The Second International Workshop on Ubiquitous Crowdsourcing in conjunction with the 13th ACM International Conference on Ubiquitous Computing: Beijing, China September 17-21st, 2011
With the adoption of mobile, digital and social media, networked crowds are reporting and acting upon events in smart environments. Existing platforms for crowdsourcing support specific types of activities, such as microtasks on Amazon Mechanical Turk, yet they fall short in facilitating general mechanisms that easily set up and maintain crowd networks, in a flexible manner and in a variety of domains. Building upon the First International Workshop on Ubiquitous Crowdsourcing, in this edition researchers and practitioners are being challenged to identify requirements for a platform for crowd computing, arising from experiences in deployment of crowdsourcing applications, which engage crowd members as sensors, controllers and actuators in smart cities and environments.
This workshop will bring together researchers to produce a vision for the universal crowdsourcing platform, documenting it in a theme publication. In addition, following the workshop, accepted workshop papers will be shaped as chapters for a book on “Scientific Foundations of a Crowd Computing Platform.”
The Workshop focus is on understanding requirements for supporting crowdsourcing applications in the context of the platform for crowd computing. The workshop facilitators are interested in exploring the way the crowdsourcing taxonomy (e.g. task complexity, duration, etc.) drives the requirements for the infrastructure. Submissions from both the industry and academia are encouraged. Some of the key application domains of interest include disaster management, maintenance, and healthcare domains.
Specific topics of interest include:
- Crowds as Sensors. In many scenarios, crowd members report various aspects of the physical world. They take the role of sensors. How do we build systems to capture this role of a crowd, in addition to its participants being actuators and controllers?
- Crowds as Networks. When dealing with situations such as disaster management, we can model geographically co-located people as networks. The emerging field of network science will be useful for answering several interesting questions related to community detection, expertise identification, and routing communication.
- Quality Assurance. How is crowdsourcing going to face the challenges of quality assurance, while providing valuable incentive frameworks that enable honest contributions? An important consideration is the impact of QA on the cost of the crowdsourcing solution. For example, in the low-cost disaster environments when crowdsourcing is introduced to masses of volunteers, one needs to control the cost arising from the quality and trust mechanisms.
- Incentives. Incentives are a key to success or failure of the crowdsourcing activity. How do can you differentiate between the incentives for an individual task, in comparison to a group-collaborative activity?
- Security and Privacy. The heterogeneity of wireless network protocols used by the large variety of network connected hardware and software sensors providing crowdsourcing data increases the risk of security compromises. Furthermore, crowdsourcing systems may gather, collate and distribute personal information about individuals. It is essential that users have means for retaining control over the distribution and dissemination of their private information.
Here is an invitation to submit your speaking proposal and present at the Second International Workshop on Ubiquitous Crowdsourcing. Participants will be selected based on short 4-page papers and 2-page demonstrations around the aforementioned topics of interest. All papers should follow the Ubicomp ACM Word or Latex template.
For more information on how to submit a paper or presentation proposal click here.
- June 18, 2001: Submission deadline
- July 1, 2011: Notification of acceptance
- July 11, 2011: Camera Ready Accepted Papers Due
- Sep 18, 2011: Ubicomp 2011 Workshop Program
- Maja Vukovic, IBM Research, TJ Watson, Hawthorne, USA (email@example.com)
- Soundar Kumara, Pennsylvania State University, USA (firstname.lastname@example.org)
- Chi Changyan, IBM China Research Lab, China
- Giorgos Cheliotis, National University of Singapore, Singapore
- Jonathan Corney, University of Strathclyde, UK
- Shalini Govil-Pai, Google, USA
- Dongwon Lee, Pennsylvania State University,USA
- Ponnurangam Kumaraguru, IIIT-Delhi, India
- Jonghun Park, Seoul National University, Korea
- Wiiliam Regli, Drexel University, USA
- Sanjay Sarma, MIT, USA
- Munindar Singh, North Carolina State, University, USA
- Michael VanPutte, Information Sciences Institute, USA
- Petros zerfos, IBM Research, USA
- Naveen Sharma, Xerox labs, USA
- LiYing Cui, Kimberly-Clark, USA