Applications in different domains require reactive processing of massive, dynamically generated streams of data. This trend is increasingly visible also on the Web, where more and more streaming sources are becoming available. These originate from social networks, sensor networks, the Internet of Things (IoT) and many other technologies that use the Web as a platform for sharing data. This has resulted in new Web-centric efforts such as the Web of Things (WoT), which focuses on exposing and describing the IoT resources on the Web; or the Social Web which provides protocols, vocabularies, and APIs to facilitate access to social communications and interactions on the Web.
Several challenges arise in this context, including the opportunity of performing data analytics over Web streams. This requires the necessity of integrating heterogeneous Web data, which should be distributed and accessible in a decentralized manner. Some of these challenges have been addressed through emerging efforts like Stream Reasoning and RDF Stream Processing.
While these are relevant examples of research in this domain, there is a growing need to develop flexible and scalable analytical processing for streaming data on the Web, in order to allow decentralized processing, publication and discovery of streaming data, as well as integration mechanisms at Web scale. To achieve this, the expertise from other communities, including stream mining, machine learning and distributed processing can be highly valuable.
This workshop aims at putting together relevant communities in order to discuss and explore holistic processing models for streaming data on the Web. This will include discussions on the issues related to publishing data streams on the Web as well as analysing them with queries and inference processes. The event will contribute to the creation of an active community interested in integrating stream processing, data analytics and and dynamic data reasoning by using methods inspired by data and knowledge management.