Hands On Data Science For Librarians

Author : Sarah Lin,Dorris Scott
Publisher : CRC Press
Page : 199 pages
File Size : 44,9 Mb
Release : 2023-05-09
Category : Business & Economics
ISBN : 9781000863178

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Hands-On Data Science for Librarians by Sarah Lin,Dorris Scott Pdf

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 : David Stuart
Publisher : Facet Publishing
Page : 200 pages
File Size : 46,5 Mb
Release : 2020-07-24
Category : Language Arts & Disciplines
ISBN : 9781783303441

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Practical Data Science for Information Professionals by David Stuart Pdf

Practical Data Science for Information Professionals provides an accessible introduction to a potentially complex field, providing readers with an overview of data science and a framework for its application. It provides detailed examples and analysis on real data sets to explore the basics of the subject in three principle areas: clustering and social network analysis; predictions and forecasts; and text analysis and mining. As well as highlighting a wealth of user-friendly data science tools, the book also includes some example code in two of the most popular programming languages (R and Python) to demonstrate the ease with which the information professional can move beyond the graphical user interface and achieve significant analysis with just a few lines of code. After reading, readers will understand: · 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 can use. Bringing together the growing importance of data science and the increasing role of information professionals in the management and use of data, Practical Data Science for Information Professionals will provide a practical introduction to the topic specifically designed for the information community. It will appeal to librarians and information professionals all around the world, from large academic libraries to small research libraries. By focusing on the application of open source software, it aims to reduce barriers for readers to use the lessons learned within.

Author : Yunfei Du,Hammad Rauf Khan
Publisher : Bloomsbury Publishing USA
Page : 169 pages
File Size : 55,6 Mb
Release : 2020-03-26
Category : Language Arts & Disciplines
ISBN : 9798216071907

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Data Science for Librarians by Yunfei Du,Hammad Rauf Khan Pdf

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 : Yunfei Du,Hammad Rauf Khan
Publisher : Bloomsbury Publishing USA
Page : 181 pages
File Size : 42,5 Mb
Release : 2020-03-26
Category : Language Arts & Disciplines
ISBN : 9781440871221

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Data Science for Librarians by Yunfei Du,Hammad Rauf Khan Pdf

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 : Chirag Shah
Publisher : Cambridge University Press
Page : 459 pages
File Size : 41,9 Mb
Release : 2020-04-02
Category : Business & Economics
ISBN : 9781108472449

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A Hands-On Introduction to Data Science by Chirag Shah Pdf

An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.

Author : Jason Miller
Publisher : SD
Page : 0 pages
File Size : 46,8 Mb
Release : 2024-05-07
Category : Language Arts & Disciplines
ISBN : 9798224533565

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Data Science for Librarians by Jason Miller Pdf

Discover the transformative potential of data science in the world of libraries with this comprehensive guide tailored specifically for librarians seeking to enhance their professional expertise. Delving into the intersection of information science and cutting-edge data analytics, this book equips readers with the knowledge and skills needed to harness the power of data for informed decision-making and innovative service delivery. From understanding the fundamentals of data science to implementing advanced techniques like machine learning and text mining, each chapter offers practical insights and real-world examples that illuminate the path forward. Readers will learn how to collect, clean, and analyze data effectively, uncovering valuable insights that can drive strategic initiatives and optimize library resources. But this book is more than just a technical manual-it's a roadmap for librarians navigating the complexities of the digital age. With a focus on ethical considerations, privacy protection, and staying ahead of emerging trends, it empowers librarians to leverage data responsibly and ethically, ensuring that their practices uphold the core values of librarianship. Whether you're a seasoned professional looking to expand your skill set or a newcomer eager to explore the possibilities of data science, this book is your indispensable companion on the journey to unlocking the full potential of libraries in the 21st century.

Author : David Paper
Publisher : Apress
Page : 247 pages
File Size : 49,5 Mb
Release : 2019-11-16
Category : Computers
ISBN : 9781484253731

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Hands-on Scikit-Learn for Machine Learning Applications by David Paper Pdf

Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised and unsupervised machine learning algorithms. Care is taken to walk you through the principles of machine learning through clear examples written in Python that you can try out and experiment with at home on your own machine. All applied math and programming skills required to master the content are covered in this book. In-depth knowledge of object-oriented programming is not required as working and complete examples are provided and explained. Coding examples are in-depth and complex when necessary. They are also concise, accurate, and complete, and complement the machine learning concepts introduced. Working the examples helps to build the skills necessary to understand and apply complex machine learning algorithms. Hands-on Scikit-Learn for Machine Learning Applications is an excellent starting point for those pursuing a career in machine learning. Students of this book will learn the fundamentals that are a prerequisite to competency. Readers will be exposed to the Anaconda distribution of Python that is designed specifically for data science professionals, and will build skills in the popular Scikit-Learn library that underlies many machine learning applications in the world of Python. What You'll LearnWork with simple and complex datasets common to Scikit-Learn Manipulate data into vectors and matrices for algorithmic processing Become familiar with the Anaconda distribution used in data scienceApply machine learning with Classifiers, Regressors, and Dimensionality Reduction Tune algorithms and find the best algorithms for each dataset Load data from and save to CSV, JSON, Numpy, and Pandas formats Who This Book Is For The aspiring data scientist yearning to break into machine learning through mastering the underlying fundamentals that are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming and very basic applied linear algebra will make learning easier, although anyone can benefit from this book.

