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It is over 20 years since the functional data model and functional programming languages were first introduced to the computing community. Although developed by separate research communities, recent work, presented in this book, suggests there is powerful synergy in their integration. As database technology emerges as central to yet more complex and demanding applications in areas such as bioinformatics, national security, criminal investigations and advanced engineering, more sophisticated approaches like those presented here, are needed. A tutorial introduction by the editors prepares the reader for the chapters that follow, written by leading researchers, including some of the early pioneers. They provide a comprehensive treatment showing how the functional approach provides for modeling, analyzis and optimization in databases, and also data integration and interoperation in heterogeneous environments. Several chapters deal with mathematical results on the transformation of expressions, fundamental to the functional approach. The book also aims to show how the approach relates to the Internet and current work on semistructured data, XML and RDF. The book presents a comprehensive view of the functional approach to data management, bringing together important material hitherto widely scattered, some new research, and a comprehensive set of references. It will serve as a valuable resource for researchers, faculty and graduate students, as well as those in industry responsible for new systems development.
Multi-Domain Master Data Management delivers practical guidance and specific instruction to help guide planners and practitioners through the challenges of a multi-domain master data management (MDM) implementation. Authors Mark Allen and Dalton Cervo bring their expertise to you in the only reference you need to help your organization take master data management to the next level by incorporating it across multiple domains. Written in a business friendly style with sufficient program planning guidance, this book covers a comprehensive set of topics and advanced strategies centered on the key MDM disciplines of Data Governance, Data Stewardship, Data Quality Management, Metadata Management, and Data Integration. - Provides a logical order toward planning, implementation, and ongoing management of multi-domain MDM from a program manager and data steward perspective. - Provides detailed guidance, examples and illustrations for MDM practitioners to apply these insights to their strategies, plans, and processes. - Covers advanced MDM strategy and instruction aimed at improving data quality management, lowering data maintenance costs, and reducing corporate risks by applying consistent enterprise-wide practices for the management and control of master data.
This book constitutes the refereed proceedings of the 21st International Conference on Scientific and Statistical Database Management, SSDBM 2009, held in New Orleans, LA, USA in June 2009. The 29 revised full papers and 12 revised short papers including poster and demo papers presented together with three invited presentations were carefully reviewed and selected from 76 submissions. The papers are organized in topical sections on improving the end-user experience, indexing, physical design, and energy, application experience, workflow, query processing, similarity search, mining, as well as spatial data.
The two-volume set LNAI 10191 and 10192 constitutes the refereed proceedings of the 9th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2017, held in Kanazawa, Japan, in April 2017. The total of 152 full papers accepted for publication in these proceedings was carefully reviewed and selected from 420 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Intelligent Database Systems; Intelligent Information Systems; Decision Support and Control Systems; Machine Learning and Data Mining; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Intelligent and Context Systems; Multiple Model Approach to Machine Learning; Applications of Data Science; Artificial Intelligence Applications for E-services; Automated Reasoning and Proving Techniques with Applications in Intelligent Systems; Collective Intelligence for Service Innovation, Technology Opportunity, E-Learning and Fuzzy Intelligent Systems; Intelligent Computer Vision Systems and Applications; Intelligent Data Analysis, Applications and Technologies for Internet of Things; Intelligent Algorithms and Brain Functions; Intelligent Systems and Algorithms in Information Sciences; IT in Biomedicine; Intelligent Technologies in the Smart Cities in the 21st Century; Analysis of Image, Video and Motion Data in Life Sciences; Modern Applications of Machine Learning for Actionable Knowledge Extraction; Mathematics of Decision Sciences and Information Science; Scalable Data Analysis in Bioinformatics and Biomedical Informatics; and Technological Perspective of Agile Transformation in IT organizations.
For 60 years the International Federation for Information Processing (IFIP) has been advancing research in Information and Communication Technology (ICT). This book looks into both past experiences and future perspectives using the core of IFIP's competence, its Technical Committees (TCs) and Working Groups (WGs). Soon after IFIP was founded, it established TCs and related WGs to foster the exchange and development of the scientific and technical aspects of information processing. IFIP TCs are as diverse as the different aspects of information processing, but they share the following aims: To establish and maintain liaison with national and international organizations with allied interests and to foster cooperative action, collaborative research, and information exchange. To identify subjects and priorities for research, to stimulate theoretical work on fundamental issues, and to foster fundamental research which will underpin future development. To provide a forum for professionals with a view to promoting the study, collection, exchange, and dissemination of ideas, information, and research findings and thereby to promote the state of the art. To seek and use the most effective ways of disseminating information about IFIP’s work including the organization of conferences, workshops and symposia and the timely production of relevant publications. To have special regard for the needs of developing countries and to seek practicable ways of working with them. To encourage communication and to promote interaction between users, practitioners, and researchers. To foster interdisciplinary work and – in particular – to collaborate with other Technical Committees and Working Groups. The 17 contributions in this book describe the scientific, technical, and further work in TCs and WGs and in many cases also assess the future consequences of the work’s results. These contributions explore the developments of IFIP and the ICT profession now and over the next 60 years. The contributions are arranged per TC and conclude with the chapter on the IFIP code of ethics and conduct.
The objective of the conference is to bring to focus the recent technological advancements across all the stages of data analysis including acquisition, processing, and communication. Advancements in acquisition sensors along with improved storage and computational capabilities, have stimulated the progress in theoretical studies and state-of-the-art real-time applications involving large volumes of data. This compels researchers to investigate the new challenges encountered, where traditional approaches are incapable of dealing with large, complicated new forms of data.
As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.
Dealing with the volume, complexity, and diversity of data currently being generated by scientific experiments and simulations often causes scientists to waste productive time. Scientific Data Management: Challenges, Technology, and Deployment describes cutting-edge technologies and solutions for managing and analyzing vast amounts of data, helping
"This book provides a wide compendium of references to topics in the field of the databases systems and applications"--Provided by publisher.