This two-day workshop will introduce data literacy elements and skills required for working with data through the research process. Day 1 is focused on data management, including the collection and structuring of data to answer a research question and the services that libraries can provide to support campus data curation. Day 2 is focused on the exploration of data, specifically cleaning and visualizing data. Participants will learn best practices and be introduced to new tools along the way.
09:00 | Getting Started - Git |
09:30 | Developing the Research Question |
10:30 | Break |
10:45 | Data Fundamentals |
12:00 | Lunch Break |
1:00 | Working With Data in OpenRefine |
3:30 | Break |
3:45 | Data Services |
4:30 | Closing |
09:00 | About Data Science |
9:30 | Data Wrangling in R |
11:15 | Break |
11:30 | Data Visualization Best Practices |
12:00 | Lunch Break |
1:00 | Data Visualization in Tableau |
3:00 | Break |
3:15 | Saving files - Git and GitHub |
4:00 | Reflections and Plans |
4:30 | Closing |
The Data 'Shop's teaching is hands-on, so participants are encouraged to use their own computers to ensure the proper setup of tools for an efficient workflow. These lessons assume no prior knowledge of the skills or tools, but working through this lesson requires working copies of the software described. To most effectively use these materials, please make sure to download the data and install everything before working through this lesson.
The Data 'Shop,
2018. License. Contributing.
Questions? Feedback?
Please file
an issue on GitHub.
On
Twitter: @123POW