This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.

This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.

This book presents a mathematical treatment of the radio resource allocation of modern cellular communications systems in contested environments. It focuses on fulfilling the quality of service requirements of the living applications on the user devices, which leverage the cellular system, and with attention to elevating the users' quality of experience. The authors also address the congestion of the spectrum by allowing sharing with the band incumbents while providing with a quality-of-service-minded resource allocation in the network. The content is of particular interest to telecommunications scheduler experts in industry, communications applications academia, and graduate students whose paramount research deals with resource allocation and quality of service.

The "EPCglobal Architecture Framework" is currently the most accepted technical approach to the Internet of Things and provides a solid foundation for building Business-to-Business information networks based on unique identifications of 'things'. Lately, the vision of the Internet of Things has been extended to a more holistic approach that integrates sensors as well as actuators and includes non-business stakeholders. A detailed look at the current state of the art in
research concerning cost and benefit estimations is provided and the limits of Cost Benefit Sharing for RFID-based IT-infrastructures are explained. In this work a market driven evaluation based on sales potential of information is developed. Simple technical means for aggregation of micro values to a billable amount are discussed. The requirements for electronic billing infrastructure are defined and a matching e-billing solutions for an evaluation scenario is presented, providing a technical infrastructure to evaluate and bill product-related information in a future Internet of Things, based on an extended EPCglobal Architecture. Further opportunities and threats are discussed to provide an overview of its future potential. As a result it will contribute to the sustainable success of the Internet of Things itself.

In the mid 1990s, Tim Berners-Lee had the idea of developing the World Wide Web into a "Semantic Web", a web of information that could be interpreted by machines in order to allow the automatic exploitation of data, which until then had to be done by humans manually. One of the first people to research topics related to the Semantic Web was Professor Rudi Studer. From the beginning, Rudi drove projects like ONTOBROKER and On-to-Knowledge, which later resulted in W3C standards such as RDF and OWL. By the late 1990s, Rudi had established a research group at the University of Karlsruhe, which later became the nucleus and breeding ground for Semantic Web research, and many of today's well-known research groups were either founded by his disciples or benefited from close cooperation with this think tank. In this book, published in celebration of Rudi's 60th birthday, many of his colleagues look back on the main research results achieved during the last 20 years. Under the editorship of Dieter Fensel, once one of Rudi's early PhD students, an impressive list of contributors and contributions has been collected, covering areas like Knowledge Management, Ontology Engineering, Service Management, and Semantic Search. Overall, this book provides an excellent overview of the state of the art in Semantic Web research, by combining historical roots with the latest results, which may finally make the dream of a "Web of knowledge, software and services" come true.

This book contains the combined proceedings of the 4th International Conference on Ubiquitous Computing Application and Wireless Sensor Network (UCAWSN-15) and the 16th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT-15). The combined proceedings present peer-reviewed contributions from academic and industrial researchers in fields including ubiquitous and context-aware computing, context-awareness reasoning and representation, location awareness services, and architectures, protocols and algorithms, energy, management and control of wireless sensor networks. The book includes the latest research results, practical developments and applications in parallel/distributed architectures, wireless networks and mobile computing, formal methods and programming languages, network routing and communication algorithms, database applications and data mining, access control and authorization and privacy preserving computation.

Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination. Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection. This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.

Imagine yourself as a military officer in a conflict zone trying to identify locations of weapons caches supporting road-side bomb attacks on your country's troops. Or imagine yourself as a public health expert trying to identify the location of contaminated water that is causing diarrheal diseases in a local population. Geospatial abduction is a new technique introduced by the authors that allows such problems to be solved. Geospatial Abduction provides the mathematics underlying geospatial abduction and the algorithms to solve them in practice; it has wide applicability and can be used by practitioners and researchers in many different fields. Real-world applications of geospatial abduction to military problems are included. Compelling examples drawn from other domains as diverse as criminology, epidemiology and archaeology are covered as well. This book also includes access to a dedicated website on geospatial abduction hosted by University of Maryland. Geospatial Abduction targets practitioners working in general AI, game theory, linear programming, data mining, machine learning, and more. Those working in the fields of computer science, mathematics, geoinformation, geological and biological science will also find this book valuable.

This book constitutes the refereed proceedings of the 4th IFIP WG 8.1 Working Conference on Method Engineering, ME 2011, held in Paris, France, in April 2011. The 13 revised full papers and 6 short papers presented together with the abstracts of two keynote talks were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections on situated method engineering, method engineering foundations, customized methods, tools for method engineering, new trends to build methods, and method engineering services.

In this book, the editors explain how students enrolled in two digital forensic courses at their institution are exposed to experiential learning opportunities, where the students acquire the knowledge and skills of the subject-matter while also learning how to adapt to the ever-changing digital forensic landscape. Their findings (e.g., forensic examination of different IoT devices) are also presented in the book. Digital forensics is a topic of increasing importance as our society becomes "smarter" with more of the "things" around us been internet- and inter-connected (e.g., Internet of Things (IoT) and smart home devices); thus, the increasing likelihood that we will need to acquire data from these things in a forensically sound manner. This book is of interest to both digital forensic educators and digital forensic practitioners, as well as students seeking to learn about digital forensics.

