Graphs are about connections, and are an important part of our connected and data-driven world. A Librarians 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.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Technology
Zielgruppe
Maße
Höhe: 234 mm
Breite: 156 mm
ISBN-13
978-1-78063-434-0 (9781780634340)
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Schweitzer Klassifikation
James Powell is employed at Los Alamos National Laboratory in the Lab's Research Library. As a Research Technologist at the Lab, he has worked on a variety of information technology products both within and outside the library. James has published papers on libraries and information technology, is the author of HTML Plus! And has contributed to several other books. This is his first book with Chandos Publishing.
Autor*in
Los Alamos National Laboratory, Los Alamos, NM, USA
Graphs in theory; Science of networks; Networks in biology and bioinformatics; Networks in life sciences; Networks in economics; Networks in chemistry and physics; Networks in social Sciences; Library networks: Co-authorship and citation graphs; Dynamical networks: The next frontier; Graph tools: Rendering topologies; Graph analysis libraries; Network solutions to information problems; Semantic graphs and the semantic web.
