Workshop Resources

Feedback and Topic Suggestion Form
 

In-Person Workshop Materials

1. 3D Modeling in SketchUp
2. ArcGIS Online for Absolute Beginners
3. ArcGIS StoryMaps
4. Building a Better Lit Review with VOSviewer
5. Cleaning Social Science Data with OpenRefine
6. Data Analysis with Stata
7. Data Organization in Spreadsheets (Tidy Data)
8. Gathering Data from the Web Using APIs
9. Introduction to Git and GitHub
10. Multimedia Timelines with Timeline.js
11. Notion for Absolute Beginners
12. Personal Digital Preservation Basics
13. Programming Logic for Non-Programmers
14. Writing Data Management Plans for Federal Funding Agencies
     

Select Recommended Asynchronous Learning Materials

1. Carpentries curriculum pages (free workshop materials for a variety of data and computational skills topics)

   1. Data Carpentry
   2. Software Carpentry
2. Hesburgh Libraries Digital Standards Team Guidelines & Best Practices for Metadata

   1. Accessible PDF Guidelines (2012)
   2. Audio Video Metadata Best Practices (2013)
   3. Digital Processing Standards and Best Practices (2012)
   4. Discovery and User Interface Best Practices (2012)
   5. Metadata Application Profile (2012)
   6. Patent Metadata Best Practices (2013)
   7. Recommended Steps for Digitizing Collections (2012)
   8. Rights Management Guidelines (2012)
   9. Visual Resources Metadata Best Practices (2013)
3. remix.nd.edu (free step-by-step tutorials related to multimedia project skills), e.g.

   1. Podcasting
   2. Research Posters
4. Sage Publishing (free to Notre Dame, online courses of varying lengths/expertise levels), e.g.

   1. Analyze Qualitative Data (5 hours)
   2. Conduct a Literature Review (5 hours)
   3. Plan Your Focus Group (4 hours)
   4. Fundamentals of Quantitative Text Analysis (15 hours–long course)
   5. Introduction to Data Visualization (12 hours–long course)
   6. Introduction to R (20 hours–long course)
   7. Introduction to Python (24 hours–long course)
   8. Working with Transcribed Data (2 hours)
   9. Introduction to Text Mining (10 hours–long course)