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Author: Lesley S. J. Farmer Publisher: ISBN: 9781783301614 Category : Libraries Languages : en Pages : 192
Book Description
This book shows how to act on and make sense of data in libraries. Using a range of techniques, tools and methodologies it explains how data can be used to help inform decision making at every level.Sound data analytics is the foundation for making an evidence-based case for libraries, in addition to guiding myriad organizational decisions, from optimizing operations for efficiency to responding to community needs. Designed to be useful for beginners as well as those with a background in data, this book introduces the basics of a six point framework that can be applied to a variety of library settings for effective system based, data-driven management. Library Improvement Through Data Analytics includes:- the basics of statistical concepts- recommended data sources for various library functions and processes, and guidance for using census, university, or - - government data in analysis- techniques for cleaning data- matching data to appropriate data analysis methods- how to make descriptive statistics more powerful by spotlighting relationships- 14 practical case studies, covering topics such as access and retrieval, digitization, e-book collection development, staffing, facilities, and instruction.This book's clear, concise coverage will enable librarians, archivists, curators and technologists of every experience level to gain a better understanding of statistics in order to facilitate library improvement.
Author: Lesley S. J. Farmer Publisher: ISBN: 9781783301614 Category : Libraries Languages : en Pages : 192
Book Description
This book shows how to act on and make sense of data in libraries. Using a range of techniques, tools and methodologies it explains how data can be used to help inform decision making at every level.Sound data analytics is the foundation for making an evidence-based case for libraries, in addition to guiding myriad organizational decisions, from optimizing operations for efficiency to responding to community needs. Designed to be useful for beginners as well as those with a background in data, this book introduces the basics of a six point framework that can be applied to a variety of library settings for effective system based, data-driven management. Library Improvement Through Data Analytics includes:- the basics of statistical concepts- recommended data sources for various library functions and processes, and guidance for using census, university, or - - government data in analysis- techniques for cleaning data- matching data to appropriate data analysis methods- how to make descriptive statistics more powerful by spotlighting relationships- 14 practical case studies, covering topics such as access and retrieval, digitization, e-book collection development, staffing, facilities, and instruction.This book's clear, concise coverage will enable librarians, archivists, curators and technologists of every experience level to gain a better understanding of statistics in order to facilitate library improvement.
Author: Ben Showers Publisher: Facet Publishing ISBN: 1856049655 Category : Language Arts & Disciplines Languages : en Pages : 209
Book Description
This book will inform and inspire librarians, archivists, curators and technologists to make better use of data to help inform decision-making, the development of new services and the improvement of the user experience. With the wealth of data available to library and cultural heritage institutions, analytics are the key to understanding their users and improving the systems and services they offer. Using case studies to provide real-life examples of current developments and services, and packed full of practical advice and guidance for libraries looking to realize the value of their data, this will be an essential guide for librarians and information professionals. Library Analytics and Metrics brings together a group of internationally recognized experts to explore some of the key issues in the exploitation of data analytics and metrics in the library and cultural heritage sectors, including: The role of data in helping inform collections management and strategy Approaches to collecting, analyzing and utilizing data Using analytics to develop new services and improve the user experience Using ethnographic methodologies to better understand user behaviours The opportunities of library data as ‘big data’ The role of ‘small data’ in delivering meaningful interventions for users Practical advice on managing the risks and ethics of data analytics How analytics can help uncover new types of impact and value for institutions and organizations. Readership: This book will be an invaluable resource for librarians and library directors interested in developing a data-driven approach to their service provision and decision making; students on library and information science courses; and managers and practitioners in other cultural heritage sectors such as museums, archives and galleries.
Author: Yunfei Du Publisher: Bloomsbury Publishing USA ISBN: Category : Language Arts & Disciplines Languages : en Pages : 169
Book Description
This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries. Data Science for Librarians introduces data science to students and practitioners in library services. Writing for academic, public, and school library managers; library science students; and library and information science educators, authors Yunfei Du and Hammad Rauf Khan provide a thorough overview of conceptual and practical tools for data librarian practice. Partially due to how quickly data science evolves, libraries have yet to recognize core competencies and skills required to perform the job duties of a data librarian. As society transitions from the information age into the era of big data, librarians and information professionals require new knowledge and skills to stay current and take on new job roles, such as data librarianship. Such skills as data curation, research data management, statistical analysis, business analytics, visualization, smart city data, and learning analytics are relevant in library services today and will become increasingly so in the near future. This text serves as a tool for library and information science students and educators working on data science curriculum design.
Author: Dhamdhere, Sangeeta Namdev Publisher: IGI Global ISBN: 1799830519 Category : Language Arts & Disciplines Languages : en Pages : 211
Book Description
Today, libraries must provide various web-based services, social media, and internet to patrons in order to adequately support their information needs. In addition to these services, the maintenance of online literature, databases, data sets, and archives cause librarians to have to handle huge amounts of data each day. Big data can support with quality improvement and problem solving to improve library services and can help librarians to provide up-to-date and innovative real-time services to library users. Big Data Applications for Improving Library Services is an essential scholarly publication that examines the implications and applications of big data analytics on services provided by libraries. Highlighting a wide range of topics such as data analytics, mobile technologies, and web-based services, this book is ideal for librarians, knowledge managers, data scientists, data analysts, cataloguers, academicians, IT professionals, researchers, and students.
