Method engineering is a very young field. Generally, method engineering can be considered from engineering of an entire methodology for information systems development to engineering of modeling techniques according to project requirements. Computer aided method engineering is about generation and use of information systems design techniques according to user needs. Some times such environments are called generic tools or MetaCASE. Computer-Aided Method Engineering: Designing Case Repositories for the 21st Century presents a contribution on a methodology and architecture of a CASE repository, forwarding a theory that will bring about the component based development into CASE tool design and development covering a repository construction principle for the 21st century.

Collaborative working has been increasingly viewed as a good practice for organizations to achieve efficiency. Organizations that work well in collaboration may have access to new sources of funding, deliver new, improved, and more integrated services, make savings on shared costs, and exchange knowledge, information and expertise. Collaboration and the Semantic Web: Social Networks, Knowledge Networks and Knowledge Resources showcases cutting-edge research on the intersections of Semantic Web, collaborative work, and social media research, exploring how the resources of so-called social networking applications, which bring people together to interact and encourage sharing of personal information and ideas, can be tapped by Semantic Web techniques, making shared Web contents readable and processable for machine and intelligent applications, as well as humans. Semantic technologies have shown their potential for integrating valuable knowledge, and they are being applied to the composition of digital learning and working platforms. Integrated semantic applications, linked data, social networks, and networked digital solutions can now be used in collaborative environments and present participants with the context-aware information that they need.

Multimedia and its rich semantics are profligate in today s digital environment. Databases and content management systems serve as essential tools to ensure that the endless supply of multimedia content are indexed and remain accessible to end users. Methods and Innovations for Multimedia Database Content Management highlights original research on new theories, algorithms, technologies, system design, and implementation in multimedia data engineering and management with an emphasis on automatic indexing, tagging, high-order ranking, and rule mining. This book is an ideal resource for university researchers, scientists, industry professionals, software engineers and graduate students.

In the literature of information science, a number of studies have been carried out attempting to model cognitive, affective, behavioral, and contextual factors associated with human information seeking and retrieval. On the other hand, only a few studies have addressed the exploration of creative thinking in music, focusing on understanding and describing individuals' information seeking behavior during the creative process. Trends in Music Information Seeking, Behavior, and Retrieval for Creativity connects theoretical concepts in information seeking and behavior to the music creative process. This publication presents new research, case studies, surveys, and theories related to various aspects of information retrieval and the information seeking behavior of diverse scholarly and professional music communities. Music professionals, theorists, researchers, and students will find this publication an essential resource for their professional and research needs.

Privacy protection within large databases can be a challenge. By examining the current problems and challenges this domain is facing, more efficient strategies can be established to safeguard personal information against invasive pressures. HCI Challenges and Privacy Preservation in Big Data Security is an informative scholarly publication that discusses how human-computer interaction impacts privacy and security in almost all sectors of modern life. Featuring relevant topics such as large scale security data, threat detection, big data encryption, and identity management, this reference source is ideal for academicians, researchers, advanced-level students, and engineers that are interested in staying current on the advancements and drawbacks of human-computer interaction within the world of big data.

Managing Time in Relational Databases: How to Design, Update and Query Temporal Data introduces basic concepts that will enable businesses to develop their own framework for managing temporal data. It discusses the management of uni-temporal and bi-temporal data in relational databases, so that they can be seamlessly accessed together with current data; the encapsulation of temporal data structures and processes; ways to implement temporal data management as an enterprise solution; and the internalization of pipeline datasets. The book is organized into three parts. Part 1 traces the history of temporal data management and presents a taxonomy of bi-temporal data management methods. Part 2 provides an introduction to Asserted Versioning, covering the origins of Asserted Versioning; core concepts of Asserted Versioning; the schema common to all asserted version tables, as well as the various diagrams and notations used in the rest of the book; and how the basic scenario works when the target of that activity is an asserted version table. Part 3 deals with designing, maintaining, and querying asserted version databases. It discusses the design of Asserted Versioning databases; temporal transactions; deferred assertions and other pipeline datasets; Allen relationships; and optimizing Asserted Versioning databases.

Education and research in the field of database technology can prove problematic without the proper resources and tools on the most relevant issues, trends, and advancements. Selected Readings on Database Technologies and Applications supplements course instruction and student research with quality chapters focused on key issues concerning the development, design, and analysis of databases. Containing over 30 chapters from authors across the globe, these selected readings in areas such as data warehousing, information retrieval, and knowledge discovery depict the most relevant and important areas of classroom discussion within the categories of Fundamental Concepts and Theories; Development and Design Methodologies; Tools and Technologies; Application and Utilization; Critical Issues; and Emerging Trends.

