Tag Archives: mood tracking

Mobile MoodMap for iOS and Android Published

My Know-Center team “Ubiquitous Personal Computing ” just published the mobile MoodMap App for iOS and Android:

The Apps were developed by Peter Marton initially as a technical study of the the cross-platform development Titanium. Since this worked out fine overall – voilà two Apps!

Use the Apps to:

  • Express your mood in colours
  • Tag your mood: What happened in that instant? What are your (private) comments?
  • Visualise: Have a look at your own mood over time, and at the mood of the team around you.
  • React: It is up to you to react to mood changes. If things are going well: Enjoy! If things are not: Re-think the way you are communicating and working.

The mobile MoodMap App was developed in the context of the MIRROR EU project on reflective learning at work, based on the web-based, collaborative MoodMap App developed within MIRROR. We experimented with mood-tracking at work in order to identify things that go well and things that do not – with the goal to improve work practice of course.

Related publications (based on the collaborative MoodMap App) are:

Mood in the City – Urban Location-Based Mood Tracking

I am currently brainstorming around the topic of urban location-based mood tracking.

The starting point for this brainstorming was our work on collaborative mood tracking for the purpose of workplace learning in the context of the EU IP MIRROR (FP7). I followed up on this idea together with Anna Weber in a discussion paper that got accepted at the Smart City Learning WS @ ECTEL 2014 in Graz. Both our paper and the slides (presented by Jörg Simon as both Anna and myself were finally unavailable – thanks!) are available from the WS. site.

I repeat the abstract here, in the hope that it represents well the core idea and leads interested people to read the whole paper (only 4 pages after all…)

In the paper we discuss urban location-related mood self-tracking with respect to interaction design and benefits of use. The design of the interaction workflow in conjunction with software architecture needs to consider in which way mood data will be gathered, stored, shared and represented. Interaction and collected information could serve for single citizens to become aware of one’s own and others’ mood in relation to public spaces. From this viewpoint, the proposed system could serve citizens to learn about themselves in relation to a smart, in the sense of ‘technologically enhanced’, city. Additionally, collected information could be useful to trigger reflection on city-level in terms of viewing the city as socio-technical system. In this sense the proposed system could serve city government to learn about city design by collecting data from its most central constituent: the people visiting, living or working in a city.