Fuzzy Cluster Analysis presents advanced and powerful fuzzy clustering techniques. This thorough and self-contained introduction to fuzzy clustering methods and applications covers classification, image recognition, data analysis and rule generation. Combining theoretical and practical perspectives, each method is analysed in detail and fully illustrated with examples. Features include:

• Sections on inducing fuzzy if-then rules by fuzzy clustering and non-alternating optimization fuzzy clustering algorithms
• Discussion of solid fuzzy clustering techniques like the fuzzy c-means, the Gustafson-Kessel and the Gath-and-Geva algorithm for classification problems
• Focus on linear and shell clustering techniques used for detecting contours in image analysis
• Accompanying software and data sets pertaining to the examples presented, enabling the reader to learn through experimentation
• Examination of the difficulties involved in evaluating the results of fuzzy cluster analysis and of determining the number of clusters with analysis of global and local validity measures
• Description of different fuzzy clustering techniques allowing the user to select the method most appropriate to a particular problem

This book sheds new light on the current and future challenges faced by cities, and presents approaches, options and solutions enabled by Information and Communication Technologies (ICT) in the smart city context. By focusing on sustainability objectives within a rapidly changing social, economic, environmental and technological setting, it explores a variety of planning challenges faced by contemporary cities and the power of smart city developments in terms of providing innovative tools, approaches, methodologies and technologies to help cities cope with these challenges. Key issues addressed include smart city (e-) planning and (e-)participation; smart data management to facilitate decision-making processes in cities and insular communities on a variety of topics; smart and sustainable management aspects of climate change, water scarcity, mobility, energy, infrastructure, tourism, blue growth, risk assessment; etc. The book presents current and potential pathways and applications for the evolution of smart cities and communities, taking into consideration the unique problems and opportunities emanating from their specific geographical location. The case study examples mainly concern small and medium-sized cities and communities as well as insular areas in the Mediterranean region, while also incorporating lessons learned from other parts of the world. Their focus is on the specific opportunities and threats emerging in these urban and insular environments, which are characterized by their role as globally known tourist destinations, their coastal or port character, and unique cultural resources, as well as the high rated vulnerability in very many sustainability respects (social, economic, biodiversity, urbanization, migration, poverty, etc.) to be found in the Mediterranean region at large

The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data's immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.

When digitized entities, connected devices and microservices interact purposefully, we end up with a massive amount of multi-structured streaming (real-time) data that is continuously generated by different sources at high speed. Streaming analytics allows the management, monitoring, and real-time analytics of live streaming data. The topic has grown in importance due to the emergence of online analytics and edge and IoT platforms. A real digital transformation is being achieved across industry verticals through meticulous data collection, cleansing and crunching in real time. Capturing and subjecting those value-adding events is considered to be the prime task for achieving trustworthy and timely insights. The authors articulate and accentuate the challenges widely associated with streaming data and analytics, describe data analytics algorithms and approaches, present edge and fog computing concepts and technologies and show how streaming analytics can be accomplished in edge device clouds. They also delineate several industry use cases across cloud system operations in transportation and cyber security and other business domains. The book will be of interest to ICTs industry and academic researchers, scientists and engineers as well as lecturers and advanced students in the fields of data science, cloud/fog/edge architecture, internet of things and artificial intelligence and related fields of applications. It will also be useful to cloud/edge/fog and IoT architects, analytics professionals, IT operations teams and site reliability engineers (SREs).

As economies continue to evolve, knowledge is being recognized as a business asset and considered a crucial component of business strategy. The ability to manage knowledge is increasingly important for securing and maintaining organizational success and surviving in the knowledge economy. ""Knowledge Management Strategies for Business Development"" addresses the relevance of knowledge management strategies for the advancement of organizations worldwide. This reference book supplies business practitioners, academicians, and researchers with comprehensive tools to systematically guide through a process that focuses on data gathering, analysis, and decision making.

A paradigm shift is taking place in computer science: one generation ago, we learned to abstract from hardware to software, now we are abstracting from software to serviceware implemented through service-oriented computing. Yet ensuring interoperability in open, heterogeneous, and dynamically changing environments, such as the Internet, remains a major challenge for actual machine-to-machine integration. Usually significant problems in aligning data, processes, and protocols appear as soon as a specific piece of functionality is used within a different application context.

The Semantic Web Services (SWS) approach is about describing services with metadata on the basis of domain ontologies as a means to enable their automatic location, execution, combination, and use. Fensel and his coauthors provide a comprehensive overview of SWS in line with actual industrial practice. They introduce the main sociotechnological components that ground the SWS vision (like Web Science, Service Science, and service-oriented architectures) and several approaches that realize it, e.g. the Web Service Modeling Framework, OWL-S, and RESTful services. The real-world relevance is emphasized through a series of case studies from large-scale R&D projects and a business-oriented proposition from the SWS technology provider Seekda.

