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Many challenging problems in information systems engineering involve the manipulation of complex metadata artifacts or models, such as database schema, interface specifications, or object diagrams, and mappings between models. Applications solving metadata manipulation problems are complex and hard to build. The goal of generic model management is to reduce the amount of programming needed to solve such problems by providing a database infrastructure in which a set of high-level algebraic operators are applied to models and mappings as a whole rather than to their individual building blocks. This book presents a systematic study of the concepts and algorithms for generic model management. The first prototype of a generic model management system is described, the algebraic operators are introduced and analyzed, and novel algorithms for implementing them are developed. Using the prototype system and the operators presented, solutions are developed for several practically relevant problems, such as change propagation and reintegration.
Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. - Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics - Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics - Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions
The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge.
This book constitutes the refereed proceedings of the 26th International Conference on Conceptual Modeling, ER 2007. Coverage in the papers includes data warehousing and data mining, design methodologies and tools, information and database integration, information modeling concepts and ontologies, integrity constraints, logical foundations of conceptual modeling, patterns and conceptual meta-modeling, semi-structured data and XML, as well as Web information systems and XML.
This two-volume set LNCS 3760/3761 constitutes the refereed proceedings of the three confederated conferences CoopIS 2005, DOA 2005, and ODBASE 2005 held as OTM 2005 in Agia Napa, Cyprus in October/November 2005. The 89 revised full and 7 short papers presented together with 3 keynote speeches were carefully reviewed and selected from a total of 360 submissions. Corresponding with the three OTM 2005 main conferences CoopIS, DOA, and ODBASE, the papers are organized in topical sections on workflow, workflow and business processes, mining and filtering, petri nets and processs management, information access and integrity, heterogeneity, semantics, querying and content delivery, Web services, agents, security, integrity and consistency, chain and collaboration mangement, Web services and service-oriented architectures, multicast and fault tolerance, communication services, techniques for application hosting, mobility, security and data persistence, component middleware, java environments, peer-to-peer computing architectures, aspect oriented middleware, information integration and modeling, query processing, ontology construction, metadata, information retrieval and classification, system verification and evaluation, and active rules and Web services.
This Festschrift volume, published in honor of John Mylopoulos on the occasion of his retirement from the University of Toronto, contains 25 high-quality papers, written by leading scientists in the field of conceptual modeling. The volume has been divided into six sections. The first section focuses on the foundations of conceptual modeling and contains material on ontologies and knowledge representation. The four sections on software and requirements engineering, information systems, information integration, and web and services, represent the chief current application domains of conceptual modeling. Finally, the section on implementations concentrates on projects that build tools to support conceptual modeling. With its in-depth coverage of diverse topics, this book could be a useful companion to a course on conceptual modeling.
This book constitutes the thoroughly refereed post-proceedings of 11 international workshops held as satellite events of the 9th International Conference on Model Driven Engineering Languages and Systems, MoDELS 2006, in Genoa, Italy, in October 2006 (see LNCS 4199). The 32 revised full papers were carefully selected for inclusion in the book. They are presented along with a doctorial and an educators' symposium section.
A comprehensive guide to using strategic HR methods to increase company performance. This book explains what strategic human resources means, how it differs from other HR activities, and why it is critical to business performance. It walks through key questions for designing, deploying and integrating different strategic HR processes including staffing, performance management, compensation, succession management, and development. The book also addresses the role of technology in strategic HR, and discusses how to get companies to support, adopt, and maintain effective strategic HR processes. The book includes dozens of illustrative examples of effective and ineffective strategic HR using stories drawn from a range of companies and industries.
This book constitutes the refereed proceedings of the Second European Conference on Model Driven Architecture - Foundations and Applications, ECMDA-FA 2006, held in Bilbao, Spain, in July 2006. The 30 revised full papers presented - 18 papers from the foundations track and 12 from the applications track - were carefully reviewed and selected from 78 submissions. The papers are organized in topical sections on integration, applikcatoins of transformations, applications of MDA, process, model consistency, model management, transformation, ontologies, re-engineering, tools and profiles, tool generation, constraints, model management and transformations.
Data Modeling Essentials, Third Edition, covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with "the rules". In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises. This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective. - Thorough coverage of the fundamentals and relevant theory - Recognition and support for the creative side of the process - Expanded coverage of applied data modeling includes new chapters on logical and physical database design - New material describing a powerful technique for model verification - Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict