Numbers to physical variables: Mind to Reality workshop week
From May 2nd to May 6th 2016, Citizen Data Lab visited our colleagues at Density Design in Milan, to witness and assist in an experiment in dataphysicalization. 30 Design & Engineering students and 20 students from the MA Communication Design teamed up for a one-week hackathon organized by Monica Bordegoni and Michele Mauri at the makerspace of Politecnico di Milano. The objective was to create a working prototype for a domestic object that allows new tangible interactions with live, realtime data streams.
What is dataphysicalization?
Dataphysicalization, is data encoded into physical modalities (geometry, material properties or movement) making data tangible, and providing a multisensory, embodied experience of the data represented. Although not a new phenomenon, the physical representation of data has many contemporary appearances, such as pixel sculptures, object augmentation, wearable visualizations, data sculptures and interactive installations. As the structure and organization of our information evolves into more and more complex, linked and layered datasets, interdisciplinary design teams will have to keep finding ways to keep this data intelligible for human faculties. Interesting opportunities are emerging where current developments in digital fabrication, tangible interfaces and shape-changing displays intersect.
Beyond screens and LEDs
During this workshop week, students were free in choosing their datastream of choice (the design students all had experience working with digital methods). The makerspace was equipped and staffed to support the physical and electronic prototyping of the objects.
The most challenging aspect of this experiment was to coax the teams into thoroughly exploring how you can express and experience the data in a tangible way, relying as little as possible on visual cues such as displays or lights and instead experimenting with movement, taste, scent or other modalities. This requires a very iterative hands-on ideation and production process and a certain amount of material research. For designers who are used to designing for print or screens this can be quite a leap, but as the week unfolded the workspace got messier, sweatier and more physical indeed.
Results to build on
The 10 teams demonstrated working prototypes representing changes in live data about bank transactions, wind and tidal information, geo-location, twitter feeds, and activity on Spotify playlists . They experimented with an interesting array of physical variables apart from LED strips and RGB LEDs, such as: changing direction of dials, manipulating the flow of liquids, dropping balls from a pipe, moving origami and tilting surfaces. This video shows a weekly budgeting machine tracking your expenses (one ball for every euro per day) that one team made (see picture at top of post).
In instances where the datastream was rather singular (eg. “if it’s noisy in my garage, send a trigger”) the question arose whether we are dealing with data gathering, or sensing. Should we consider them to be one and the same? Or is it helpful to make a clear distinction? Where does the sensing system of inputs and outputs end and the dataphysicalization begin? Witnessing this process and getting into the literature sparked a lot of other ideas and questions for future work on dataphysicalization in the context of citizen empowerment:
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Jansen, Yvonne, et al. “Opportunities and challenges for data physicalization.” Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 2015.
Jansen, Yvonne, and Pierre Dragicevic. Data Physicalization Wiki. 2015. Web. 17 May 2016. <http://dataphys.org/>.
Jansen, Yvonne, and Pierre Dragicevic. “List of Physical Visualizations.” Data Physicalization Wiki. 2015. Web. 17 May 2016. <http://dataphys.org/list>.
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