Multidimensional Data Visualization

This book is a step-by-step tutorial full of diagrams, core concept explanations, best practice tips, and links to working book examples. This book will show you how create web-ready data visualizatio

This book opens discussion on the topics of data management. It is not a new topic at all because scientists deal with data every day; what makes this topic unique is the scale of data everyone is dea

This book canvases the thoughts and practices of Kenneth W. Thompson, who has contributed a 'public philosophy' of multidimensional and interdisciplinary ideas and practices. Drawing on interviews wit

Based on the authors’ market leading data structures books in Java and C++, this book offers a comprehensive, definitive introduction to data structures in Python by authoritative authors. Data Struct

This book surveys the state of the art in multidimensional, physically-correct visual texture modeling. Features: reviews the entire process of texture synthesis, including material appearance represe

This book deploys philosopher and economist Amartya Sen's Capabilities Approach to re-evaluate and estimate multidimensional poverty in Mozambique. Sen's conceptual notion of poverty as "unfreedom" is

Human liberation has become an epochal challenge in today’s world, requiring not only emancipation from oppressive structures but also from the oppressive self.? It is a multidimensional struggle and

Multivariate procedures allow social workers and other human services researchers to analyze complex, multidimensional social problems and interventions in ways that minimize oversimplification. This

With the purpose of building upon standard web technologies, open linked data serves as a useful way to connect previously unrelated data and to publish structured data on the web. The application of

This book surveys the development of integral geometry on domains of homogeneous spaces, covering analysis of multidimensional Euclidean domains and Riemannian symmetric spaces of arbitrary ranks as w

We live in the era of Big Data, with storage and transmission capacity measured notjust in terabytes but in petabytes (where peta- denotes a quadrillion, or athousand trillion). Data collection is con

A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the

The amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Scie

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You’ll start with general concepts of measurement and work your way through a detai

This classic, best selling data structures text provides a firm foundation in data abstraction that emphasizes the distinction between specifications and implementation as the basis for an object-orie

?The first objective of this study is to derive a multidimensional research framework simultaneously outlining and concretising particular aspects being relevant to and surrounding the elicitation and

Specially selected from the reviewed and edited proceedings of the 2012 International Symposium on Spatial Data Handling, this collection of the latest research achievements incorporates findings in a

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic commun

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic commun

On 25 January 2012, the European Commission presented its long awaited new “Data protection package”. With this proposal for a drastic revision of the data protection framework in Europe, it is fair t

Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or ot

What is bad data? Some people consider it a technical phenomenon, like missing values or malformed records, but bad data includes a lot more. In this handbook, data expert Q. Ethan McCallum has gather

For machine intelligence applications to work successfully, machines must perform reliably under variations of data and must be able to keep up with data streams. Internet-Scale Pattern Recognition: N

The Complete Book of Data Anonymization: From Planning to Implementation supplies a 360-degree view of data privacy protection using data anonymization. It examines data anonymization from both a prac

Bringing a practitioner’s view to big data analytics, this work examines the drivers behind big data, postulates a set of use cases, identifies sets of solution components, and recommends various impl

A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with real data examples, numerous screen shots, and output excerpts.

Data Insights offers multi-disciplinary perspectives and useful information about how visualizations can open your eyes to data. This thought-provoking book takes a conversational approach to presenti

Unique insights to implement big data analytics and reap big returns to your bottom lineFocusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohl

Boost your Big Data IQ! Gain insight into how to govern and consume IBM's unique in-motion and at-rest Big Data analytic capabilitiesBig Data represents a new era of computing'an inflection point of o

The world is awash with digital data from social networks, blogs, business, science and engineering. Data-intensive computing facilitates understanding of complex problems that must process massive amounts of data. Through the development of new classes of software, algorithms and hardware, data-intensive applications can provide timely and meaningful analytical results in response to exponentially growing data complexity and associated analysis requirements. This emerging area brings many challenges that are different from traditional high-performance computing. This reference for computing professionals and researchers describes the dimensions of the field, the key challenges, the state of the art and the characteristics of likely approaches that future data-intensive problems will require. Chapters cover general principles and methods for designing such systems and for managing and analyzing the big data sets of today that live in the cloud and describe example applications in bioin

You can choose several data access frameworks when building Java enterprise applications that work with relational databases. But what about big data? This hands-on introduction shows you how Spring D

In his latest book, bestselling author Gregory Michie critiques high-stakes schooling and provides a powerful alternative vision of teaching as a humanistic enterprise, students as multidimensional be

Each edition of Introduction to Data Compression has widely been considered the best introduction and reference text on the art and science of data compression, and the?fourth edition continues in thi

This book covers important aspects of fundamental research in data provenance and data management(DPDM), including provenance representation and querying, as well as practical applications in such dom

Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time

As more and more data is generated at a faster-than-ever rate, processing large volumes of data is becoming a challenge for data analysis software. Addressing performance issues, Cloud Computing: Data

Are you struggling with the formal design of your organization's data resource? Do you find yourself forced into generic data architectures and universal data models? Do you find yourself warping th

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become sel

Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mini

Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same e