Practical Data Science for Information Professionals

David Stuart is an independent information professional and an honorary research fellow at the University of Wolverhampton, and was previously a research fellow at King's College London and the University of Wolverhampton. He regularly publishes in peer-reviewed academic journals and professional journals on information science, metrics, and semantic web technologies. He is author of Practical Ontologies for Information Professionals (2016), Web Metrics for Library and Information Professionals (2014), and Facilitating Access to the Web of Data (2011).

• ContentsFigures Tables Boxes Preface 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 professionalsEight challenges to data scienceTen steps to data science librarianship The final word: playReferences 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

'If libraries and librarians are to be serious about the ‘I’ in LIS, then analysing data to find meaning for our customers will be a core component of the service offering. David Stuart’s book is an excellent entry point to the discipline.'