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Author: Archana Patel Publisher: CRC Press ISBN: 1000964132 Category : Computers Languages : en Pages : 315
Book Description
As the world enters the era of big data, there is a serious need to give a semantic perspective to the data in order to find unseen patterns, derive meaningful information, and make intelligent decisions. Semantic technologies offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. These technologies reduce the problem of large semantic loss in the process of modelling knowledge, and provide sharable, reusable knowledge,and a common understanding of the knowledge. As a result, the interoperability and interconnectivity of the model make it priceless for addressing the issues of querying data. These technologies work with the concepts and relations that are very lose to the working of the human brain. They provide a semantic representation of any data format: unstructured or semi-structured. As a consequence, data becomes real-world entity rather than a string of characters. For these reasons, semantic technologies are highly valuable tools to simplify the existing problems of the industry leading to new opportunities. However, there are some challenges that need to be addressed to make industrial applications and machines smarter. This book aims to provide a roadmap for semantic technologies and highlights the role of these technologies in industry. The book also explores the present and future prospects of these semantic technologies along with providing answers to various questions like: Are semantic technologies useful for the next era (industry 4.0)? Why are semantic technologies so popular and extensively used in the industry? Can semantic technologies make intelligent industrial applications? Which type of problem requires the immediate attention of researchers? Why are semantic technologies very helpful in people’s future lives? This book will potentially serve as an important guide towards the latest industrial applications of semantic technologies for the upcoming generation, and thus becomes a unique resource for scholars, researchers, professionals and practitioners in the field.
Author: Archana Patel Publisher: CRC Press ISBN: 1000964132 Category : Computers Languages : en Pages : 315
Book Description
As the world enters the era of big data, there is a serious need to give a semantic perspective to the data in order to find unseen patterns, derive meaningful information, and make intelligent decisions. Semantic technologies offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. These technologies reduce the problem of large semantic loss in the process of modelling knowledge, and provide sharable, reusable knowledge,and a common understanding of the knowledge. As a result, the interoperability and interconnectivity of the model make it priceless for addressing the issues of querying data. These technologies work with the concepts and relations that are very lose to the working of the human brain. They provide a semantic representation of any data format: unstructured or semi-structured. As a consequence, data becomes real-world entity rather than a string of characters. For these reasons, semantic technologies are highly valuable tools to simplify the existing problems of the industry leading to new opportunities. However, there are some challenges that need to be addressed to make industrial applications and machines smarter. This book aims to provide a roadmap for semantic technologies and highlights the role of these technologies in industry. The book also explores the present and future prospects of these semantic technologies along with providing answers to various questions like: Are semantic technologies useful for the next era (industry 4.0)? Why are semantic technologies so popular and extensively used in the industry? Can semantic technologies make intelligent industrial applications? Which type of problem requires the immediate attention of researchers? Why are semantic technologies very helpful in people’s future lives? This book will potentially serve as an important guide towards the latest industrial applications of semantic technologies for the upcoming generation, and thus becomes a unique resource for scholars, researchers, professionals and practitioners in the field.
Author: Archana Patel Publisher: CRC Press ISBN: 1000964108 Category : Computers Languages : en Pages : 395
Book Description
As the world enters the era of big data, there is a serious need to give a semantic perspective to the data in order to find unseen patterns, derive meaningful information, and make intelligent decisions. Semantic technologies offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. These technologies reduce the problem of large semantic loss in the process of modelling knowledge, and provide sharable, reusable knowledge,and a common understanding of the knowledge. As a result, the interoperability and interconnectivity of the model make it priceless for addressing the issues of querying data. These technologies work with the concepts and relations that are very lose to the working of the human brain. They provide a semantic representation of any data format: unstructured or semi-structured. As a consequence, data becomes real-world entity rather than a string of characters. For these reasons, semantic technologies are highly valuable tools to simplify the existing problems of the industry leading to new opportunities. However, there are some challenges that need to be addressed to make industrial applications and machines smarter. This book aims to provide a roadmap for semantic technologies and highlights the role of these technologies in industry. The book also explores the present and future prospects of these semantic technologies along with providing answers to various questions like: Are semantic technologies useful for the next era (industry 4.0)? Why are semantic technologies so popular and extensively used in the industry? Can semantic technologies make intelligent industrial applications? Which type of problem requires the immediate attention of researchers? Why are semantic technologies very helpful in people’s future lives? This book will potentially serve as an important guide towards the latest industrial applications of semantic technologies for the upcoming generation, and thus becomes a unique resource for scholars, researchers, professionals and practitioners in the field.
