In my everyday life, I engage with healthy food, eco-friendly behaviour and fair distribution of value.
I am fascinated by designers who have the power to make products, services and systems that support us towards these sustainable and societal challenges.
My passion lies in the endless possibilities of data, this digital trace that everyone leaves behind. By revealing the behaviour of individuals, groups and societies, data is a critical material to inform and assess design solutions to complex challenges. However, data is hard to leverage and raises ethical concerns.
At the intersection of Design and Human-Computer Interaction, I build tools that help designers use human behaviour data in their design process effectively and responsibly.
I define Data-Centric Design as a research field at the intersection of Data Science and Human-Centred Design. I hypothesise that the central use of behavioural data in Human-Centred Design can turn challenges and limitations of both fields into flourishing ethical and collaborative opportunities.
Let me first introduce my vision of education. Far too often, we place education in the second row behind research activities. It feels to me like completing an MSc before even starting the BSc. It also feels like missing opportunities to combine research and education as a way to strengthen both.
As a Teacher, I Learn
We have a lot to learn from our students. I see teaching as the best way to assess the new vocabulary of our research with BSc students and its implementation with MSc students. For instance, how can I work with MSc students to inspire and validate behavioural data in Design? How can I assess the framing of new activities while interacting with our Bachelor students, namely the place of data science and computational thinking in Design? We must be transparent about our activities: both students and teachers are here to develop new knowledge. As researchers, we are only more conscious that there is a lot we do not know. Therefore, it is critical to remove the gap between education and research, and more importantly, between students and researchers.
An example I use from autonomous learning is the continuous feedback and reflection loop. For each learning activity, each weekly module and each iteration of the course, I engage the students in reflecting on what they have learned and how they experienced it. In turn, I respond to this feedback by focusing on a misunderstood concept, applying students’ suggestions, or improving the course material. I am also transparent about my motivation and reasoning when I decide not to take action. It gives students agency and responsibility for their learning path.
As a Teacher, I Entertain
I believe in knowledge being accessible to everyone, and the Internet is a powerful tool to achieve this. Therefore, I thrive on open-source material in both education and research activities. All material we create must benefit beyond our cohorts of students to anyone eager to learn.
As a University, our strengths lie in empowering students to take ownership of their learning process rather than just consuming knowledge. Thus, as a teacher, I am an entertainer giving away energy, inspiration and enthusiasm to students who take their responsibilities and engage with interactive learning activities. This approach creates more room to work with students who want to engage, regardless of their backgrounds, special needs or other unique situations. In that regard, I am not afraid to try new learning activities and fail. It shows our students that we fail more often than they could imagine and that failure is an excellent way to build experience and move forward.
As a Teacher, I Create an Identity
Conducting scientific research that contributes to Design means that we grasp the future of this particular corner of the field. While we actively collect and build on student feedback, our scientific research should drive learning objectives and final attainment levels. It should give the colour, the distinction of our education compare to other schools and faculties of Design, naturally creating a diversity of profiles pairing with research progress.
Education is a beautiful collective challenge, continuously pushing us to understand and reflect on the diversity of the Design field inside our Faculty. Being a teacher means taking responsibility for the course we coordinate, but also for the whole programme. For example, I look forward to seeing our new Bachelor in motion and listening to the feedback from the students. I am also turning myself to a new construction site, the revision of our MSc education. I see ample room to sharpen our scientific research in collaboration with students.
I also stick to my core values when conducting scientific research: openness, inclusion and sustainability. I want to empower designers and users to work together towards design solutions that address societal challenges. While Human-Centred Design, Participatory Design, or Codesign foster collaborations between designers and users, I hypothesise that behavioural data is a critical facilitator in these design processes.
ethical and collaborative design activities with behavioural data
Behavioural data refers to data that represents the behaviour of individuals, groups and organisations. Such information is commonly used in the retail and web industry to analyse consumer behaviours and optimise businesses. In addition, the Internet of Things (IoT) captures behavioural data in the physical world. This data maps the dynamic behaviour of humans and objects in time and space. The term dynamic refers to asynchronous updates over time. Human data traditionally used in Design focuses on static information such as ergonomic or demographic data and qualitative data. Thus, the dynamic characteristic of behavioural data makes it novel in Design.
Imagine a world that empowers everyone to contribute to addressing societal challenges. A world where our society is an effective and responsible open laboratory.
On the one hand, the foundation of Human-Centred Design lies in democratic processes and a strong focus on user needs. However, digitalisation makes data a central part of this process. It creates concerns, tensions and frictions between the design solution and the use of data. On the other hand, designers cannot ignore the power of behavioural data to inform, drive and evaluate their Design. But doing so ethically and meaningfully requires close collaboration with users. As experts of their data, users provide critical insights on the problem at hand.
