The Data Literacy Cookbook

Description

Today’s students create and are confronted with many kinds of data in multiple formats. Data literacy enables students and researchers to access, interpret, critically assess, manage, handle, and ethically use data.
The Data Literacy Cookbook includes a variety of approaches to and lesson plans for teaching data literacy, from simple activities to self-paced learning modules to for-credit and discipline-specific courses. Sixty-five recipes are organized into nine sections based on learning outcomes:

Interpreting Polls and Surveys

Finding and Evaluating Data

Data Manipulation and Transformation

Data Visualization

Data Management and Sharing

Geospatial Data

Data in the Disciplines

Data Literacy Outreach and Engagement

Data Literacy Programs and Curricula 

Many sections have overlapping learning outcomes, so you can combine recipes from multiple sections to whip up a scaffolded curriculum. The Data Literacy Cookbook provides librarians with lesson plans, strategies, and activities to help guide students as both consumers and producers in the data life cycle. Kelly Getz is an Associate Professor and S.T.E.M. Librarian at Eastern Michigan University. She holds a BA in Chemistry from Michigan State University, and both a Master of Science of Information and a Master of Science in Bioinformatics from the University of Michigan. Prior to becoming an academic librarian in 2013, she was a high school chemistry and environmental science teacher. Her teaching philosophy, in brief, is: do things to foster curiosity and no things to harm it. Kelly’s research interests include information and data literacy in secondary and post-secondary education, inclusive design in libraries, and many other sciencey rabbit holes. Outside of the library, she dedicates her life, love, time, and everything to Juni, Lionel, and Boyd; together with whom she will always make (and eat) the messiest cookies.
Meryl Brodsky is the liaison librarian for the School of Information and the Moody College of Communication at the University of Texas – Austin. She has a Master of Library Science from Southern Connecticut State University and an MBA from Cornell University. Her research interests include data literacy, data management, and data curation. She has spent half her career working as a corporate librarian and half as an academic librarian. It was her work in the corporate sector that sparked her interest in data literacy. She witnessed her co-workers doing terrible things to data and returned to the academic sector to become involved in data literacy education. Table of Contents
Introduction
 
Section 1. Interpreting Polls and Surveys
Ch1. Survey Literacy: A Skills-Based Approach to Teaching Survey Research
Jesse Klein
 
Ch2. Setting the Scene with Surveys: Using Polling Software to Demonstrate Primary and Secondary Data
Wendy G. Pothier
 
Ch3. The Mini-study: A Three-Part Assignment for Original Data Creation, Summation, and Visualization
William Cuthbertson, Lyda Fontes McCartin, and Sara O’Donnell
 
Section 2. Finding and Evaluating Data
Ch4. Three-Step Data Searching
Annelise Sklar
 
Ch5. Transforming Research Questions into Variables: A Recipe for Finding Secondary Data
Alicia Kubas and Jenny McBurney
 
Ch6. Sweeten the Search: Discover Data for Reuse with a Tool That Links Publications to the Underlying Data
Elizabeth Moss
 
Ch7. The Most Vital Statistics: Finding and Analyzing Historical Mortality Rates
Alisa Beth Rod and Jennie Correia
 
Ch8. Understanding the Enumerated World: Making Sense of Data as an Information Source
Alexandra Cooper, Elizabeth Hill, and Kristi Thompson
 
Ch9. Looking at Data
Kay K. Bjornen
 
Ch10. Interrogating the Data: What Data Sets Can and Cannot Tell Us
Kristin Fontichiaro
 
Ch11. Data Zines: A Hands-On Approach to Community Curiosities
Tess Wilson
 
Ch12. On the Hunt: Understanding and Analyzing GSS Data Extraction for Incorporation within Sociological Research Projects
Amy Dye-Reeves
 
Ch13. Using Statistics to Define the Problem: Data and Service Learning
Amy Harris Houk and Jenny Dale
 
Ch14. Data and Statistics in the News and Media
Kaetlyn Phillips
 
Section 3. Data Manipulation and Transformation
Ch15. A Kinesthetic Approach to Data: Moving to Understand Nominal, Ordinal, Interval, and Ratio Relationship in Data
Wendy Stephens
 
Ch16. Text Mining Charcuterie Board
Yun Dai and Fan Luo
 
Ch17. Anyone Can Cook (R)! Open Data with R, a Five-Week Mini-mester
Jay Forrest and Ameet Doshi
 
Ch18. Software Carpentry Al Dente: Rendering Tech Training for Online Artisans
Peace Ossom-Williamson, Shiloh Williams, and Hammad Rauf Khan
 
Ch19. A Recipe for Improving Online Instruction for the Carpentries
Kay K. Bjornen and Clarke Iakovakis
 
Section 4. Data Visualization
Ch20. Correlation Does Not Equal Causality: Introducing Data Literacy through Infographics and Statistics in the Media
Nick Ruhs
 
Ch21. Pies, Bars, Charts, and Graphs, Oh My! A Data Visualization Appetizer
Haley L. Lott
 
Ch22. Data Visualizations: The Good, the Bad, and the Ugly
Kaetlyn Phillips
 
Ch23. Seasonal Visual Literacy: Using Current Events to Teach Data and Spatial Literacy Skills with Adaptable LibGuides
Jacqueline Fleming and Theresa Quill
 
