4TU.ResearchData)