Introduction to Data Science
by Jeffrey Stanton
Number of pages: 196
This book provides non-technical readers with a gentle introduction to essential concepts and activities of data science. For more technical readers, the book provides explanations and code for a range of interesting applications using the open source R language for statistical computing and graphics.
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by Mark Watson
A guide for using RDF data in information processing, linked data, and semantic web applications using both the AllegroGraph product and the Sesame open source project. Primarily written for programmers using either Java or other JVM languages.
by Nick Milton - Polimetrica
This book provides a comprehensive introduction to Knowledge Engineering, Knowledge Based Engineering, Knowledge Webs, Ontologies and Semantic Webs. It is aimed at students, researchers and practitioners interested in Knowledge Management.
by Richard T. Watson - Global Text Project
This textbook teaches how to exploit IS in a technology-rich environment. It focuses on information systems showing how IS is integrated in organizations, how knowledge workers are supported, and how important IS is for an organization’s success.
by Tom Heath, Christian Bizer - Morgan & Claypool
The book gives an overview of the principles of Linked Data as well as the Web of Data that has emerged through the application of these principles. The book discusses patterns for publishing Linked Data, describes deployed Linked Data applications.