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This chapter aims to help librarians understand the underlying rationale for Resource Description and Access (RDA) and recognize the great potential of the Semantic Web for libraries.

It explains the linked data model and Semantic Web technologies in basic, informative terms, and describes how the Semantic Web is constructed. Semantic Web standards and technologies are discussed in detail, including URI, RDF, and ontologies. The study also traces the development of RDA and some of the major library Semantic Web projects. The authors explore how RDA shapes bibliographical data and prepares it for linked data in the Semantic Web. In addition, this study examines what libraries in the United States and the rest of the world have achieved in implementing RDA since its release.

RDA is the correct approach libraries should take.

This is the first and only chapter that covers the development of RDA in other countries as well as in the United States. It is highly informative for anyone who wishes to understand the RDA and Semantic Web and their relevance to libraries in a short period of time.

Purpose – To investigate the potential of the semantic web as a source of information about social networks within academia, as well as more widely for webometric investigations.

Methodology – The functionality of five semantic search engines were analyzed to determine their suitability for webometric investigations, with the most suitable, Sindice.com, then being used to investigate the use of Friend of a Friend (FOAF) within UK academic web space.

Findings – In comparison to the web of documents, the semantic web is still a small part of online content. Even the well-established FOAF social vocabulary was not found on the majority of academic web sites, let alone being found to represent the majority of academics, and provided little indication of social networks between institutions. Nonetheless from a webometric perspective the study does show the potential of a semantic web for a far wider range of webometric investigations, and demonstrates that, unlike the traditional web, there are currently useful tools available.

Implications – Having established that there are appropriate tools available for webometric investigations of the semantic web, and acknowledging the potential of the semantic web for far more detailed webometric investigations, there is a need for additional studies to determine the specific strengths and limitations of the tools that are available, and investigate those areas where webometric investigations can provide the most useful insights.

Originality/value – The research applies established webometric methodologies to the social semantic web, demonstrating the potential of a whole new area for future webometric investigation.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

This chapter will explore how assessment might look in next generation learning spaces where we have the potential to merge physical and virtual activities. Students now have ready access to a world of resources within their classroom and this fundamentally changes the nature of learning and assessment. The trend toward gamification of learning and assessment will be examined and the issue of assessment in new educational environments such as MOOCs will be explored. The impact of the semantic web (Web 3.0), where web objects and their context are all linked and objects have memory of how an individual student used them on previous occasions, will be discussed.

Next generation learning spaces encapsulate the affordances of both physical and virtual spaces and yet many assessment tasks are still designed as if students occupied only one of these spaces. Teachers will need to design more authentic, meaningful tasks that will engage students in using the full range of their capabilities and available resources, both physical and virtual. Students come together physically to engage in the social construction of their knowledge and can use the virtual spaces to broaden the social dimension of their learning environment.

Gamification of learning and assessment will require new approaches to defining tasks as teachers will need to decide how to incorporate diagnostic, formative, and summative assessment components within a more holistic educational environment. Game theory will be blended with learning theory in curriculum design and will result in the redesign of learning and assessment activities that are based on engagement (flow), user needs, and an evidence-centered design approach.

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. Besides, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management, and so on. In recent years, knowledge graph techniques in China are also developing rapidly and different Chinese knowledge graphs have been built to support various applications. Under the background of “One Belt One Road (OBOR)” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China on developing knowledge graph is also a good reference. Thus, in this chapter, the authors mainly introduce the development of Chinese knowledge graphs and their applications. The authors first describe the background of OBOR, and then introduce the concept of knowledge graph and three typical Chinese knowledge graphs, including Zhishi.me, CN-DBpedia, and XLORE. Finally, the authors demonstrate several applications of Chinese knowledge graphs.

The silos of library cataloging data have long been recognized as barriers to the seamless discovery of library resources via the Web and to the interaction of library data with Web data and other uses. In order to better serve users, library cataloging data must be available in a more open environment, and libraries are looking to linked data to present library resources in the data stream of the Web in a way that is seamless to users. This entails changing cataloging formats and tools to Web standards. While there is a lot of discussion and activity around linked data, this chapter approaches the highly technological topic in a way that is geared more toward a general and practical cataloging perspective.

This chapter helps us to understand the staffing and workflow ramifications of Linked Data. A survey of the current state of metadata work, compared to the possibilities and intentions of Linked Data modeling and technology, allows us to make a needs assessment for future planning. Findings are that current trends in metadata work – distributed production alongside centralized management, iterative and collaborative resource description – are appropriate in a Linked Data environment, and should be further cultivated. A plan for training staff on the conceptual modeling of Linked Data is also outlined, together providing a launching pad to begin organizational planning for Linked Data.