Learning Outcomes
Understand
- Human Data Interaction is one way of looking at the way people interact with and use technology.
- The role of data within Human Data Interaction
Remember
- Performativity
- Context Mapping
- Value Constellations
- Speculative Design
- Appropriation
Apply
Identify where studies and ideas sit within the Ablative Framework
Case Study: Personal Informatics
Li et al. (2010) describe five steps of self-tracking. In step 1, people prepare to collect data. For example, they buy an Apple iPhone because it will track their steps with the Health app, or download the Moves app. In step 2, people collect their data. With phone-based activity tracking, all one needs to do is to carry the phone at all times to measure steps. In step 3, people integrate their data. Some tools will do it for them, such as the Health app on the iPhone, or Moves. They then reflect on the data in stage 4, and may or may not take action (Stage 5).
- I. Li, A. Dey, and J. Forlizzi, “A stage-based model of personal informatics systems,” in Proceedings of the 28th international conference on Human factors in computing systems – CHI ’10, 2010, p. 557.
List of Difficult Sentences
“However, an increasing amount of data is personal. That is, because their preferences, attitudes and behaviour can be measured online in many ways, people nowadays generate lots of data, both consciously and unconsciously.”
“Performativity is a complex term that Dewsbury describes as “the gap, the rupture, the spacing that unfolds the next moment allowing change to happen.”
“By reversing the traditional ablative case in which ‘by’ is given agency, ‘with’ is co-produced and ‘from’ is taken, it is possible to express the shift in practices that designers have begun to develop as data moves from being something like a source to design ‘from’, to a complex and fluid setting to design ‘with’, and finally to a condition in which design is produced ‘by’ data itself.”
” It would be natural for levels of access to depend upon on the roles individual actors play with respect to collections of things. “
“The standard double diamond of design” -> Can be found here: Introduction to the Double Diamond by the Design Council
List of Difficult Concepts
Context Mapping: This refers quite simply to mapping out, analysing the context in which a service or a product is used. A list of relevant maps can be found on the Service Design Tools web site.
Performativity: The term as used in the paper comes from speech act theory. The Ling Space explains the ideas in this YouTube video. For example, marriage is a complex legal bond between two people (and indeed, two families). Marriage can be enacted through language (e.g., saying “I do”), or actions (e.g. hand fasting).
Speculative Design: This design idea looks towards the future – what will our world, our products, and our services look like in one, five, ten years? Envisioning the future is important, because what we design today may well have unintended implications tomorrow. This Speculative Design lecture discusses how technology can shape the future of cities. Speculative Design can also be found in good Science Fiction books, in particular near-future science fiction.
Value Constellations: The idea of a value constellation emphasises that value is subjective. This means that products and services need to be personalised, and that clients and companies negotiate value. An example from an industry blog is this piece by Aegis on car sharing; a useful example of a constellation graph for a vacuum cleaner hire company can be found on Vincenzo Musumeci’s blog.
Additional Useful Concept
Appropriation: When studying how people use products, you will often find them using things not as they were intended. This process is called appropriation, and this is something that you should explicitly make room for in your design, and you should be open to learning from appropriation.
One of the advantages of design by data is that anomalies in the data can point us to instances where an artefact has been appropriated for new uses.
Items for Discussion
- When is data a treasure, when is it a deluge?
- Can data ever be without moral/ethical or social/commercial value?
- How do we find out whether we’re getting it right?
- What is the difference between designing with data and designing by data?