Ch24. To Visualize Is to Experience Data
Chelsea H. Barrett and Gerard Shea
 
Ch25. Upping the Baseline for Data Literacy Instruction
Jessica Vanderhoff
 
Ch26. A Literacy-Based Approach to Learning Visualization with R’s ggplot2 Package
Angela M. Zoss
 
Ch27. Build Your Own Data Viz Pizza: A Modular Approach to Data Visualization Instruction
Rachel Starry
 
Ch28. Veggie Pizza: Choosing a Data Visualization Tool
Rachel Starry
 
Ch29. Four-Cheese Pizza: Color and Accessible Design
Rachel Starry
 
Ch30. Data Visualization using Web Apps in a Rainbow Layer Cake
Yun Dai and Fan Luo
 
Ch31. Graphical Abstracts: Creating Appetizing Infographics for Your Research Article
Aleshia Huber
 
Section 5. Data Management and Sharing
Ch32. Making File Names for Digital Exhibits
Kate Thornhill and Gabriele Hayden
 
Ch33. Data Management Failures: Teaching the Importance of DMPs through Cautionary Examples
Richard M. Mikulski
 
Ch34. Low-Fat Research Data Management
Elizabeth Blackwood
 
Ch35. Managing Qualitative Social Science Data: An Open, Self-Guided Course
Sebastian Karcher and Diana Kapiszewski
 
Ch36. Seven Weeks, Seven DMPs: Iterative Learning around Data Management Plan Creation
Emma Slayton and Hannah C. Gunderman
 
Ch37. Equitable from the Beginning: Incorporating Critical Data Perspectives into Your Research Design
Jodi Coalter, David Durden, and Leigh Amadi Dunewood
 
Section 6. Geospatial Data
Ch38. Challenge Accepted: Introducing Geospatial Data Literacy through an Online Learning Path
Joshua Sadvari and Katie Phillips
 
Ch39. GIS for Success Series: Learning the Basics of QGIS Workshop
Kelly Grove
 
Ch40. GIS for Success Series: Let’s Make a Map in QGIS Workshop
Kelly Grove
 
Ch41. Statistical and Geospatial Literacy for Integrative Genetics
Jay Forrest and Chrissy Spencer
 
Ch42. Web Map Layer Cake: Teaching Web Mapping Skills with Leaflet for R
Sarah Zhang and Julie Jones
 
Section 7. Data in the Disciplines
Ch43. Data in Context: How Data Fit into the Scholarly Conversation
Theresa Burress
 
Ch44. Let the Dough Rise! Integrating Library Instruction in a Digital Humanities Course
René Duplain and Chantal Ripp
 
Ch45. Ethics and Biodiversity Data
Rebecca Hill Renirie
 
Ch46. Data Decisions and the Research Process in the Sciences and Social Sciences
Nicole Helregel
 
Ch47. Financial Data for Economics Students
Jennifer Yao Weinraub
 
Ch48. Stuffed Shiny App with Business Intelligence
Yun Dai and Fan Luo
 
Ch49. Fast Casual Marketing Strategies
Juliann Couture, Halley Todd, and Natalia Tingle Dolan
 
Ch50. When and Where: A Framework for Finding and Evaluating Social Science Data for Reuse
Ari Gofman
 
Ch51. Data Literacy Layered Lasagna for Preservice Teachers
Brad Dennis and Allison Hart-Young
 
Section 8. Data Literacy Outreach and Engagement
Ch52. Data Visualization Day: Promoting Data Literacy with Campus Partners
Wenli Gao
 
Ch53. Getting Messy Ourselves: An Experiential Learning Curriculum for Subject Librarians to Engage with Data Literacy
Adrienne Canino
 
Ch54. Research Data Management Stone Soup: Gauging Team Competencies
Michelle Armstrong, Megan Davis, Ellie Dworak, Yitzhak “Yitzy” Paul, and Elisabeth Shook
 
Ch55. Data Literacy Family Style: Full-Day Professional Development
Molly Ledermann, Emilia Marcyk, Terence O’Neill, and Dianna E. Sachs
 
Ch56. Everyone Is Welcome at the Table: Outreach for Data Management and Data Literacy in Research Assignment Design
Shannon Sheridan and Hilary Baribeau
 
Ch57. Seasoning and Simmering: Cultivating Data Literacy Skills through an Open Data Hackathon
Peace Ossom-Williamson
 
Ch58. From Soup to Nuts: Finding Your Way around the Data Services Buffet
Jane Fry and Chantal Ripp
 
Ch59. Teaching Data Literacy and Computational Thinking in Educational Technology
Lesley S. J. Farmer
 
Section 9. Data Literacy Programs and Curricula
Ch60. Cooking Up a Data Literacy Course
Claire Nickerson
 
Ch61. Baking a Data Layer Cake: Scaffolding Data Skills through Video Vignettes
Shannon Sheridan
 
Ch62. Building Data Literacy through Scaffolded Workshops: Experiences and Challenges
Jiebei Luo and Yaqing (Allison) Xu
 
Ch63. Data Literacy Appetizers: LibGuide Data Instruction Modules for Undergraduates
Beth Hillemann and Aaron Albertson
 
Ch64. Data as Curation: Framing Data Creation as a Critical Practice through Collections-Based Research Inquiry
Gesina A. Phillips, Tyrica Terry Kapral,
Matthew J. Lavin, and Aaron Brenner
 
Ch65. Quantitative Data Skills for Undergraduates: A Seminar Series for Social Science Students
Whitney Kramer and Amelia Kallaher
 

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