Web Data Management Practices PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Web Data Management Practices PDF full book. Access full book title Web Data Management Practices by Athena Vakali. Download full books in PDF and EPUB format.
Author: Athena Vakali
Publisher: IGI Global
ISBN: 1599042282
Category : Computers
Languages : en
Pages : 323
Get Book Here
Book Description
"This book provides an understanding of major issues, current practices and the main ideas in the field of Web data management, helping readers to identify current and emerging issues, as well as future trends. The most important aspects are discussed: Web data mining, content management on the Web, Web applications and Web services"--Provided by publisher.
Author: Athena Vakali
Publisher: IGI Global
ISBN: 1599042282
Category : Computers
Languages : en
Pages : 323
Get Book Here
Book Description
"This book provides an understanding of major issues, current practices and the main ideas in the field of Web data management, helping readers to identify current and emerging issues, as well as future trends. The most important aspects are discussed: Web data mining, content management on the Web, Web applications and Web services"--Provided by publisher.
Author: Serge Abiteboul
Publisher: Cambridge University Press
ISBN: 113950505X
Category : Computers
Languages : en
Pages : 451
Get Book Here
Book Description
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.
Author: Serge Abiteboul
Publisher: Morgan Kaufmann
ISBN: 9781558606227
Category : Computers
Languages : en
Pages : 280
Get Book Here
Book Description
Data model. Queries. Types. Sysems. A syntax for data. XML.. Query languages. Query languages for XML. Interpretation and advanced features. Typing semistructured data. Query processing. The lore system. Strudel. Database products supporting XML. Bibliography. Index. About the authors.
Author: Ma, Zongmin
Publisher: IGI Global
ISBN: 1605660299
Category : Computers
Languages : en
Pages : 384
Get Book Here
Book Description
Provides a single record of technologies and practices of the Semantic approach to the management, organization, interpretation, retrieval, and use of Web-based data.
Author: Susan Aasman
Publisher: Taylor & Francis
ISBN: 1040263496
Category : Language Arts & Disciplines
Languages : en
Pages : 469
Get Book Here
Book Description
The Routledge Companion to Transnational Web Archive Studies explores the untapped potential of web archives for researching transnational digital history and communication. It covers cross- border, cross- collection, and cross- institutional examination of web archives on a global scale. This comprehensive collaborative work, emerging from the WARCnet research network, presents an exploration of the ways web archive research can transcend technological and legal challenges to allow for new comparative, transnational studies of the web’s pasts, and of global events. By combining interdisciplinary work and fostering collaboration between web archivists and researchers, the book provides readers with cutting- edge approaches to analyzing digital cultural heritage across countries. The book contains concrete examples on how to research national web domains through a transnational perspective; provides case studies with grounded explorations of the COVID- 19 crisis as a distinctly transnational event captured by web archives; offers methodological considerations while unpacking techniques and skill sets for conducting transnational web archive research; and critically engages the politics and power dynamics inherent to web archives as institutionalised collections. The Routledge Companion to Transnational Web Archive Studies is an essential read for graduate students and scholars from internet and media studies, cultural studies, history, and digital humanities. It will also appeal to web archiving practitioners, including librarians, web curators, and IT developers.
Author: Kun Ma
Publisher: Springer
ISBN: 3319301926
Category : Technology & Engineering
Languages : en
Pages : 169
Get Book Here
Book Description
This book presents some of the emerging techniques and technologies used to handle Web data management. Authors present novel software architectures and emerging technologies and then validate using experimental data and real world applications. The contents of this book are focused on four popular thematic categories of intelligent Web data management: cloud computing, social networking, monitoring and literature management. The Volume will be a valuable reference to researchers, students and practitioners in the field of Web data management, cloud computing, social networks using advanced intelligence tools.
Author: Sourav S. Bhowmick
Publisher: Springer Science & Business Media
ISBN: 0387217819
Category : Computers
Languages : en
Pages : 481
Get Book Here
Book Description
Existence of huge amounts of data on the Web has developed an undeferring need to locate right information at right time, as well as to integrating information effectively to provide a comprehensive source of relevant information. There is a need to develop efficient tools for analyzing and managing Web data, and efficiently managing Web information from the database perspective. The book proposes a data model called WHOM (Warehouse Object Model) to represent HTML and XML documents in the warehouse. It defines a set of web algebraic operators for building new web tables by extracting relevant data from the Web, as well as generating new tables from existing ones. These algebraic operators are used for change detection.
Author: Connie Clare
Publisher:
ISBN: 9781783748020
Category : Data centers
Languages : en
Pages : 153
Get Book Here
Book Description
Engaging Researchers with Data Management is an invaluable collection of 24 case studies, drawn from institutions across the globe, that demonstrate clearly and practically how to engage the research community with RDM. These case studies together illustrate the variety of innovative strategies research institutions have developed to engage with their researchers about managing research data. Each study is presented concisely and clearly, highlighting the essential ingredients that led to its success and challenges encountered along the way. By interviewing key staff about their experiences.
Author: Dama International
Publisher:
ISBN: 9781634622349
Category : Database management
Languages : en
Pages : 628
Get Book Here
Book Description
Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309287812
Category : Mathematics
Languages : en
Pages : 191
Get Book Here
Book Description
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
