With smart-phones in their pockets, more than 1 billion people now have access to sensing, computation, and connectivity, making it possible to harness the power of the crowd to collect and share data about their surroundings and experiences on a massive scale. Crowdsensing/crowdsourcing is a novel data collection paradigm that leverages this vast mobile sensor network, making it possible to expand the scope of research endeavors and address civic issues without requiring the purchase of specialized sensors or the installation and maintenance of network infrastructure. Data collected using such applications may come from unexpected yet interesting and valuable sources and may allow for collecting data in previously inaccessible locations and contexts.

This new data collection paradigm introduces several research challenges. Privacy is a primary concern for users who contribute sensitive or personally identifiable information (PII). Incentive mechanisms for participation may be needed to encourage people to volunteer their resources to collect data. Methods are needed for processing large-scale, user-generated data sets into meaningful information, and for assessing and understanding the quality of information to help guide decision-making. Approaches which involve the crowd in such data analysis tasks, with humans serving as a source of semantic information, interpretation, and evaluation of crowdsensing/crowdsourcing data, can also help to build an understanding of the physical, computational, and socio-technical environment.

The objective of this workshop is to provide a forum for discussion, debate, and collaboration focused on ideas, trends, techniques, and recent advances in crowdsensing and crowdsourcing. We invite original research contributions that advance the state of the art as well as position papers that pose a new direction or present a controversial point of view. Topics of interest include, but are not limited to:

• Algorithms to handle, process, and visualize large-scale crowdsensing/crowdsourcing data sets
• Data integrity, security, privacy, and provenance for crowdsensing/crowdsourcing data
• Trust and reputation systems for crowdsensing/crowdsourcing applications
• Determining and assessing Quality of Information for crowdsensing/crowdsourcing data
• Crowd-assisted (human-in-the-loop) approaches to analyzing crowdsensing/crowdsourcing data
• Context modeling and reasoning in crowdsensing/crowdsourcing applications
• Incentive mechanisms for participation in crowdsensing/crowdsourcing applications
• Supporting crowdsensing/crowdsourcing in heterogeneous networks
• Crowd assisted pervasive systems and communications
• Novel use of sensors for crowdsensing/crowdsourcing applications
• Energy-efficient mechanisms for crowdsensing/crowdsourcing applications
• Programming abstractions and middleware for crowdsensing/crowdsourcing applications
• Novel large-scale crowdsensing/crowdsourcing applications

Submitted papers must be original contributions that are unpublished and are not currently under consideration for publication by other venues. Submissions are limited to a maximum length of 6 pages and must adhere to IEEE format (2 column, 10 pt font). Papers can be submitted via the EDAS submission portal for CASPer 2018. Templates are available via the workshop website. Workshop papers will be included and indexed in the IEEE digital libraries (Xplore). Note, that each accepted workshop paper requires a full PerCom registration (no registration is available for workshops only).

Important Dates:

• Submission deadline: November 25, 2017 (FIRM)
• Author Notification: December 23, 2017
• Camera ready due: January 12, 2018 (FIRM)