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1. Data visualization

   San Francisco, CA : Wiley, [2013]

   This issue delivers concrete suggestions for optimally using data visualization in evaluation, as well as suggestions for best practices in data visualization design. It focuses on specific quantitative and qualitative data visualization approaches that include data dashboards, graphic recording, and geographic information systems (GIS). Readers will get a step-by-step process for designing an effective data dashboard system for programs and organizations, and various suggestions to improve their utility. The next section illustrates the role that graphic recording can play in helping programs and evaluators understand and communicate the mission and impact that an intervention is having in a democratic and culturally competent way. The GIS section provides specific examples of how mapped data can be used to understand program implementation and effectiveness, and the influence that the environment has on these outcomes. * Discusses best practices that inform and shape our data visualization design choices * Highlights the best use of each tool/approach * Provides suggestions for effective practice * Discuss the strengths and limitations of each approach in evaluation practice This is the 140th volume of the Jossey-Bass quarterly report series New Directions for Evaluation, an official publication of the American Evaluation Association.Do you communicate data and information to stakeholders? This issue is Part 1 of a two-part series on data visualization and evaluation. In Part 1, we introduce recent developments in the quantitative and qualitative data visualization field and provide a historical perspective on data visualization, its potential role in evaluation practice, and future directions. It discusses: Quantitative visualization methods such as tree maps Sparklines Web-based interactive visualization Different types of qualitative data visualizations, along with examples in various evaluation contexts A toolography describing additional data visualization tools and software, along with their major strengths and limitations. Intended as a guidance for understanding and designing data visualizations, this issue introduces fundamental concepts and links them to daily practice. This is the 139 th volume of the Jossey-Bass quarterly report series New Directions for Evaluation , an official publication of the American Evaluation Association.

2. Data visualization : principles and practice

   Telea, Alexandru, 1972-

   Second edition. - Boca Raton, FL : CRC Press, [2015]

   "This book explores the study of processing and visually representing data sets. Data visualization is closely related to information graphics, information visualization, scientific visualization, and statistical graphics. This second edition presents a better treatment of the relationship between traditional scientific visualization and information visualization, a description of the emerging field of visual analytics, and updated techniques using the GPU and new generations of software tools and packages. This edition is also enhanced with exercises and downloadable code and data sets"--Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration with third-party code, and more. Focusing on those techniques and methods with the broadest applicability across fields, the second edition of Data Visualization: Principles and Practice provides a streamlined introduction to various visualization techniques. The book illustrates a wide variety of applications of data visualizations, illustrating the range of problems that can be tackled by such methods, and emphasizes the strong connections between visualization and related disciplines such as imaging and computer graphics. It covers a wide range of sub-topics in data visualization: data representation; visualization of scalar, vector, tensor, and volumetric data; image processing and domain modeling techniques; and information visualization. See What's New in the Second Edition: Additional visualization algorithms and techniques New examples of combined techniques for diffusion tensor imaging (DTI) visualization, illustrative fiber track rendering, and fiber bundling techniques Additional techniques for point-cloud reconstruction Additional advanced image segmentation algorithms Several important software systems and libraries Algorithmic and software design issues are illustrated throughout by (pseudo)code fragments written in the C++ programming language. Exercises covering the topics discussed in the book, as well as datasets and source code, are also provided as additional online resources.

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3. Data visualization : a practical introduction

   Healy, Kieran Joseph, 1973-

   Princeton ; Oxford : Princeton University Press, [2019]

   "[This book] builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this...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."--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.

Your search also found 6 topic specific databases.

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1. Urban Studies

2. Learning and Using R at Stanford

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5. Digital Humanities

6. Religious studies

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8. Resource Guide for CISAC Honor Thesis Research

9. Resource Guide for Program in International Relations Honor Thesis Research

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Library info; guides & content by subject specialists

1. Native American Studies

   Stanford Libraries' American History collections include print and online materials for the study of American history, and extensive photographic, archival, and rare books collections.

2. Art, Art History, Architecture

   Stanford Libraries' collections in Art and Architecture include print and digital materials for the study of art history, art, architecture, design, and related interdisciplinary fields, and archives, digital images, and special collections materials.

3. Love Data Week Fair 2024

Digital showcases for research and teaching.

1. 

   Data Visualization and the Modern Imagination

Geospatial content, including GIS datasets, digitized maps, and census data.

1. Anti-Eviction Mapping Project

   2020

   The Anti-Eviction Mapping Project is a data-visualization, data analysis, and storytelling collective documenting dispossession and resistance upon...

2. Calls for Service in New Orleans, LA, 2017

   2017

   This point shapefile represents Calls for Service for New Orleans, LA in 2017. This dataset reflects incidents that have been reported to the New O...