Big Data Analytics Panel at the International Workshop on Crowd Assisted Sensing, Pervasive Systems and Communications (CASPer 2017) at IEEE PerCom

Crowd assisted sensing and crowdsourcing, as well as their underlying pervasive systems and communications are a fast growing research area and one of the enabling technologies of smart cities and smart infrastructures, as well as important building blocks in healthcare monitoring and vehicular technologies. Crowd assisted sensing (often called participatory sensing) opens new ways for data collection which can enable the development of highly scalable and successful pervasive applications and services.
These are topics of the 4th International Workshop on Crowd Assisted Sensing, Pervasive Systems and Communications (CASPer 2017). This workshop is held in conjunction with the 15th IEEE International Conference on Pervasive Computing and Communications, PerCom 2017, in Kona, Hawaii, March 13-17 , sponsored among others by the IEEE Computer Society and the National Science Foundation NSF. IEEE PerCom is dealing with a range of topics such as mobile and distributed computing, sensor systems, ambient intelligence, and smart devices and has distinguished keynote speakers like John Krumm (Microsoft Research) and Hui Lei (IBM, Watson Cloud).
Alexander Zipf (GIScience Heidelberg/ HeiGIT) is invited Panel Member at the panel session of CASPer 2017. The panel will discuss questions related to the issue of processing unstructured Big Data, as this is currently one of the most challenging problems facing Data Scientists. In this panel we will explore how crowdsourcing can help big data by leveraging the power of the crowd to make sense of the data. Examples from Heidelberg include VGI Quality Analytics and deriving new information from VGI/OSM the Social Web and Geo-Microtasking (e.g. MapSwipe) for example through Deep Learning.