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Modern information systems differ in essence from their predecessors. They support operations at multiple locations and different time zones, are distributed and network-based, and use multidimensional data analysis, data warehousing, knowledge discovery, knowledge management, mobile computing, and other modern information processing methods. This book considers fundamental issues of modern information systems. It discusses query processing, data quality, data mining, knowledge management, mobile computing, software engineering for information systems construction, and other topics. The book presents research results that are not available elsewhere. With more than 40 contributors, it is a solid source of information about the state of the art in the field of databases and information systems. It is intended for researchers, advanced students, and practitioners who are concerned with the development of advanced information systems.
Is this book about patterns? Yes and no. It is about software reuse and representation of knowledge that can be reapplied in similar situations; however, it does not follow the classic Alexandine conventions of the patterns community--i.e. Problem- solution- forces- context- example, etc. Chapter 6 on claims comes close to classic patterns, and the whole book can be viewed as a patterns language of abstract models for software engineering and HCI. So what sort of patterns does it contain? Specifications, conceptual models, design advice, but sorry not code. Plenty of other C++ code pattern books (see PLOP series). Nearest relative in published patterns books are Fowler's (1995) Analysis Patterns: Reusable object models and Coad, North and Mayfield. What do you mean by a Domain Theory? Not domains in the abstract mathematical sense, but domains in the knowledge--natural language sense, close to the everyday meaning when we talk about the application domain of a computer system, such as car rental, satellite tracking, whatever. The book is an attempt to answer the question ' what are the abstractions behind car rental, satellite tracking' so good design solutions for those problems can be reused. I work in industry, so what's in it for me? A new way of looking at software reuse, ideas for organizing a software and knowledge reuse program, new processes for reusing knowledge in requirements analysis, conceptual modeling and software specification. I am an academic, should I be interested? Yes if your research involves software engineering, reuse, requirements engineering, human computer interaction, knowledge engineering, ontologies and knowledge management. For teaching it may be useful for Master courses on reuse, requirements and knowledge engineering. More generally if you are interested in exploring what the concept of abstraction is when you extend it beyond programming languages, formal specification, abstract data types, etc towards requirements and domain knowledge. ADDITIONAL COPY: Based on more than 10 years of research by the author, this book is about putting software reuse on a firmer footing. Utilizing a multidisciplinary perspective--psychology and management science, as well as software--it describes the Domain Theory as a solution. The domain theory provides an abstract theory that defines a generic, reusable model of domain knowledge. Providing a comprehensive library of reusable models, practice methods for reuse, and theoretical insight, this book: *introduces the subject area of reuse and software engineering and explains a framework for comparing different reuse approaches; *develops a metric-oriented framework to assess the reuse claims of three competing approaches: patterns, ERPs, and the Domain Theory OSMs (object system models); *explains the psychological background for reuse and describes generic tasks and meta-domains; *introduces claims that provide a representation of design knowledge attached to Domain Theory models, as well as being a schema for representing reusable knowledge in nearly any form; *reports research that resulted from the convergence of the two theories; *describes the methods, techniques, and guidelines of design for reuse--the process of abstraction; and *elaborates the framework to investigate the future of reuse by different paradigms, generation of applications from requirements languages, and component-based software engineering via reuse libraries.
Twenty-nine papers from the July 1996 conference focus on such themes as knowledge engineering; design process and concurrency; assembly representation and modeling for articulated mechanisms; design optimization; case-based reasoning; and integrated design and artificial reality. This is the eighth
This book constitutes the thoroughly refereed joint post-proceedings of four workshops held during the Pacific Rim International Conference on Artificial Intelligence, PRICAI 2000, held in Melbourne, Australia, in August/September 2000. The 32 revised full papers presented were carefully selected during two rounds of reviewing and revision. In accordance with the four workshops represented, the book is organized in topical sections on applications of artificial intelligence in industry, artificial intelligence in electronic commerce, intelligent information agents, and teamwork and adjustable autonomy in agents.
This handbook charts the new engineering paradigm of engineering systems. It brings together contributions from leading thinkers in the field and discusses the design, management and enabling policy of engineering systems. It contains explorations of core themes including technical and (socio-) organisational complexity, human behaviour and uncertainty. The text includes chapters on the education of future engineers, the way in which interventions can be designed, and presents a look to the future. This book follows the emergence of engineering systems, a new engineering paradigm that will help solve truly global challenges. This global approach is characterised by complex sociotechnical systems that are now co-dependent and highly integrated both functionally and technically as well as by a realisation that we all share the same: climate, natural resources, a highly integrated economical system and a responsibility for global sustainability goals. The new paradigm and approach requires the (re)designing of engineering systems that take into account the shifting dynamics of human behaviour, the influence of global stakeholders, and the need for system integration. The text is a reference point for scholars, engineers and policy leaders who are interested in broadening their current perspective on engineering systems design and in devising interventions to help shape societal futures.
In this monograph, the authors demonstrate how the integration of adaptability, operability, and re-configurability in the design of complex systems is indispensable for the further digitization of engineering systems in smart manufacturing. Globalization of the customer base has resulted in distributed and networked manufacturing systems. However, current design methods are not suitable to address variations in product design, changes in production scale, or variations in product quality necessitated by dynamic changes in the market. Adaptability, operability, and re-configurability are key characteristics that are necessary to address the limitations of the current methods used to design networked manufacturing systems. In recent years, the digital transformation driving Industry 4.0 has had an enormous impact on globally distributed manufacturing. Digitalisation, the integration of digital technology into networked engineered systems, is increasingly being adopted to respond to changes in the market. This is achieved by means of (a) the concurrent design of adaptable systems, (b) addressing flexibility in design parameters, (c) conducting an operability analysis, and (d) employing a reconfiguration strategy to address faults and variances in product quality and re-establish connectivity among the elements in the system. The design of manufacturing systems in the age of Industry 4.0 is addressed in this monograph. The authors introduce the concept of a ‘smart platform’ and a computational framework for the digitalization of networked manufacturing systems. They also suggest how the framework and techniques in this monograph are applicable beyond the manufacturing domain for architecting networked engineered systems in other industries such as chemical processes and health care, that are being transformed through the adoption of the Industry 4.0 construct.
Data Warehousing and Mining (DWM) is the science of managing and analyzing large datasets and discovering novel patterns and in recent years has emerged as a particularly exciting and industrially relevant area of research. Prodigious amounts of data are now being generated in domains as diverse as market research, functional genomics and pharmaceuticals; intelligently analyzing these data, with the aim of answering crucial questions and helping make informed decisions, is the challenge that lies ahead. The Encyclopedia of Data Warehousing and Mining provides a comprehensive, critical and descriptive examination of concepts, issues, trends, and challenges in this rapidly expanding field of data warehousing and mining (DWM). This encyclopedia consists of more than 350 contributors from 32 countries, 1,800 terms and definitions, and more than 4,400 references. This authoritative publication offers in-depth coverage of evolutions, theories, methodologies, functionalities, and applications of DWM in such interdisciplinary industries as healthcare informatics, artificial intelligence, financial modeling, and applied statistics, making it a single source of knowledge and latest discoveries in the field of DWM.