Notes on Seams, Seamfulness and Seamlessness

Posted: December 9th, 2006 | 1 Comment »

Notes on Seams, Seamfulness and Seamlessness (How designers can help users to exploit shortcomings of technology) taken by Antti Oulasvirta (User Experience Research Group, Helsinki Institute for Information Technology) at the Seamfulness Workshop on 17th of august 2004, at TeliaSonera Haninge. Antti summurizes the Seamful Design as an endeavour not to make everything seamful, but to aim for “seamless interaction but seamful technology“. This calls for solving the following problems:

  1. Understanding which seams are important. There are zillions of possible attributes of system/context/interaction/user that can potentially create a seam. We need to know which ones are important to users.
  2. Presenting seams to users. Presenting seams to users is a more traditional user interface design or information visualization problem than the two other.
  3. Designing interaction with seams. Especially, the question of how users are able to switch from the main task with the device to seams fluently is important.

Antti’s talk on SeamfulSystems: What are they and how can we design them? contains several very interesting thoughts and references (everyday life types of seams, Seamfulnessin 8 current approaches to ubicomp HCI, seams are part of the context, designing seamful systems is ultimately a UCD problem).

I really enjoy the physical example he uses to describe a “beautiful seam”.

 U Oulasvir Haninge Index Files Image001
A beautiful seam. Construction site at the Doge’s Palace in Venice is hidden behind a sheet that depicts how the building is going to look like after the construction is ready. With a little effort, an ugly seam (construction sites tend to be noisy, unsightly, and block pedestrians and cars) is turned into a one that can inspire passers-by to think and share opinions about how the palace is going to look like.

Relation to my thesis: My work aims at informing location-aware systems designers on ways to manage shortcomings of ubiquitous technologies. Unintentionally, my 3 sub-heuristics target the 3 points of the seamful design program in the context of location-aware systems as mentioned in my research plan:

Understanding which seams are important
the degree of positioning accuracy being appropriate to the task or activity at hand. In consequence, according to the activities supported by our location-aware system, how certain (accurate) do positional and tracking systems have to be in
order to be useful and acceptable?

Presenting seams to users
There is no comprehensive understanding of the parameters that influence successful uncertainty visualization. There is a need for a more systematic approach to understand the usability of uncertainty representation methods and interactive interfaces for using those representations. With our scope of ubiquitous computing we will investigate the visualization of spatial uncertainty in a real-time location-aware system.

Designing interaction with seams:
What is the balance between implicit and explicit forms of human interaction with a location-aware system. Therefore, according to the activities supported by our location-aware system, we can investigate interaction dynamics to communication uncertainty, and nurture usefulness of the system.

Finally, as inprired by Antti’s presentation, I would like to find more failed prototypes that could have benefited from an appropriate management of the technological shortcomings.
Failed Prototypes Seamfulness


One Comment on “Notes on Seams, Seamfulness and Seamlessness”

  1. 1 7.5th Floor » Blog Archive » An Environment Monitoring System as Element of Urban Life said at 2:38 pm on May 21st, 2009:

    [...] b) An imperfect mirror to reality A complete picture might be hard to achieve with incomplete environmental data patched together by data mining, filtering and visualization algorithms. In many ways we are limited to classic technical issues related to data resolution and heterogeneity. Even mobile sensors do not yet provide high-density sampling coverage over a wide area, limiting research to sense what is technically possible to sense with economical and social constraints. One set of solutions rely on the calibration of mathematical models with only a few sensors nodes and complementing data sources to create a set of spatial indicators. Another, approach aims at revealing instead of hiding the incompleteness of the data. Visualizing the uncertainty of spatial data is a recurrent theme in cartography and information visualization (see Approaches to Uncertainty Visualization). These uncertainty visualization techniques present data in such a manner that users are made aware of the degree of uncertainty in their data so as to make more informed analyses and decision. It is a strategy to promote the user appropriation of the information with an awareness of its limitations (see Notes on Seams, Seamfulness and Seamlessness). [...]