This introductory text presents basic principles of social science research through maps, graphs, and diagrams. The authors show how concept maps and mind maps can be used in quantitative, qualitative, and mixed methods research, using student-friendly examples and classroom-based activities. Integrating theory and practice, chapters show how to use these tools to plan research projects, "see" analysis strategies, and assist in the development and writing of research reports.

Rachel Dorothy Tanur (1958-2002) wasn't trained as a social scientist, but she cared deeply about people and their lives and was an acute observer of living conditions and interactions. Her profound empathy for others and her commitment to helping those less fortunate than herself accompanied her on her travels and often guided her photography. She delighted in capturing the interaction between people and the artifacts they created and used, which, of course, are the raw materials of social science. In 1999 Tanur was diagnosed with cancer, and in response, she made several trips to Cuba, South and Central America, Africa, and Europe, as well as across the United States, before her death at the age of 43. The following year, Tanur's family and friends organized a memorial exhibit at Gilda's Club in New York called Cancer Journeys. The Social Science Research Council then opened its space for second show entitled Photographic Journeys. When Nikita Pokrovsky of Moscow's State University-Higher School of Economics experienced the SSRC exhibit, he was struck by the "human passion and compassion" of Tanur's work. He suggested combining the photographs with commentary, transforming the photos into useful tools for visual social science. These commentaries, written by an international group of social scientists, now accompany close to fifty of Rachel's photographs, and together the exhibit made its debut at the National Science Foundation in their Art of Science's 2006 show, Visualizing Social Science. This volume is an extension of that exhibition.

The representation of abstract data and ideas can be a difficult and tedious task to handle when learning new concepts; however, the advances in emerging technology have allowed for new methods of representing such conceptual data. Information Visualization Techniques in the Social Sciences and Humanities is a critical scholarly resource that examines the application of information visualization in the social sciences and humanities. Featuring coverage on a broad range of topics such as social network analysis, complex systems, and visualization aesthetics, this book is geared towards professionals, students, and researchers seeking current research on information visualization.

An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions

This book presents a methodology for visualizing large scientific domains. Authors Moya-Anegón and Vargas-Queseda create science maps, so-called "scientograms", based on the interactions between authors and their papers through citations and co-citations, using approaches such as domain analysis, social networks, cluster analysis and pathfinder networks. The resulting scientograms offer manifold possibilities.

Today we are witnessing an increased use of data visualization in society. Across domains such as work, education and the news, various forms of graphs, charts and maps are used to explain, convince and tell stories. In an era in which more and more data are produced and circulated digitally, and digital tools make visualization production increasingly accessible, it is important to study the conditions under which such visual texts are generated, disseminated and thought to be of societal benefit. This book is a contribution to the multi-disciplined and multi-faceted conversation concerning the forms, uses and roles of data visualization in society. Do data visualizations do 'good' or 'bad'? Do they promote understanding and engagement, or do they do ideological work, privileging certain views of the world over others? The contributions in the book engage with these core questions from a range of disciplinary perspectives.

This book addresses key issues concerning visualization in the teaching and learning of science at any level in educational systems. It is the first book specifically on visualization in science education. The book draws on the insights from cognitive psychology, science, and education, by experts from five countries. It unites these with the practice of science education, particularly the ever-increasing use of computer-managed modelling packages.

Science maps that can help us understand and navigate the immense amount of results generated by today's science and technology. Cartographic maps have guided our explorations for centuries, allowing us to navigate the world. Science maps have the potential to guide our search for knowledge in the same way, allowing us to visualize scientific results. Science maps help us navigate, understand, and communicate the dynamic and changing structure of science and technology—help us make sense of the avalanche of data generated by scientific research today. Atlas of Science, featuring more than thirty full-page science maps, fifty data charts, a timeline of science-mapping milestones, and 500 color images, serves as a sumptuous visual index to the evolution of modern science and as an introduction to “the science of science”—charting the trajectory from scientific concept to published results. Atlas of Science, based on the popular exhibit, “Places & Spaces: Mapping Science”, describes and displays successful mapping techniques. The heart of the book is a visual feast: Claudius Ptolemy's Cosmographia World Map from 1482; a guide to a PhD thesis that resembles a subway map; “the structure of science” as revealed in a map of citation relationships in papers published in 2002; a visual periodic table; a history flow visualization of the Wikipedia article on abortion; a globe showing the worldwide distribution of patents; a forecast of earthquake risk; hands-on science maps for kids; and many more. Each entry includes the story behind the map and biographies of its makers. Not even the most brilliant minds can keep up with today's deluge of scientific results. Science maps show us the landscape of what we know.

This introductory text presents basic principles of social science research through maps, graphs, and diagrams. The authors show how concept maps and mind maps can be used in quantitative, qualitative, and mixed methods research, using student-friendly examples and classroom-based activities. Integrating theory and practice, chapters show how to use these tools to plan research projects, “see” analysis strategies, and assist in the development and writing of research reports.

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.