Call for Participation

Crowdsourcing has become a valuable tool for subjective evaluation as it enables an easy and cost effective access to a large number of diverse users. However, for years the main focus of those evaluation lay on web-based application for PCs or laptops. On the contrary, crowdsensing and some citizen science approach already use the potential of the increasing number of mobile users, but mainly focus on collecting sensoric data from smart devices.

The summer school ‘Crowdsourcing and IoT‘ focuses on combining objective measurement data from mobile sensors, like smart devices or IoT devices, and subjective ratings. This enables assessing environmental factors in QoE studies and adding context information to sensor data measurements. The program of the summer school includes a general introduction in the research areas of crowdsourcing and mobile sensing. Best practices for subjective assessments will be given as well as selected Topics on IoT. The statistical evaluation of measurements and subjective user studies is taken into account.

The summer school takes place in Würzburg, Germany from July 31 to August 4th, 2017. The number of places is limited. Therefore, we encourage you to apply and register for the summer school as soon as possible: Registration.

Submission of and Extended Abstract

Students are encouraged to submit an extended abstract of maximal two pages describing their current research with respect to the topic of the summer school. Students who have submitted an extended abstract and present their own poster during the poster session will be confirmed an equivalent to 3 ECTS points load. Students who participate without abstract and poster presentation will be confirmed an equivalent to 1 ECTS point load. The number of places is limited and PhD students with abstract and poster presentation will have priority over other registrations. Submitted abstracts must be at most one pages long, including all figures, tables, references, appendices, etc. The extended abstracts must be formatted according to the ACM conference proceedings format.

The abstract is to be submitted via EDAS. Please, see the Registration page for further details.

Who can participate?

PhD students are welcome to participate in the summer school, especially when working in the field of quality assessment, subjective user studies, Internet of things, or crowdsourcing. Master students, post-docs, and researchers working in the same field are welcome to participate (upon availability).

Joint Group Work

The concept of this summer school is to form research groups of PhD students supervised by a tutor. Thereby, the PhD students will be grouped according to their research interests. Before the summer school, these groups will already start discussing about potential research questions and how to investigate them. A poster presentation of the groups’ ideas will take place during the summer school in order to foster collaboration and innovation between all groups.

During the summer school, the groups will get time to jointly research on their common topic with the support and help of the tutor. Crowdsourcing and IoT experiments may be conducted and the results analyzed statistically in order to investigate new and interesting research questions. In the end, this may result in a joint publication of the research group.

Application and Registration

  • The application for the summer school is now open and closes 31.06.2017 or if the maximum number of participants (30) is reached.
  • The participation in the summer school is free of charge.
  • The number of places is limited to 30 participants.
  • Group work: In order to find groups of researchers interested in the same topic and to do joint group work please prepare short document addressing the following questions.
    • Do you have any experience with crowdsourcing experiments, QoE studies or IoT?
    • What kind of crowdsourcing experiment or QoE study would you like to conduct?
    • What is your interest in IoT?

Please, see the Registration page for further details.