This two volume set LNCS 10041 and LNCS 10042 constitutes the proceedings of the 17th International Conference on Web Information Systems Engineering, WISE 2016, held in Shanghai, China, in November 2016. The 39 full papers and 31 short papers presented in these proceedings were carefully reviewed and selected from 233 submissions. The papers cover a wide range of topics such as Social Network Data Analysis; Recommender Systems; Topic Modeling; Data Diversity; Data Similarity; Context-Aware Recommendation; Prediction; Big Data Processing; Cloud Computing; Event Detection; Data Mining; Sentiment Analysis; Ranking in Social Networks; Microblog Data Analysis; Query Processing; Spatial and Temporal Data; Graph Theory; Non-Traditional Environments; and Special Session on Data Quality and Trust in Big Data.

This two volume set LNCS 10041 and LNCS 10042 constitutes the proceedings of the 17th International Conference on Web Information Systems Engineering, WISE 2016, held in Shanghai, China, in November 2016. The 39 full papers and 31 short papers presented in these proceedings were carefully reviewed and selected from 233 submissions. The papers cover a wide range of topics such as Social Network Data Analysis; Recommender Systems; Topic Modeling; Data Diversity; Data Similarity; Context-Aware Recommendation; Prediction; Big Data Processing; Cloud Computing; Event Detection; Data Mining; Sentiment Analysis; Ranking in Social Networks; Microblog Data Analysis; Query Processing; Spatial and Temporal Data; Graph Theory; Non-Traditional Environments; and Special Session on Data Quality and Trust in Big Data.

There has been a recent marked increase in the amount of spatial data collected by smart phones, space telescopes, and medical devices, among others. The increased volume has brought into focus the need for specialized systems to handle big spatial data. The Era of Big Spatial Data summarizes the state-of-the-art in this area. It classifies the existing work by considering six aspects of big spatial data systems, namely, approach, architecture, language, indexing, querying, and visualization. It describes each of these components in detail and gives examples of how they are implemented in existing systems. It also provides the reader with case studies of real applications that make use of these systems to provide services for end users. This is an invaluable reference for researchers or practitioners interested in getting a handle on the state of the art for Big Spatial Data storage and querying.