Practical data science for information professionals / David Stuart.

Includes bibliographical references and index

Table of contents 1 What is data science?
Data, information, knowledge, wisdom
Data everywhere
The data deserts
Data science
The potential of data science
From research data services to data science in libraries
Programming in libraries
Programming in this book
The structure of this book
2 Little data, big data
Big data
Data formats
Standalone files
Application programming interfaces
Unstructured data
Data sources
Data licences
3 The process of data science
Modelling the data science process Frame the problem
Collect data
Transform and clean data
Analyse data
Visualise and communicate data
Frame a new problem
4 Tools for data analysis
Finding tools
Software for data science
Programming for data science
5 Clustering and social network analysis
Network graphs
Graph terminology
Network matrix
Visualisation
Network analysis
6 Predictions and forecasts
Predictions and forecasts beyond data science
Predictions in a world of (limited) data
Predicting and forecasting for information professionals
Statistical methodologies 7 Text analysis and mining
Text analysis and mining, and information professionals
Natural language processing
Keywords and n-grams
8 The future of data science and information professionals
Eight challenges to data science
Ten steps to data science librarianship
The final word: play
References
Appendix
Programming concepts for data science
Variables, data types and other classes
Import libraries
Functions and methods
Loops and conditionals
Final words of advice
Further reading
Index

The growing importance of data science, and the increasing role of information professionals in the management and use of data, are brought together in Practical Data Science for Information Professionals to provide a practical introduction specifically designed for information professionals. Data science has a wide range of applications within the information profession, from working alongside researchers in the discovery of new knowledge, to the application of business analytics for the smoother running of a library or library services. Practical Data Science for Information Professionals provides an accessible introduction to data science, using detailed examples and analysis on real data sets to explore the basics of the subject. Content covered includes: the growing importance of data science; the role of the information professional in data science; some of the most important tools and methods that information professionals may use; an analysis of the future of data science and the role of the information professional. This book will be of interest to all types of libraries around the world, from large academic libraries to small research libraries. By focusing on the application of open source software, the book aims to reduce barriers for readers to use the lessons learned within

Information Studies Information Studies

Sagar Shahanawaz