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Conceptually, a database consists of objects and relationships. Object Relationship Notation (ORN) is a simple notation that more precisely defines relationships by combining UML multiplicities with uniquely defined referential actions. This book shows how ORN can be used in UML class diagrams and database definition languages (DDLs) to better model and implement relationships and thus more productively develop database applications. For the database developer, it presents many examples of relationships modeled using ORN-extended class diagrams and shows how these relationships are easily mapped to an ORN-extended SQL or Object DDL. For the DBMS developer, it presents the specifications and algorithms needed to implement ORN in a relational and object DBMS. This book also describes tools that can be downloaded or accessed via the Web. These tools allow databases to be modeled using ORN and implemented using automatic code generation that adds ORN support to Microsoft SQL Server and Progress Object Store. Object Relationship Notation (ORN) for Database Applications: Enhancing the Modeling and Implementation of Associations is written for research scientists, research libraries, professionals, and advanced-level students in computer science.
Conceptually, a database consists of objects and relationships. Object Relationship Notation (ORN) is a simple notation that more precisely defines relationships by combining UML multiplicities with uniquely defined referential actions. This book shows how ORN can be used in UML class diagrams and database definition languages (DDLs) to better model and implement relationships and thus more productively develop database applications. For the database developer, it presents many examples of relationships modeled using ORN-extended class diagrams and shows how these relationships are easily mapped to an ORN-extended SQL or Object DDL. For the DBMS developer, it presents the specifications and algorithms needed to implement ORN in a relational and object DBMS. This book also describes tools that can be downloaded or accessed via the Web. These tools allow databases to be modeled using ORN and implemented using automatic code generation that adds ORN support to Microsoft SQL Server and Progress Object Store. Object Relationship Notation (ORN) for Database Applications: Enhancing the Modeling and Implementation of Associations is written for research scientists, research libraries, professionals, and advanced-level students in computer science.
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This book contains the best papers of the First International Conference on Software and Data Technologies (ICSOFT 2006), organized by the Institute for Systems and Technologies of Information, Communication and Control (INSTICC) in cooperation with the Object Management Group (OMG). Hosted by the School of Business of the Polytechnic Institute of Setubal, the conference was sponsored by Enterprise Ireland and the Polytechnic Institute of Setúbal. The purpose of ICSOFT 2006 was to bring together researchers and practitioners int- ested in information technology and software development. The conference tracks were “Software Engineering”, “Information Systems and Data Management”, “Programming Languages”, “Distributed and Parallel Systems” and “Knowledge Engineering.” Being crucial for the development of information systems, software and data te- nologies encompass a large number of research topics and applications: from imp- mentation-related issues to more abstract theoretical aspects of software engineering; from databases and data-warehouses to management information systems and kno- edge-base systems; next to that, distributed systems, pervasive computing, data quality and other related topics are included in the scope of this conference. ICSOFT included in its program a panel to discuss the future of software devel- ment, composed by six distinguished world-class researchers. Furthermore, the c- ference program was enriched by a tutorial and six keynote lectures. ICSOFT 2006 received 187 paper submissions from 39 countries in all continents.
This book is a comprehensive presentation of entity-relationship (ER) modeling with regard to an integrated development and modeling of database applications. It comprehensively surveys the achievements of research in this field and deals with the ER model and its extensions. In addition, the book presents techniques for the translation of the ER model into classical database models and languages, such as relational, hierarchical, and network models and languages, as well as into object-oriented models.
The Internet and World Wide Web have revolutionized access to information. Users now store information across multiple platforms from personal computers to smartphones and websites. As a consequence, data management concepts, methods and techniques are increasingly focused on distribution concerns. Now that information largely resides in the network, so do the tools that process this information. This book explains the foundations of XML with a focus on data distribution. It covers the many facets of distributed data management on the Web, such as description logics, that are already emerging in today's data integration applications and herald tomorrow's semantic Web. It also introduces the machinery used to manipulate the unprecedented amount of data collected on the Web. Several 'Putting into Practice' chapters describe detailed practical applications of the technologies and techniques. The book will serve as an introduction to the new, global, information systems for Web professionals and master's level courses.
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results