Data-driven generative design of personalized mementos

Bettina Nissen, Culture Lab, Newcastle University

Introduction

This position paper is touching on themes of personalisation, algorithmic design and the relationship between digital information and physical artefacts from a perspective of a product designer and with a view on the increasing accessibility of digital fabrication tools to wider audiences.

With a background in product design and only recently having joined the HCI research community, I am interested in exploring the changing role of professional product designers and the process of designing in this emergent era of digital fabrication technology. The design and fabrication of physical objects, which until recently was only accessible to specialist engineers and manufacturers have been opened up to a wider audience. The boundary between professional and amateur or between ‘designer’ and ‘user’ are being increasingly merged[1]. This enables non-specialist users to access, create and share 3-dimensional objects, shifting the focus from mass-production towards mass-customisation, from the design of products to the design of co-creation systems [14] and algorithmic frameworks allowing the user to generate their own personalized objects.

Miller argues that every object in a persons’ home (or the absence of objects) is an expression of themselves (individually or collectively); personal experiences are recalled and embodied in souvenirs and artefacts. Individuals tend to surround themselves with objects that mean something to them and express their lives, personalities or emotions [11]. Petrelli et al define such personal object as memento: “A memento is an object given or deliberately kept as reminder of a person, place or event.”[13] These mementos can take a number of different shapes or forms, from drawings and photographs to handmade or everyday objects, triggering very personal memories and stories.

There are numerous generative interfaces online today for the co-creation of personalised products, such as Nervous Systems[12], Fluid Forms[8], Cubify[5] and Supabold[17], but most of them are fairly limited in structure so that the user only has a finite amount of freedom to personalise and create a shape. This process of algorithmic or generative design is the development of a set of mathematical rules that create various unique programmatically generated outcomes of “artworks, three-dimensional forms or architectural propositions”[10].

Research into generative design and co-creation has mainly focused on the design of systems that let users change the shape of the object to personalise it. This research however is developing the idea of co-creation a step further to generate shapes from captured data which is inherently personal and not reproducible (almost like a fingerprint) before the user can access the shape to customise it further. I hypothesise that this additional level of personalisation incorporated into the design process will create a stronger emotional attachment to an object. Creating mementos as physical manifestations of a temporary experience will be explored through capture, visualisation and personal fabrication tools.

The following case study is an initial idea or work in progress of how data can inform the design and co-creation of objects and incorporate experiential meaning.

Case study: ~Flow

“~Flow is a tidemill – a floating building on the River Tyne that generates its own power using a tidal waterwheel. The onboard instruments respond to the constantly changing environment of the river, generating sound and data.” Flowmill [6]

The Flowmill project was developed as part of the Cultural Olympiad by the artists Ed Carter and Owl Project for the local community as well as international visitors in Newcastle upon Tyne. (Fig. 1)

Figure 1: The Flowmill project (exterior), image credit: ~Flow

Sensors on board of the tidemill were measuring the river’s environment, such as acidity, oxygen, nitrates, salinity and turbidity every 30 minutes (Fig. 2). This data was then used by arduino driven musical instruments that visitors could engage with to experience both the river and sound in a different way.

Figure 2: The Flowmill’s interactive sound instruments (left) and measuring devices (right)

In order to invite other artists, designers, creatives to engage with the data that was collected and broaden the experience for the visitors the artists made the collected data available online through Cosm [7], a platform for sharing and exchanging data[4]. Below is an example of the 5 data streams combined into one diagram (Fig.3).

Figure 3: Combination of all data streams published on Cosm [7]

With my background in product design I explored the possibility of using these data streams to create objects based on temporal change of data. The 5 data streams were used as driving dimensions for the shape of an object. To create a conceptual connection to the river, flow and its data, a vase was chosen as basis for the design of an object. A CAD model was developed of a basic vase shape with its dimensions (diameters and heights) based on the river’s data (Fig.4).

                  

Figure 4: Basic, data-driven vase shape and initial CAD model (as animated gif)

The physical manifestation of this temporary information is a form of capturing the experience with each shape representing a different moment in time (Fig.5) and its environmental data as a driving force behind the object.

Figure 5: Data-driven CAD designs

The different CAD generated models were 3D printed in different materials (Fig.6), through printing services such as Shapeways [16], to compare material qualities. Although new materials for digital fabrication are constantly developed and the quality of materials changes rapidly the currently accessible materials are still of lesser industrial quality than traditional materials and manufacturing techniques. The most suitable material for this instance was 3D printed ceramic which was glazed to make this material food safe as well as water resistant which was essential for this design.

Figure 6: 3D printed prototypes on Makerbot (left) in SLS nylon (right) and ceramic (far right)

Discussion and further developments

These initial prototypes are in the early stages of the development and an interface has not yet been developed. The development of an online interface is the next step. The main feature is the incorporation of different data streams from websites such as Cosm[4] so that the user can copy their data API into the interface to change the input for the generated object as well as then customise the shape, surface or structure further. The object can then be sent to a printer directly, uploaded to a 3d printing service, like sculpteo[15], shapeways[16] or imaterialise[9], or shared via online platforms such asthingiverse[18] or social networking sites.

The potential of designing objects that are inherently driven by one’s own data or information will create more meaningful mementos and therefore create products with longevity. The vast data that is gathered and captured every day could be used to generate a new type of object. Spatial, environmental or social data are only a few examples of what possible data streams could be used to develop these mementos.

By incorporating ones personal information into the design of the object a more meaningful personalised artefact can be developed. The digital interfaces for this personalisation process to generate significant mementos are an important part of the design process.

There is also potential to not only create online interfaces but develop meaningful mobile apps that relate to spatial, architectural or environmental experiences. Developments into the creation of 3D objects through mobile devices [2,3] has only been explored more recently but similar to the online interfaces, the systems don’t yet respond to personal or spatial experiences which holds a lot of potential for future explorations.

References

[1] Atkinson, P., 2010. Boundaries? What Boundaries? The Crisis of Design in a Post-Professional Era. The Design Journal, 13(2), p.19.

[2] Blown by Geoffrey Mann https://itunes.apple.com/gb/app/blown/id524313178?mt=8&ign-mpt=uo%3D2 (accessed on 15th January 2013)

[3] Chihuly App https://itunes.apple.com/us/app/the-chihuly-app/id572960717?mt=8 (accessed on 15th January 2013)

[4] Cosm (formerly Pachube) www.cosm.com (accessed on 15th January 2013)

[5] Cubify www.cubify.com (accessed on 15th January 2013)

[6] Flowmill www.flowmill.org

[7] Flowmill data on Cosm: https://cosm.com/feeds/46386?pachube_redirect=true (accessed on 30th August 2012)

[8] Fluid Forms www.fluid-forms.com (accessed on 15th January 2013)

[9] imaterialise www.i.materialise.com (accessed on 15th January 2013)

[10] Marshall, J., Unver, E. & Atkinson, P., 2007. AutoMAKE: Generative systems, digital manufacture and craft production. p.2

[11] Miller, D., 2008. The Comfort of Things, Polity Press, Durham.

[12] Nervous Systems www.n-e-r-v-o-u-s.com (accessed on 15th January 2013)

[13] Petrelli, D., Whittaker, S. & Brockmeier, J., 2008. AutoTopography: what can physical mementos tell us about digital memories? CHI’08 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems pp.53–62.

[14] Sanders, E.B.-N. & Stappers, P.J., 2008. Co-creation and the new landscapes of design. CoDesign, 4(1), pp.5–18.

[15] Sculpteo www.sculpteo.com (accessed on 15th January 2013)

[16] Shapeways www.shapeways.com (accessed on 15th January 2013)

[17] Supabold (Fluid Vase) http://www.supabold.com (accessed on 15th January 2013)

[18] Thingiverse www.thingiverse.com (accessed on 15th January 2013)