Each chapter of the book is structured according to a predefined template, covering both theoretical and practical aspects, and including walk-through examples and hands-on exercises. Additional learning material is available on the book website www.swsbook.org. With its additional features, the book is ideally suited as the basis for courses or self-study in this field, and it may also serve as a reference for researchers looking for a state-of-the-art overview of formalisms, methods, tools, and applications related to SWS."

Logic and the Organization of Information closely examines the historical and contemporary methodologies used to catalogue information objects-books, ebooks, journals, articles, web pages, images, emails, podcasts and more-in the digital era.
This book provides an in-depth technical background for digital librarianship, and covers a broad range of theoretical and practical topics including: classification theory, topic annotation, automatic clustering, generalized synonymy and concept indexing, distributed libraries, semantic web ontologies and Simple Knowledge Organization System (SKOS). It also analyzes the challenges facing today's information architects, and outlines a series of techniques for overcoming them.
Logic and the Organization of Information is intended for practitioners and professionals working at a design level as a reference book for digital librarianship. Advanced-level students, researchers and academics studying information science, library science, digital libraries and computer science will also find this book invaluable.

This book provides extensive insight into the possibilities and challenges of XML in building new information management solutions in networked organizations. After a brief introduction to Web communication features and XML fundamentals, the book examines the benefits of adopting XML and illustrates various types of XML use: XML in document management; XML for data-centric and multimedia components; XML as a format for metadata, including metadata for the Semantic Web; and XML in support of data interchange between software applications and among organizations. The challenges of adopting XML in large-scale information management are also discussed. In addition, applications across a broad spectrum are examined and numerous case studies pertaining to the adoption of XML are presented. The book is particularly suitable for courses offered in Information Studies, Information Systems, or Information Technology. It also serves as an excellent practical guide for professionals in information management and provides important support material for courses in Computer Science and in Business.

Recently, researchers have gained innovative principles, methods, algorithms, and solutions to challenging problems faced in the development of data warehousing, knowledge discovery, and data mining applications. Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications provides a comprehensive analysis on current issues and trends in retrieval expansion. Containing research from leading international experts, this book presents future challenges and opportunities in the field valuable to academicians, researchers, and practitioners.

This book covers diverse aspects of advanced computer and communication engineering, focusing specifically on industrial and manufacturing theory and applications of electronics, communications, computing and information technology. Experts in research, industry, and academia present the latest developments in technology, describe applications involving cutting-edge communication and computer systems and explore likely future directions. In addition, access is offered to numerous new algorithms that assist in solving computer and communication engineering problems. The book is based on presentations delivered at ICOCOE 2014, the 1st International Conference on Communication and Computer Engineering. It will appeal to a wide range of professionals in the field, including telecommunication engineers, computer engineers and scientists, researchers, academics and students.

This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featuring chapters which discuss effective and efficient approaches in dealing with the inherent complexity and increasing demands in data science, a variety of application domains are covered. Various case studies by data management and analysis experts are presented in these chapters. Covered applications include banking, social networks, bioinformatics, healthcare, transportation and criminology. Highlighting the Importance of Big Data Management and Analysis for Various Applications will provide the reader with an understanding of how data management and analysis are adapted to these applications. This book will appeal to researchers and professionals in the field.

This book investigates the impact of production input factors on the market, consumer and producer energy demand characteristics in 30 industrial sectors for South Korea over the period 1980-2009, and for Japan over the period 1973-2006, with special emphasis placed on the effects of ICT investment on the demand for energy. A dynamic factor demand model is developed, accounting for the adjustment costs that are defined in terms of forgone output from current production. It addresses four key aspects of production and energy demand in manufacturing: first, it establishes the various relationships between different factors of production. Second, it investigates whether the energy demand in the industrial sectors in South Korea would be decreased or increased by substituting/complementing with other input factors such as ICT capital and labor. Third, it looks at sources of growth in the industrial sectors through decomposing the Divisia index based total factor productivity (TFP). Finally it provides appropriate policy recommendations based on these findings. The results of this study may provide industrial sectors' stakeholders and environmental and industrial policy makers with a flexible model that has the capacity to assess outcomes of various policies under certain scenarios. The factor demand methodology described in this book is very advanced and up-to-date. It can be used when teaching advanced graduate courses and in empirically advanced research. Therefore, it is highly relevant in both teaching as a main or supplementary text and in particular as a reference handbook in conducting empirical research. The focus on ICT effects on energy use makes this book an important addition to the existing literature on industrial development.

This monograph illustrates important notions in security reductions and essential techniques in security reductions for group-based cryptosystems. Using digital signatures and encryption as examples, the authors explain how to program correct security reductions for those cryptographic primitives. Various schemes are selected and re-proven in this book to demonstrate and exemplify correct security reductions. This book is suitable for researchers and graduate students engaged with public-key cryptography.

This book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection of the best papers originally presented in French at the EGC 2014 and EGC 2015 conferences held in Rennes (France) in January 2014 and Luxembourg in January 2015. The book is in three parts: The first four chapters discuss optimization considerations in data mining. The second part explores specific quality measures, dissimilarities and ultrametrics. The final chapters focus on semantics, ontologies and social networks. Written for PhD and MSc students, as well as researchers working in the field, it addresses both theoretical and practical aspects of knowledge discovery and management.