This book constitutes the proceedings of the 21st International Conference on Web Engineering, ICWE 2021, which was supposed to be held in Biarritz, France, in May 2021. Due to the corona pandemic the conference changed to a virtual format.The total of 22 full and 13 short contributions presented in this volume were carefully reviewed and selected from 128 submissions. The book also contains 6 demonstration, 1 poster, 3 PhD, and 3 tutorial papers. The papers were organized in topical sections named: Semantic Web; social Web; Web modeling and engineering; Web big data and data analytics; Web mining and knowledge extraction; Web of Things; Web programming; Web user interfaces; PhD symposium; posters and demonstrations; and tutorials. Chapter "A Web-Based Co-Creation and User Engagement Method and Platform" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Resource Description Framework (or RDF, in short) is set to deliver many of the original semi-structured data promises: flexible structure, optional schema, and rich, flexible Universal Resource Identifiers as a basis for information sharing. Moreover, RDF is uniquely positioned to benefit from the efforts of scientific communities studying databases, knowledge representation, and Web technologies. As a consequence, the RDF data model is used in a variety of applications today for integrating knowledge and information: in open Web or government data via the Linked Open Data initiative, in scientific domains such as bioinformatics, and more recently in search engines and personal assistants of enterprises in the form of knowledge graphs. Managing such large volumes of RDF data is challenging due to the sheer size, heterogeneity, and complexity brought by RDF reasoning. To tackle the size challenge, distributed architectures are required. Cloud computing is an emerging paradigm massively adopted in many applications requiring distributed architectures for the scalability, fault tolerance, and elasticity features it provides. At the same time, interest in massively parallel processing has been renewed by the MapReduce model and many follow-up works, which aim at simplifying the deployment of massively parallel data management tasks in a cloud environment. In this book, we study the state-of-the-art RDF data management in cloud environments and parallel/distributed architectures that were not necessarily intended for the cloud, but can easily be deployed therein. After providing a comprehensive background on RDF and cloud technologies, we explore four aspects that are vital in an RDF data management system: data storage, query processing, query optimization, and reasoning. We conclude the book with a discussion on open problems and future directions.

The Internet and World Wide Web have revolutionized access to information. Users now store information across multiple platforms from personal computers, to smartphones, to websites such as Youtube and Picasa. As a consequence, data management concepts, methods, and techniques are increasingly focused on distribution concerns. Now that information largely resides in the network, so do the tools that process this information. This book explains the foundations of XML, the Web standard for data management, with a focus on data distribution. It covers the many facets of distributed data management on the Web, such as description logics, that are already emerging in today's data integration applications and herald tomorrow's semantic Web. It also introduces the machinery used to manipulate the unprecedented amount of data collected on the Web. Several 'Putting into Practice' chapters describe detailed practical applications of the technologies and techniques. Striking a balance between the conceptual and the practical, the book will serve as an introduction to the new, global, information systems for Web professionals as well as for master's level courses.