Emerging Web 3 0 Semantic Web Applications In Higher Education

The Web is evolving from a place where a prodigious amount of text and images are stored to a place where educational and other needs are serviced. The Web is becoming increasingly automated with functions that previously required human action undertaken automatically moving learners and other users more quickly to useful support. More and more such services interoperate with each other through computer programs and agents. This is the territory of semantic Web services and Web 3.0. Just as shop bots and auction bots abound in handling a particular task on the Web currently, in higher education of the future such related bots and agents will interact with the heterogeneous information that is the stuff of higher education. The scale of such agent-based mediation and linked data will grow over time. Increasingly, intelligent agents and bots will undertake tasks on behalf of their faculty, administrator, and student owners. Collaborations among faculty and students around the world will be increasingly supported by semantic social networks capable of providing crucial functions. Students can be engaged in participating in the design and development of semantic Web applications in such areas as structuring and representing knowledge. The increasing availability of interactive educational tools and collaborative community-resources, such as wikis, can be the foundation for deploying semantically marked-up and social-connected educational spaces where students construct their own learning pathways in explorations of knowledge and creating new content integration. This volume will share visions and partial realizations of the impact of the semantic Web and associated Web 3.0 features on higher education. This volume will provide accounts of cutting-edge pedagogic applications of the semantic Web with its extremely extensive use of interconnecting information technologies.

This is the first book treatment on two "hot button" topics in Information Systems, Computer Science and Education: the application of web technology for educational use. The result is a thorough and highly useful presentation on the confluence of the technical aspects of the Semantic Web and the field of Education or the art of teaching. The book will interest researchers and students in the fields of Information Systems, Computer Science, and Education.

The final part deals with the social semantic web. Aspects covered include a broad survey of this emerging area; a description of a number of projects and experiences exploring semantic web technologies in social learning contexts; and a new approach to collaborative filtering.

Artificial intelligence (AI) technologies are one of top investment priorities in these days. They are aimed at finding applications in fields of special value for humans, including education. The fourth industrial revolution will replace not only human hands but also human brains, the time of machines requires new forms of work and new ways of business education, however we must be aware that if there is no control of human-chatbot interaction, there is a risk of losing sight of this interaction’s goal. First, it is important to get people to truly understand AI systems, to intentionally participate in their use, as well as to build their trust, because “the measure of success for AI applications is the value they create for human lives” (Stanford University 2016, 33). Consequently, society needs to adapt to AI applications if it is to extend its benefits and mitigate the inevitable errors and failures. This is why it is highly recommended to create new AI-powered tools for education that are the result of cooperation between AI researchers and humanities’ and social sciences’ researchers, who can identify cognitive processes and human behaviors. This book is authored by a range of international experts with a diversity of backgrounds and perspectives hopefully bringing us closer to the responses for the questions what we should teach (what the ‘right’ set of future skills is), how we should teach (the way in which schools should teach and assess them) and where we should teach (what implications does AI have for today’s education infrastructure). We must remember as we have already noticed before “…education institutions would need to ensure that that they have an appropriate infrastructure, as well as the safety and credibility of AI-based systems. Ultimately, the law and policies need to adjust to the rapid pace of AI development, because the formal responsibility for appropriate learning outcomes will in future be divided between a teacher and a machine. Above all, we should ensure that AI respect human and civil rights (Stachowicz-Stanusch, Amann, 2018)”.

Continual advancements in web technology have highlighted the need for formatted systems that computers can utilize to easily read and sift through the hundreds of thousands of data points across the internet. Therefore, having the most relevant data in the least amount of time to optimize the productivity of users becomes a priority. Semantic Web Science and Real-World Applications provides emerging research exploring the theoretical and practical aspects of semantic web science and real-world applications within the area of big data. Featuring coverage on a broad range of topics such as artificial intelligence, social media monitoring, and microblogging recommendation systems, this book is ideally designed for IT consultants, academics, professionals, and researchers of web science seeking the current developments, requirements and standards, and technology spaces presented across academia and industries.

The Semantic Web combines the descriptive languages RDF (Resource Description Framework) and OWL (Web Ontology Language), with the data-centric, customizable XML (eXtensible Mark-up Language) to provide descriptions of the content of Web documents. These machine-interpretable descriptions allow more intelligent software systems to be written, automating the analysis and exploitation of web-based information. Software agents will be able to create automatically new services from already published services, with potentially huge implications for models of e-Business. Semantic Web Technologies provides a comprehensive overview of key semantic knowledge technologies and research. The authors explain (semi-)automatic ontology generation and metadata extraction in depth, along with ontology management and mediation. Further chapters examine how Semantic Web technology is being applied in knowledge management (“Semantic Information Access”) and in the next generation of Web services. Semantic Web Technologies: Provides a comprehensive exposition of the state-of-the art in Semantic Web research and key technologies. Explains the use of ontologies and metadata to achieve machine-interpretability. Describes methods for ontology learning and metadata generation. Discusses ontology management and evolution, covering ontology change detection and propagation, ontology dependency and mediation. Illustrates the theoretical concepts with three case studies on industrial applications in digital libraries, the legal sector and the telecommunication industry. Graduate and advanced undergraduate students, academic and industrial researchers in the field will all find Semantic Web Technologies an essential guide to the technologies of the Semantic Web.

In the last few years, there has been an increased advancement and evolution in semantic web and information systems in a variety of fields. The integration of these approaches to ontology engineering, sophisticated methods and algorithms for open linked data extraction, and advanced decision-making creates new opportunities for a bright future. Innovations, Developments, and Applications of Semantic Web and Information Systems is a critical scholarly resource that discusses integrated methods of research and analytics in information technology. Featuring coverage on a broad range of topics, such as cognitive computing, artificial intelligence, machine learning, data analysis, and algorithms, this book is geared towards researchers, academicians, and professionals seeking current information on semantic web and information systems.

The Semantic Web is a vision – the idea of having data on the Web defined and linked in such a way that it can be used by machines not just for display purposes but for automation, integration and reuse of data across various applications. However, there is a widespread misconception that the Semantic Web is a rehash of existing AI and database work. Kashyap, Bussler, and Moran dispel this notion by presenting the multi-disciplinary technological underpinnings such as machine learning, information retrieval, service-oriented architectures, and grid computing. Thus they combine the informational and computational aspects needed to realize the full potential of the Semantic Web vision.