With Data-Centric Design, I aim to strengthen Human-Centred Design approaches while opening avenues for ethical use of behavioural data. I identify six types of activities – the verbs of Data-Centric Design in Human-Centred Design processes – that leverage behavioural data to foster ethical and collaborative practices.
Six Verbs for Data-Centric Design
In the following sections, I introduce the work of three PhD candidates conducting research to
Open with Data Donation,
Connect with Remote Presence and
Converse with Participatory Data Storytelling. Then, I expand on initial work to
Nurture along avenues to explore.
OPEN Designerly Data Donation
Imagine a world where designers collaborate with thousands of people generating behavioural data. For example, designers want to support people who menstruate. They articulate their aim and a list of behavioural data to get insights (e.g. menstruation apps, smartwatches). People who menstruate might already look for support through an app or track their activities for various reasons. Value exchange ranges from receiving novel insights through personalised analysis of their data to contributing to the design of something that could change their life.
Behavioural data captures the dynamic and intimate of people’s daily life. For designers, it is a rich source of insights as they search for clues to understand their design challenges and map the solution space. However, the use of personal data yields ethical concerns. Its use is often opaque for users, unfortunately, a data market in which they have no say.
How can designers use behavioural data as part of their design process in collaboration with people who understand and volunteer their data to a design cause?
To address this research question, Alejandra Gomez Ortega proposes the concept of Designerly Data Donation as a core proposition of her PhD research. We highlight the initial foundations for this framework in our UbiComp’21 SensiBlend Workshop paper. We announce data donation campaigns on our Data Donation Platform and offer graduation opportunities to develop new campaigns such as voice data donation and menstruation data donation.
CONNECT Designerly Remote Presence
Imagine a world where designers remotely immerse themselves into the behaviour of users. For example, how does it feel to be on the road all day, driving an electric cargo bike to deliver parcels? Designers receive timely, specific events by the behavioural data of users riding their bikes. They experience this presence through notifications or actions.
The GoodNight Lamp by Alexandra Deschamps-Sonsino
In this vision, the use of live data is explicit and move away from the traditional data science towards a critical need for designers: empathy.
How can behavioural data help designers develop empathy through live connection to the (inaccessible) wild?
Traditional data exploration methods are asynchronous, taking place after data collection. In contrast, a remote presence is live, allowing for timely reflections and impressions as the behaviour gets captured. This highly intimate process takes place in continuous collaboration with the data subject.
To realise this vision, Wo Meyer proposes the concept of Designerly Remote Presence.
CONVERSE Participatory Data Storytelling
Imagine a world where designers and users collaborate to develop rich and detailed data stories. These stories blend the skills of designers with the domain expertise of users. On the one hand, users offer context-specific information that ensures an appropriate interpretation of data. On the other hand, designers develop an awareness of data opportunities and limitations within the design context. Later on, data stories form reference points helping designers to reflect on their design solutions.
How can participatory data storytelling effectively turn behavioural data into a driver of design insights?
To realise this vision, Di Yan proposes the concept of Participatory Data Storytelling. It fosters collaborative analysis of data by engaging users in active conversation around data. This process makes behavioural data an accessible resource that balances the stakeholders’ roles in the design process.
PROJECT Participatory Data Analysis
Imagine a world where designers can develop rich views of a situation along with projections of potential futures. Then, users can reflect on the impact of these possible futures and raise issues, corrections or validation.
projection of potential washing maching use to maximise energy consumption from solar Photovoltaics
Users learn new insights from unique, deep analyses of their data and predictions of potential futures: what they can do and act upon to achieve their goals. In the example above, I present to householders an analysis of washing machine use. The visualisation shows how they used their washing machine (in red) and how they could have used it better (in green). In this context, better means to maximise the electricity production of their solar Photovoltaics.
What are the necessary tools for designers to leverage data science and machine learning to offer users tangible projections and alternative paths?
REALISE Open Design Platforms
Imagine a world where designers collaborate globally with many stakeholders through open-source live data prototypes. For example, a wheelchair augmented with sensors and cameras can support the design of innovative solutions at home, at work, on the go, for permanent and temporary users, etc. Building on and contributing to open-source hardware and software, the community generate valuable behavioural datasets while covering a wide range of context and challenges experienced by wheelchair users.
wheelchair prototype equiped with sensors, running on open-source code
Behavioural data open the way to a whole range of live data prototypes. These prototypes become critical for the design of feasible, viable and desirable design solutions. However, they are expensive and challenging to develop. In isolation, they do not generate enough data to yield significant insights nor machine learning input. Thus, collaboration is critical to unlocking their possibilities. For example, Nokia Bell Labs, a leading research institute, developed eSense: an earbud with extra sensorial capabilities. They offered this platform to research teams globally. It led to extensive research leveraging this prototype for a wide range of purposes and contexts.