Author: Archana Patel Publisher: CRC Press ISBN: 1000881296 Category : Computers Languages : en Pages : 234
Book Description
Gone are the days when data was interlinked with related data by humans and human interpretation was required. Data is no longer just data. It is now considered a Thing or Entity or Concept with meaning, so that a machine not only understands the concept but also extrapolates the way humans do. Data Science with Semantic Technologies: Deployment and Exploration, the second volume of a two-volume handbook set, provides a roadmap for the deployment of semantic technologies in the field of data science and enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition, this book offers the answer to various questions like: What makes a technology semantic as opposed to other approaches to data science? What is knowledge data science? How does knowledge data science relate to other fields? This book explores the optimal use of these technologies to provide the highest benefit to the user under one comprehensive source and title. As there is no dedicated book available in the market on this topic at this time, this book becomes a unique resource for scholars, researchers, data scientists, professionals, and practitioners. This volume can serve as an important guide toward applications of data science with semantic technologies for the upcoming generation.
Author: Jorge Cardoso Publisher: Springer Science & Business Media ISBN: 0387485317 Category : Computers Languages : en Pages : 308
Book Description
This professional book provides a series of case studies which give examples of real benefits to be derived from the adoption of semantic web based ontologies in real world situations, such as telecommunication, B2B integration, tourism, education and more. The book is designed to create platforms for bringing experts together (key government representatives, industry and academia) from different countries, and to compile the most recent use of semantics and ontologies.
Author: Stefan Biffl Publisher: Springer ISBN: 3319414909 Category : Computers Languages : en Pages : 405
Book Description
This is the first book to explore how Semantic Web technologies (SWTs) can be used to create intelligent engineering applications (IEAs). Technology-specific chapters reflect the state of the art in relevant SWTs and offer guidelines on how they can be applied in multi-disciplinary engineering settings characteristic of engineering production systems. In addition, a selection of case studies from various engineering domains demonstrate how SWTs can be used to create IEAs that enable, for example, defect detection or constraint checking. Part I “Background and Requirements of Industrie 4.0 for Semantic Web Solutions” provides the background information needed to understand the book and addresses questions concerning the semantic challenges and requirements of Industrie 4.0, and which key SWT capabilities may be suitable for implementing engineering applications. In turn, Part II “Semantic Web-Enabled Data Integration in Multi-Disciplinary Engineering” focuses on how SWTs can be used for data integration in heterogeneous, multi-disciplinary engineering settings typically encountered in the creation of flexible production systems. Part III “Creating Intelligent Applications for Multi-Disciplinary Engineering” demonstrates how the integrated engineering data can be used to support the creation of IEAs, while Part IV “Related and Emerging Trends in the Use of Semantic Web in Engineering” presents an overview of the broader spectrum of approaches that make use of SWTs to support engineering settings. A final chapter then rounds out the book with an assessment of the strengths, weaknesses and compatibilities of SWTs and an outlook on future opportunities for applying SWTs to create IEAs in flexible industrial production systems. This book seeks to build a bridge between two communities: industrial production on one hand and Semantic Web on the other. Accordingly, stakeholders from both communities should find this book useful in their work. Semantic Web researchers will gain a better understanding of the challenges and requirements of the industrial production domain, offering them guidance in the development of new technologies and solutions for this important application area. In turn, engineers and managers from engineering domains will arrive at a firmer grasp of the benefits and limitations of using SWTs, helping them to select and adopt appropriate SWTs more effectively. In addition, researchers and students interested in industrial production-related issues will gain valuable insights into how and to what extent SWTs can help to address those issues.
Author: Rajiv Pandey Publisher: Springer Nature ISBN: 303064619X Category : Technology & Engineering Languages : en Pages : 415
Book Description
This book is focused on an emerging area, i.e. combination of IoT and semantic technologies, which should enable breaking the silos of local and/or domain-specific IoT deployments. Taking into account the way that IoT ecosystems are realized, several challenges can be identified. Among them of definite importance are (this list is, obviously, not exhaustive): (i) How to provide common representation and/or shared understanding of data that will enable analysis across (systematically growing) ecosystems? (ii) How to build ecosystems based on data flows? (iii) How to track data provenance? (iv) How to ensure/manage trust? (v) How to search for things/data within ecosystems? (vi) How to store data and assure its quality? Semantic technologies are often considered among the possible ways of addressing these (and other, related) questions. More precisely, in academic research and in industrial practice, semantic technologies materialize in the following contexts (this list is, also, not exhaustive, but indicates the breadth of scope of semantic technology usability): (i) representation of artefacts in IoT ecosystems and IoT networks, (ii) providing interoperability between heterogeneous IoT artefacts, (ii) representation of provenance information, enabling provenance tracking, trust establishment, and quality assessment, (iv) semantic search, enabling flexible access to data originating in different places across the ecosystem, (v) flexible storage of heterogeneous data. Finally, Semantic Web, Web of Things, and Linked Open Data are architectural paradigms, with which the aforementioned solutions are to be integrated, to provide production-ready deployments.
