World Wide Web is a rich information space where documents are interconnected as a gigantic network, and users are not only able to interact with the Webs to actively explore and search for useful information as data consumers, but can also publish data through different web services to further enrich the network as data producers. The interconnection and the real-time nature of the Webs allow data produces and consumers to be tightly connected, such that web content and usages, and user interests and behaviors, can be directly and timely analyzed for different applications. For example, by monitoring information about the number of visitors to a website and the number of page views, businesses can utilize the web traffic and popularity trends for market research. On the other hand, by studying social media content and sentiments, businesses can collect public feedback with respect to a certain brand or product. 

Web analytics is a data science research sub-discipline, which focuses on the collection, measurements, analysis, and reporting of web data to support business intelligence, optimized decision makings, and other purposes. Due to the enormous sizes of the Web and the huge number of users, our existing web analytics skills are severely challenged by (1) large scale data volumes, (2) rich data schema, structure, and heterogeneity, (3) data inconsistency and noise, and (4) real-time requirement from applications. 

The data science and web analytics (DSWA) workshop intends to provide a focused research forum to advance web analytics techniques and solutions. We encourage submissions from different aspects of web related applications, systems, services, and algorithm designs.