This book provides an overview of crowdsourced data management. Covering all aspects including the workflow, algorithms and research potential, it particularly focuses on the latest techniques and recent advances. The authors identify three key aspects in determining the performance of crowdsourced data management: quality control, cost control and latency control. By surveying and synthesizing a wide spectrum of studies on crowdsourced data management, the book outlines important factors that need to be considered to improve crowdsourced data management. It also introduces a practical crowdsourced-database-system design and presents a number of crowdsourced operators. Self-contained and covering theory, algorithms, techniques and applications, it is a valuable reference resource for researchers and students new to crowdsourced data management with a basic knowledge of data structures and databases.

This book constitutes the refereed proceedings of the 37th International Conference on Conceptual Modeling, ER 2018, held in XI'an, China, in October 2018. The 30 full and 13 short papers presented together with 3 keynotes were carefully reviewed and selected from 151 submissions. This events covers a wide range of following topics: Conceptual modeling studies, ontological modeling, semi-structured data modeling, process modeling and management, spatio-temporal modeling, cloud-based modeling, schema and view modeling,languages and models, NoSQL modeling, conceptual modeling for machine learning and reasoning, applications of conceptual modeling.