Behavioural data is intrinsic to our digital world, enabled by the Internet and the Internet of Things. It is generated, collected, and stored as we navigate physical (e.g., public transport) and digital (e.g., social media) spaces. Hence, it offers a unique perspective of our behaviour and experience grounded across time and space. For this reason, HCI researchers increasingly integrate behavioural data into their human-centred and participatory processes.
However, there are three critical challenges to harnessing data effectively and responsibly in HCI research:
- First, there is a paradoxical abundance of data and an access scarcity. There is data about everything, yet researchers and people whose behaviour are captured in the data cannot meaningfully access it.
- Second, data is currently explored in isolation due to the silos it is captured from, the privacy-preserving processes it must comply with and the complexity arising from data trails. This keeps the focus on “thin” data, while much HCI research benefits from “thick” data.
- Finally, leveraging data as a boundary object to connect and collaborate still needs to be improved. This prevents tapping into the expertise of data participants, leveraging personal data with appropriate informed consent, and supporting meaningful and reciprocal exchanges of values.
Human-Centred Data-Centric Research aims to address these challenges at the intersection of Participatory Design and Data Science to support novel, effective and responsible use of behavioural data in HCI research. The field needs research on three axes:
First, the field needs to explore and develop new mechanisms to access data while eliminating the data consumption attitude of data-driven approaches. These mechanisms should empower stakeholders to leverage available data in collaboration with the relevant parties. Thus, questions to explore include: how can we rely on alternative ways to access behavioural data, such as citizen science, crowdsourcing, or data donation, to leverage existing data and diversify the availability of data material? How do these approaches fit and challenge existing data protection regulations and privacy considerations (e.g., the European General Data Protection Regulation)? What methods lead to a fair exchange of values and robust insights instead of research driven by data consumption? To what extent do these approaches reinforce or mitigate existing inequalities?
Second, the field needs tools to integrate data trails that combine multiple data streams into more comprehensive context mapping, ways of immersion to foster holistic reflections and pragmatic approaches to complement rather than replace design tools and practices. Large and small organisations alike are eager but need help integrating data in their human-centred design process to enhance the creativity and feasibility of envisioning design solutions. Thus, questions to explore include how data representations influence the design (processes) and stakeholder interactions. And how can the various data modalities and materiality support fair representation and participation with data?
Finally, the field needs data participatory tools and methods that engage, protect and credit all parties. When reporting our experiences with behavioural data, we often fail to shed light on the many hands involved in generating, collecting, storing, processing, analysing, and visualising the data. Bringing visibility to those involved throughout a data-centric process can better inform and support future HCI researchers engaging in similar activities. Thus, questions to explore include: What is beyond data privacy and open data? How to empower and foster value exchange through data? What are mechanisms and tools to facilitate data conversation at scale?
While I actively develop this field and its research agenda in collaboration with national and international collaborators, I shape my research agenda around my strength and assets as a researcher of the IDE faculty: the synergy between the human, technology, and interaction perspectives. How can researchers leverage and facilitate the use of data, and what value can it bring to data participants? Conversely, how can participants meaningfully engage with data, and what value can it bring to researchers? Through this 3-dimensional lens, I explore, develop, and assess data tools and participatory methods contributing to Human-Centred Data-Centric research. Thus, my research agenda involves three intertwined lines of research over the upcoming five years, contributing to addressing the field’s challenges.
- Line of Research 1: Human Perspective – Develop an alternative approach to using behavioural data in research, facilitating reciprocal participation supported by regulatory bodies. I aim to radically change the way human-centred research is conducted by experimenting with win-win, adequately informed partnerships. It will form a framework and guidelines for reciprocal participation through behavioural data.
- Line of Research 3: Interaction Perspective – Develop a set of human-data interactions which empower researchers and data participants to explore behavioural data collaboratively. Bringing data science to human-centred research requires moving away from data-consumption research and data-driven processes towards tangible, slower, meaningful conversations with all stakeholders revolving around behaviour data.
- Line of Research 2: Technology Perspective – Develop data tools that leverage technologies to embed behavioural data in human-centred research processes. It is critical to explore the behavioural data modalities of tomorrow to push the field forward. While the Human and Interaction perspective builds on already mature behavioural data, I explore technologies such as 360 videos and audio signals (e.g., ambient, voice assistant interaction) and biosignals to open avenues for integrating behavioural data into human-centred research processes.
Approach and Societal Relevance
These three lines of research rely on a Research through Design approach in which I iteratively prototype and test technology probes in-the-wild in collaboration with PhD and Master students, industry partners and citizens. Their synergy contributes to the Sustainable Development Goals by building participant-research partnerships, voluntary commitments and scientific capacity and capabilities (SDG 17) and opening opportunities for data literacy, access to knowledge and informed consent (SDG 4). I aim to explore the approach, the data tool and the set of human-data interactions to generate knowledge in three SDGs: good health and well-being (SDG 3), reduced inequalities (SDG 10), sustainable cities and communities (SDG 11) to generate empirical evidence within and across domains.
The primary audience of my work lies in the HCI and design community. The CHI and DIS are my default conference targets, while ToCHI and IJD are the relevant journal target. In 2022, I established the Data-Centric Delft Design Lab to create synergy between my research, teaching, organisation, and valorisation activities. The objective is to generate more visibility, establish a larger footprint in the Faculty and convert more graduation work into scientific output through better interest alignments.