Author : Mani, Nandita S.,Cawley, Michelle A.
Publisher : IGI Global
Page : 415 pages
File Size : 46,6 Mb
Release : 2022-05-06
Category : Language Arts & Disciplines
ISBN : 9781799897040

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Handbook of Research on Academic Libraries as Partners in Data Science Ecosystems by Mani, Nandita S.,Cawley, Michelle A. Pdf

Beyond providing space for data science activities, academic libraries are often overlooked in the data science landscape that is emerging at academic research institutions. Although some academic libraries are collaborating in specific ways in a small subset of institutions, there is much untapped potential for developing partnerships. As library and information science roles continue to evolve to be more data-centric and interdisciplinary, and as research using a variety of data types continues to proliferate, it is imperative to further explore the dynamics between libraries and the data science ecosystems in which they are a part. The Handbook of Research on Academic Libraries as Partners in Data Science Ecosystems provides a global perspective on current and future trends concerning the integration of data science in libraries. It provides both a foundational base of knowledge around data science and explores numerous ways academicians can reskill their staff, engage in the research enterprise, contribute to curriculum development, and help build a stronger ecosystem where libraries are part of data science. Covering topics such as data science initiatives, digital humanities, and student engagement, this book is an indispensable resource for librarians, information professionals, academic institutions, researchers, academic libraries, and academicians.

Author : Joel Herndon
Publisher : Unknown
Page : 128 pages
File Size : 52,5 Mb
Release : 2021-08-26
Category : Electronic
ISBN : 1783304596

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Data Science in the Library by Joel Herndon Pdf

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 : Lesley S. J. Farmer,Alan M. Safer
Publisher : Unknown
Page : 192 pages
File Size : 48,6 Mb
Release : 2016-07-27
Category : Libraries
ISBN : 1783301619

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Library Improvement Through Data Analytics by Lesley S. J. Farmer,Alan M. Safer Pdf

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 : Dhamdhere, Sangeeta Namdev
Publisher : IGI Global
Page : 211 pages
File Size : 45,6 Mb
Release : 2020-09-25
Category : Language Arts & Disciplines
ISBN : 9781799830511

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Big Data Applications for Improving Library Services by Dhamdhere, Sangeeta Namdev Pdf

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 : Andrew Weiss
Publisher : Rowman & Littlefield
Page : 219 pages
File Size : 46,5 Mb
Release : 2018-03-15
Category : Language Arts & Disciplines
ISBN : 9781538103241

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Big Data Shocks by Andrew Weiss Pdf

"Big data," as it has become known in business and information technology circles, has the potential to improve our knowledge about human behavior, and to help us gain insight into the ways in which we organize ourselves, our cultures, and our external and internal lives. Libraries stand at the center of the information world, both facilitating and contributing to this flood as well as helping to shape and channel it to specific purposes. But all technologies come with a price. Where the tool can serve a purpose, it can also change the user's behavior to fit the purposes of the tool. Big Data Shocks: An Introduction to Big Data for Librarians and Information Professionals examines the roots of big data, the current climate and rising stars in this world. The book explores the issues raised by big data and discusses theoretical as well as practical approaches to managing information whose scope exists beyond the human scale. What’s at stake ultimately is the privacy of the people who support and use our libraries and the temptation for us to examine their behaviors. Such tension lies deep in the heart of our great library institutions. This book addresses these issues and many of the questions that arise from them, including: What is our role as librarians within this new era of big data? What are the impacts of new powerful technologies that track and analyze our behavior? Do data aggregators know more about us and our patrons than we do? How can librarians ethically balance the need to demonstrate learning and knowledge creation and privacy? Do we become less private merely because we use a tool or is it because the tool has changed us? What's in store for us with the internet of things combining with data mining techniques? All of these questions and more are explored in this book

Author : Amy L. Affelt
Publisher : Unknown
Page : 128 pages
File Size : 53,9 Mb
Release : 2015
Category : Electronic
ISBN : OCLC:1002966977

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The Accidental Data Scientist by Amy L. Affelt Pdf

Author : Ben Showers
Publisher : Facet Publishing
Page : 209 pages
File Size : 54,9 Mb
Release : 2015-04-30
Category : Language Arts & Disciplines
ISBN : 9781856049658

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Library Analytics and Metrics by Ben Showers Pdf

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 : Yasha Hasija,Rajkumar Chakraborty
Publisher : CRC Press
Page : 299 pages
File Size : 47,6 Mb
Release : 2021-04-08
Category : Computers
ISBN : 9781000345483

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Hands on Data Science for Biologists Using Python by Yasha Hasija,Rajkumar Chakraborty Pdf

Hands-on Data Science for Biologists using Python has been conceptualized to address the massive data handling needs of modern-day biologists. With the advent of high throughput technologies and consequent availability of omics data, biological science has become a data-intensive field. This hands-on textbook has been written with the inception of easing data analysis by providing an interactive, problem-based instructional approach in Python programming language. The book starts with an introduction to Python and steadily delves into scrupulous techniques of data handling, preprocessing, and visualization. The book concludes with machine learning algorithms and their applications in biological data science. Each topic has an intuitive explanation of concepts and is accompanied with biological examples. Features of this book: The book contains standard templates for data analysis using Python, suitable for beginners as well as advanced learners. This book shows working implementations of data handling and machine learning algorithms using real-life biological datasets and problems, such as gene expression analysis; disease prediction; image recognition; SNP association with phenotypes and diseases. Considering the importance of visualization for data interpretation, especially in biological systems, there is a dedicated chapter for the ease of data visualization and plotting. Every chapter is designed to be interactive and is accompanied with Jupyter notebook to prompt readers to practice in their local systems. Other avant-garde component of the book is the inclusion of a machine learning project, wherein various machine learning algorithms are applied for the identification of genes associated with age-related disorders. A systematic understanding of data analysis steps has always been an important element for biological research. This book is a readily accessible resource that can be used as a handbook for data analysis, as well as a platter of standard code templates for building models.