Author: Joel Herndon Publisher: ISBN: 9781783304592 Category : Languages : en Pages :
Book Description
This book explores the rapid expansion of data sources, visualizations, and analytics created in the last decade and explores the strategies, tools, and approaches that educators and information specialists are employing to train a new generation of data professionals.
Author: Singh, Amandeep Publisher: IGI Global ISBN: 1799872335 Category : Business & Economics Languages : en Pages : 310
Book Description
The availability of big data, low-cost commodity hardware, and new information management and analytic software have produced a unique moment in the history of data analysis. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability especially in digital marketing. Data plays a huge role in understanding valuable insights about target demographics and customer preferences. From every interaction with technology, regardless of whether it is active or passive, we are creating new data that can describe us. If analyzed correctly, these data points can explain a lot about our behavior, personalities, and life events. Companies can leverage these insights for product improvements, business strategy, and marketing campaigns to cater to the target customers. Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing aids understanding of big data in terms of digital marketing for meaningful analysis of information that can improve marketing efforts and strategies using the latest digital techniques. The chapters cover a wide array of essential marketing topics and techniques, including search engine marketing, consumer behavior, social media marketing, online advertising, and how they interact with big data. This book is essential for professionals and researchers working in the field of analytics, data, and digital marketing, along with marketers, advertisers, brand managers, social media specialists, managers, sales professionals, practitioners, researchers, academicians, and students looking for the latest information on how big data is being used in digital marketing strategies.
Author: Robin Rice Publisher: Facet Publishing ISBN: 1783300477 Category : Language Arts & Disciplines Languages : en Pages : 193
Book Description
An insider’s guide to data librarianship packed full of practical examples and advice for any library and information professional learning to deal with data. Interest in data has been growing in recent years. Support for this peculiar class of digital information – its use, preservation and curation, and how to support researchers’ production and consumption of it in ever greater volumes to create new knowledge, is needed more than ever. Many librarians and information professionals are finding their working life is pulling them toward data support or research data management but lack the skills required. The Data Librarian’s Handbook, written by two data librarians with over 30 years’ combined experience, unpicks the everyday role of the data librarian and offers practical guidance on how to collect, curate and crunch data for economic, social and scientific purposes. With contemporary case studies from a range of institutions and disciplines, tips for best practice, study aids and links to key resources, this book is a must-read for all new entrants to the field, library and information students and working professionals. Key topics covered include: • the evolution of data libraries and data archives • handling data compared to other forms of information • managing and curating data to ensure effective use and longevity • how to incorporate data literacy into mainstream library instruction and information literacy training • how to develop an effective institutional research data management (RDM) policy and infrastructure • how to support and review a data management plan (DMP) for a project, a key requirement for most research funders • approaches for developing, managing and promoting data repositories • handling and sharing confidential or sensitive data • supporting open scholarship and open science, ensuring data are discoverable, accessible, intelligible and assessable. This title is for the practising data librarian, possibly new in their post with little experience of providing data support. It is also for managers and policy-makers, public service librarians, research data management coordinators and data support staff. It will also appeal to students and lecturers in iSchools and other library and information degree programmes where academic research support is taught.
Author: Joel Herndon Publisher: ISBN: 9781783304608 Category : Big data Languages : en Pages : 0
Book Description
This book considers the current environment for data driven research, instruction, and consultation from a variety of faculty and library perspectives and suggests strategies for engaging with the tools and methods of data driven research.
Author: Sarah Lin Publisher: CRC Press ISBN: 1000863174 Category : Business & Economics Languages : en Pages : 199
Book Description
Librarians understand the need to store, use and analyze data related to their collection, patrons and institution, and there has been consistent interest over the last 10 years to improve data management, analysis, and visualization skills within the profession. However, librarians find it difficult to move from out-of-the-box proprietary software applications to the skills necessary to perform the range of data science actions in code. This book will focus on teaching R through relevant examples and skills that librarians need in their day-to-day lives that includes visualizations but goes much further to include web scraping, working with maps, creating interactive reports, machine learning, and others. While there’s a place for theory, ethics, and statistical methods, librarians need a tool to help them acquire enough facility with R to utilize data science skills in their daily work, no matter what type of library they work at (academic, public or special). By walking through each skill and its application to library work before walking the reader through each line of code, this book will support librarians who want to apply data science in their daily work. Hands-On Data Science for Librarians is intended for librarians (and other information professionals) in any library type (public, academic or special) as well as graduate students in library and information science (LIS). Key Features: Only data science book available geared toward librarians that includes step-by-step code examples Examples include all library types (public, academic, special) Relevant datasets Accessible to non-technical professionals Focused on job skills and their applications
Author: Lesley S. J. Farmer
Author: Lesley S. J. Farmer
Author: Ben Showers
Author: Yunfei Du
Author: Dhamdhere, Sangeeta Namdev
Author: Joel Herndon
Author: Singh, Amandeep
Author: Robin Rice
Author: Joel Herndon
Author: Sarah Lin
Author: Douglas Cook