The next meeting of the Quantified Self Research Network will take place on the 25th March at the University of Warwick from 1pm to 6pm. It’s an informal seminar to present work in progress and is open to all.

If you would like to contribute then please send a short abstract and bio to by February 1st. We use ‘quantified self’ in a broad sense inclusive of self-tracking, wearable computing and digital augmentation

We’re also keen to build on the last seminar and move the discussion forward. Here are some of the key questions which emerged during the last meeting:

What is distinctive about qs?

People have tracked their health data for a long time such as keeping food diaries or measuring their weight. Is qs conceptually different to this or is it merely an automisation and intensification? Does the quantity of the data produced equate to more of the same or a qualitatively distinct phenomenon?

Are there inequalities in qs and self-tracking?

The technologies required for qs are usually quite expensive even for a basic device and would certainly be out of the range of disposable income for many people and…

Are we creating inequalities with the focus of research?

If qsers are a relatively privileged group while it may be interesting to understand their practices and development of individual and group identities there are other people who cannot afford these practices, are uninterested or simply unaware of them.

What about gender?

The QS community seems to have more men than women as active participants. What are the reasons for this? If we take the broader notion of qs suggested by some of the presenters then often the more “mundane” or “domestic” approaches to self-tracking are more associated with women? Is there something fundamentally different about these?

How do we identify a ‘non-user’?

Although some of the methods of tracking have been used for a long time some of them are very new and it is currently unclear what kind of uptake they will have. We fairly easily identify a user (agreeing on a definition may be more complex) it is more difficult to identify a non-user. Are they people who do not practice qs or use the devices because they do not have access to them, they are not aware of them or they simply do not care? Is it right to define people as non-users of a fairly niche activity often engaged in by relatively privileged people? But with the amount of data which is generated about us (often without us knowing) are we not all quantified whether we like it or not?