How can open design platforms facilitates the generation and use of behavioural data at a global scale through live data prototypes?
NURTURE Data-Centric Design Communities
Imagine a world where designers behavioural data drive an open sharing economy. Uber and AirBnB have their open-source, decentralised and transparent counterparts. Users can easily trace their data and the decisions made by the platform. They can contest but also engage in the development of the upcoming updates.
A model for designing open sharing platforms
Behavioural data is the core of many data analytics processes and especially in sharing and circular economy models. Data analytics lead design and business decisions while remaining opaque and centralised from the user perspective. It leads to power imbalance with challenging choice to take part in the society or take care of one’s privacy. In our UbiComp’16 Paper, we offered a perspective on Open Sharing Economy as an iterative and open design process.
How can data-centric design communities nurture the development of open sharing platforms by blending ethical and collaborative practices with behavioural data in their design processes?
Degrees and Postgraduate Qualifications
- 2020 UTQ University Teaching Qualification, TU Delft (NL)
- 2016 PhD In Computer Science, The Open University (UK) / University of Rennes 1 (FR)
- 2012 MSc in Computing, Graduate School of Engineering, University of Rennes 1 (FR)
- 2018 – now Tenure-Track Assistant Professor, Delft University of Technology, NL
- 2016 (2 years) Postdoc Researcher, Delft University of Technology, NL
- 2014 (3 months) Commercial Intern, National Energy Foundation (NEF), UK
- 2012 (6 months) Research Intern, The Open University, Milton Keynes, UK
- 2011 (4 months) Research Intern, INRIA Rennes, France
- 2010 (3months) Research Intern, Sens-Innov, Rennes, France
- 2009 (5 months) Analyst and Development Intern, Axper Inc, Canada
- D-Code, fundamentals of Design Competence for our Digital Future [H2020 ITN 2021+]
- IoT Rapid Proto Lab, Erasmus+ project to explore the interdisciplinary teaching of IoT [2018-2021].
- Building rhythm [2020-2021]
- Bucket, a data platform for designers which facilitates Data-Driven Design prototyping.
- Responsible Internet of Things (IoT) Data Research [Funded by the Delft Design for Values Institute, 2019-2020]
- MK:Smart, integrated innovation and support programme leveraging large-scale city data to drive economic growth. [funded by the Higher Education Funding Council for England; 1 Jan 2014 – 30 June 2017].
- Energy Balanced Living, longitudinal energy data from citizens to inform the Design of human-centred electricity Demand-Shifting methods in the context of domestic electricity generation [funded by E.On & INRIA France; 1 Jan 2012 – Dec 31 2014, Principal Investigator].
- 2022 Design/Coordination -
BSc 1st yearDigital Product Development (IOB2-2)
- 2021 Design/Coordination –
BSc 1st yearSoftware-Based Products (IO1075)
- 2019-2020 Design/Coordination –
MSc ElectivePrototyping Connected Products (ID5415)
- 2018-2021 Lecture -
MScSmart System Technologies (ID4175 AED SST)
- 2019 Design/Coordination - Data-Driven Design Approach (2-week intervention as part of
BSc ElectiveDesigning for sustainability Transition)
- 2018 Coordination -
MSc ElectiveDeveloping Data-Driven Products (ID5452B)
- 2018 Lecture -
MSc ElectiveDesigning Data-Driven Products (ID5452A)
- 2017-2020 Lecture/Coach -
BSc ElectiveSoftware (IO3040)
- 2018-2019 Expert -
MScContext and Conceptualisation (ID4216)
- Guest lecture at TPM
- Interactive minor
- Lab talk RtD
- PowerWeb - Life after your PhD in a Scientific World
- Current - Honours Programme Master - Coordinator for students from the IPD Master
- Current - Data Champion
Current - PowerWeb Executive Committee
- 2013, 2014 Student Volunteer at UbiComp
- 2013 Travel Grant for UbiComp
- 2013 Internal Open University poster competition award
2011 Participated in 4L Trophy 2011, a humanitarian race in the Moroccan desert
- Reviewer: CHI 2016, CHI 2017, UbiComp 2016, IMWUT 2017, IoT 2016, TMCE 2017
- Languages: French (Native), English (Fluent), German (Beginner), Dutch (Beginner)