
- 268 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
A Librarian's Guide to Graphs, Data and the Semantic Web
About this book
Graphs are about connections, and are an important part of our connected and data-driven world. A Librarian's Guide to Graphs, Data and the Semantic Web is geared toward library and information science professionals, including librarians, software developers and information systems architects who want to understand the fundamentals of graph theory, how it is used to represent and explore data, and how it relates to the semantic web. This title provides a firm grounding in the field at a level suitable for a broad audience, with an emphasis on open source solutions and what problems these tools solve at a conceptual level, with minimal emphasis on algorithms or mathematics. The text will also be of special interest to data science librarians and data professionals, since it introduces many graph theory concepts by exploring data-driven networks from various scientific disciplines. The first two chapters consider graphs in theory and the science of networks, before the following chapters cover networks in various disciplines. Remaining chapters move on to library networks, graph tools, graph analysis libraries, information problems and network solutions, and semantic graphs and the semantic web.
- Provides an accessible introduction to network science that is suitable for a broad audience
- Devotes several chapters to a survey of how graph theory has been used in a number of scientific data-driven disciplines
- Explores how graph theory could aid library and information scientists
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Yes, you can access A Librarian's Guide to Graphs, Data and the Semantic Web by James Powell in PDF and/or ePUB format, as well as other popular books in Languages & Linguistics & Library & Information Science. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- About the authors
- Preface and Acknowledgments
- Introduction
- 1. Graphs in theory
- 2. Graphs and how to make them
- 3. Graphs and the Semantic Web
- 4. RDF and its serializations
- 5. Ontologies
- 6. SPARQL
- 7. Inferencing, reasoning, and rules
- 8. Understanding Linked Data
- 9. Library networksâcoauthorship, citation, and usage graphs
- 10. Networks in life sciences
- 11. Biological networks
- 12. Networks in economics and business
- 13. Networks in chemistry and physics
- 14. Social networks
- 15. Upper ontologies
- 16. Library metadata ontologies
- 17. Time
- 18. Drawing and serializing graphs
- 19. Graph analytics techniques
- 20. Graph analytics software libraries
- 21. Semantic repositories and how to use them
- 22. Graph databases and how to use them
- 23. Case studies
- Index