This book constitutes the thoroughly refereed proceedings of the 16th Italian Research Conference on Digital Libraries, IRCDL 2020, held in Bari, Italy, in January 2020. The 12 full papers and 6 short papers presented were carefully selected from 26 submissions. The papers are organized in topical sections on information retrieval, bid data and data science in DL; cultural heritage; open science.
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
How should historians speak truth to power – and why does it matter? Why is five hundred years better than five months or five years as a planning horizon? And why is history – especially long-term history – so essential to understanding the multiple pasts which gave rise to our conflicted present? The History Manifesto is a call to arms to historians and everyone interested in the role of history in contemporary society. Leading historians Jo Guldi and David Armitage identify a recent shift back to longer-term narratives, following many decades of increasing specialisation, which they argue is vital for the future of historical scholarship and how it is communicated. This provocative and thoughtful book makes an important intervention in the debate about the role of history and the humanities in a digital age. It will provoke discussion among policymakers, activists and entrepreneurs as well as ordinary listeners, viewers, readers, students and teachers. This title is also available as Open Access.
This book gathers a selection of peer-reviewed papers presented at the second Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020) conference, held in Shanghai, China, on 28–29 December 2020. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.
Faced with increased budget cuts, libraries must continue to advance their services through new technologies and practices in order to keep pace with the rapid changes society is currently facing. The once traditional in-person services offered can no longer be the only option, and to keep themselves afloat, libraries must offer more in terms of digital services. The convenience of offering mobile and digital services brings a new wave of accessibility to libraries and a new question on just how much libraries will need to change to meet the newfound needs of its patrons. Beyond offering these digital services, libraries are incorporating other types of technology in multifaceted ways such as utilizing artificial intelligence practices, social media, and big data management. Moreover, libraries are increasingly looking for ways to partner and collaborate with the community, faculty, students, and other libraries in order to keep abreast of the best practices and needs of their users. The Research Anthology on Collaboration, Digital Services, and Resource Management for the Sustainability of Libraries explores emerging strategies and technologies that are redefining the role of the library within communities and academia. This reference book covers extensive ground on all the ways libraries have shifted to manage their resources, digitalize their services, and market themselves within the new technological revolution. These continued shifts for libraries come with benefits, challenges, and future projections that are critical for discussion as libraries continue to strive to remain updated and relevant in times of change. This book is ideal for librarians, archivists, collection managers, IT specialists, electronic resource librarians, practitioners, stakeholders, researchers, academicians, and students who are interested in the current state of libraries and how they are transforming to fit modern needs.
Information and records management has been an important part of society for establishing procedures to effectively manage information. As technology has increased in society, this essential function has been impacted as well. With the onset of technological tools brought upon by the fourth industrial revolution, technologies such as artificial intelligence, the internet of things, big data, and more have changed the face of information and records management. These technologies and tools have paved new ways for security, efficiency in timely processes, new ways to create and process records, and other beneficial traits. Along with these advancements come new contemporary issues, leading to the need for research on how exactly information records management is functioning in modern times, the technologies brought on by the fourth industrial revolution, and both the benefits and challenges to this transition. The Handbook of Research on Information and Records Management in the Fourth Industrial Revolution showcases contemporary issues and demonstrates the value of information and records management in the fourth industrial revolution. The book provides a summary of the key activities undertaken by information and records managers as they seek to make records and information management more visible in the modern knowledge-driven society. The chapters highlight innovation, the use of information and communication technology in information and records management, best practices, challenges encountered, and how they are overcome. The target audience of this book will be composed of professionals, librarians, archivists, lecturers, and researchers working in the field of library and information science, along with practitioners, academicians, and students interested in information and records management in the 21st century.
In this book, Xiaoqun Zhang argues that acquiring knowledge of machine learning (ML) and artificial intelligence (AI) tools is increasingly imperative for the trajectory of communication research in the era of big data. Rather than simply being a matter of keeping pace with technological advances, Zhang posits that these tools are strategically imperative for navigating the complexities of the digital media landscape and big data analysis, and they provide powerful methodologies empowering researchers to uncover nuanced insights and trends within the vast expanse of digital information. Although this can be a daunting notion for researchers without a formal background in mathematics or computer science, this book highlights the substantial rewards of investing time and effort into the endeavor – mastery of ML and AI not only facilitates more sophisticated big data analyses, but also fosters interdisciplinary collaborations, enhancing the richness and depth of research outcomes. This book will serve as a foundational resource for communication scholars by providing essential knowledge and techniques to effectively leverage ML and AI at the intersection of communication research and data science.