The long-standing debate on public vs. private healthcare systems has forced an examination of these organisations, in particular whether these approaches play corresponding or conflicting roles in service to global citizens. Healthcare Management and Economics: Perspectives on Public and Private Administration discusses public and private healthcare organisations by gathering perspectives on the differences in service, management, delivery, and efficiency. Highlighting the impact of citizens and information technology in these healthcare processes, this book is a vital collection of research for practitioners, academics, and scholars in the healthcare management field.

The body of research in all aspects of Semantic Web development, design, and application continues to grow alongside new trends in the information systems community. Semantic-Enabled Advancements on the Web: Applications Across Industries reviews current and future trends in Semantic Web research with the aim of making existing and potential applications more accessible to a broader community of academics, practitioners, and industry professionals. Covering topics including recommendation systems, semantic search, and ontologies, this reference is a valuable contribution to the existing literature in this discipline.

As the world has entered the era of big data, there is a need to give a semantic perspective to the data to find unseen patterns, derive meaningful information, and make intelligent decisions. This 2-volume handbook set is a unique, comprehensive, and complete presentation of the current progress and future potential explorations in the field of data science and related topics. Handbook of Data Science with Semantic Technologies provides a roadmap for a new trend and future development of data science with semantic technologies. The first volume serves as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for both academic researchers and industry professionals. The second volume provides a roadmap for the deployment of semantic technologies in the field of data science that enables users to create intelligence through these technologies by exploring the opportunities while eradicating the current and future challenges. The set explores the optimal use of these technologies to provide the maximum benefit to the user under one comprehensive source. This set consisting of two separate volumes can be utilized independently or together as an invaluable resource for students, scholars, researchers, professionals, and practitioners in the field.

Daily procedures such as scientific experiments and business processes have the potential to create a huge amount of data every day, hour, or even second, and this may lead to a major problem for the future of efficient data search and retrieval as well as secure data storage for the world's scientists, engineers, doctors, librarians, and business managers.Design, Performance, and Analysis of Innovative Information Retrieval examines a number of emerging technologies that significantly contribute to modern Information Retrieval (IR), as well as fundamental IR theories and concepts that have been adopted into new tools or systems. This reference is essential to researchers, educators, professionals, and students interested in the future of IR.

As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.

This book explores categories of applications and driving factors surrounding the Smart City phenomenon. The contributing authors provide perspective on the Smart Cities, covering numerous applications and classes of applications. The book uses a top-down exploration of the driving factors in Smart Cities, by including focal areas including "Smart Healthcare," "Public Safety & Policy Issues," and "Science, Technology, & Innovation." Contributors have direct and substantive experience with important aspects of Smart Cities and discuss issues with technologies & standards, roadblocks to implementation, innovations that create new opportunities, and other factors relevant to emerging Smart City infrastructures. Features an exploration of Smart City issues and solutions from a variety of stakeholders in the evolving field Presents conversational, nuanced, and forward thinking perspectives on Smart Cities, their implications, limitations, obstacles, and opportunities Includes contributions from industry insiders who have direct, relevant experience with their respective subjects as well as positioning and corporate stature

As it is with building a house, most of the work necessary to build a data warehouse is neither visible nor obvious when looking at the completed product. While it may be easy to plan for a data warehouse that incorporates all the right concepts, taking the steps needed to create a warehouse that is as functional and user-friendly as it is theoretically sound, is not especially easy. That's the challenge that Building and Maintaininga Data Warehouse answers. Based on a foundation of industry-accepted principles, this work provides an easy-to-follow approach that is cohesive and holistic. By offering the perspective of a successful data warehouse, as well as that of a failed one, this workdetails those factors that must be accomplished and those that are best avoided. Organized to logically progress from more general to specific information, this valuable guide: Presents areas of a data warehouse individually and in sequence, showing how each piece becomes a working part of the whole Examines the concepts and principles that are at the foundation of every successful data warehouse Explains how to recognize and attend to problematic gaps in an established data warehouse Provides the big picture perspective that planners and executives require Those considering the planning and creation of a data warehouse, as well as those who've already built one will profit greatly from the insights garnered by the author during his years of creating and gathering information on state-of-the-art data warehouses that are accessible, convenient, and reliable.