Author: Archana Patel Publisher: CRC Press ISBN: 1000881237 Category : Computers Languages : en Pages : 293
Book Description
As data is an important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization. This first volume of a two-volume handbook set provides a roadmap for new trends and future developments of data science with semantic technologies. Data Science with Semantic Technologies: New Trends and Future Developments highlights how data science enables the user to create intelligence through these technologies. In addition, this book offers the answers to various questions such as: Can semantic technologies facilitate data science? Which type of data science problems can be tackled by semantic technologies? How can data scientists benefit from these technologies? What is the role of semantic technologies in data science? What is the current progress and future of data science with semantic technologies? Which types of problems require the immediate attention of the researchers? What should be the vision 2030 for data science? This volume can serve as an important guide toward applications of data science with semantic technologies for the upcoming generation and, thus, it is a unique resource for scholars, researchers, professionals, and practitioners in this field.
Author: Thomas Hoppe Publisher: Springer ISBN: 366255433X Category : Computers Languages : en Pages : 264
Book Description
This book describes methodologies for developing semantic applications. Semantic applications are software applications which explicitly or implicitly use the semantics, i.e. the meaning of a domain terminology, in order to improve usability, correctness, and completeness. An example is semantic search, where synonyms and related terms are used for enriching the results of a simple text-based search. Ontologies, thesauri or controlled vocabularies are the centerpiece of semantic applications. The book includes technological and architectural best practices for corporate use. The authors are experts from industry and academia with experience in developing semantic applications.
Author: Archana Patel Publisher: Wiley-Scrivener ISBN: 9781119865339 Category : Computers Languages : en Pages : 0
Book Description
DATA SCIENCE WITH SEMANTIC TECHNOLOGIES This book will serve as an important guide toward applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for scholars, researchers, professionals, and practitioners in this field. To create intelligence in data science, it becomes necessary to utilize semantic technologies which allow machine-readable representation of data. This intelligence uniquely identifies and connects data with common business terms, and it also enables users to communicate with data. Instead of structuring the data, semantic technologies help users to understand the meaning of the data by using the concepts of semantics, ontology, OWL, linked data, and knowledge-graphs. These technologies help organizations to understand all the stored data, adding the value in it, and enabling insights that were not available before. As data is the most important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization. Data Science with Semantic Technologies provides a roadmap for the deployment of semantic technologies in the field of data science. Moreover, it highlights how data science enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition, this book provides answers to various questions like: Can semantic technologies be able to facilitate data science? Which type of data science problems can be tackled by semantic technologies? How can data scientists benefit from these technologies? What is knowledge data science? How does knowledge data science relate to other domains? What is the role of semantic technologies in data science? What is the current progress and future of data science with semantic technologies? Which types of problems require the immediate attention of researchers? Audience Researchers in the fields of data science, semantic technologies, artificial intelligence, big data, and other related domains, as well as industry professionals, software engineers/scientists, and project managers who are developing the software for data science. Students across the globe will get the basic and advanced knowledge on the current state and potential future of data science.
Author: János Abonyi Publisher: Springer Nature ISBN: 3031474449 Category : Technology & Engineering Languages : en Pages : 277
Book Description
This book presents a comprehensive framework for developing Industry 4.0 and 5.0 solutions through the use of ontology modeling and graph-based optimization techniques. With effective information management being critical to successful manufacturing processes, this book emphasizes the importance of adequate modeling and systematic analysis of interacting elements in the era of smart manufacturing. The book provides an extensive overview of semantic technologies and their potential to integrate with existing industrial standards, planning, and execution systems to provide efficient data processing and analysis. It also investigates the design of Industry 5.0 solutions and the need for problem-specific descriptions of production processes, operator skills and states, and sensor monitoring in intelligent spaces. The book proposes that ontology-based data can efficiently represent enterprise and manufacturing datasets. The book is divided into two parts: modeling and optimization. The semantic modeling part provides an overview of ontologies and knowledge graphs that can be used to create Industry 4.0 and 5.0 applications, with two detailed applications presented on a reproducible industrial case study. The optimization part of the book focuses on network science-based process optimization and presents various detailed applications, such as graph-based analytics, assembly line balancing, and community detection. The book is based on six key points: the need for horizontal and vertical integration in modern industry; the potential benefits of integrating semantic technologies into ERP and MES systems; the importance of optimization methods in Industry 4.0 and 5.0 concepts; the need to process large amounts of data while ensuring interoperability and re-usability factors; the potential for digital twin models to model smart factories, including big data access; and the need to integrate human factors in CPSs and provide adequate methods to facilitate collaboration and support shop floor workers.
Author: Archana Patel
Author: Archana Patel
Author: Archana Patel
Author: Archana Patel
Author: Jorge Cardoso
Author: Stefan Biffl
Author: Rajiv Pandey
Author: Archana Patel
Author: Thomas Hoppe
Author: Archana Patel
Author: János Abonyi