Data Curious? Stop by our data tables (see what we did there?) to find out more about data curation assistance, options for data sharing, help with data management and sharing plans, data discovery, and more!
Hunt Library, Monday, February 12, 9am-11am
Sorrells Library, Wednesday, February 14, 1pm-3pm
If you have questions about data, from finding materials to analyzing data to sharing your research, the Libraries can help. Reach out to:
The theme of this year’s love data week is “My Kind of Data”. CMU Libraries is excited to help all students, faculty, and staff who are engaging with different kinds of data to understand, use, communicate, and code with it. The following workshops will offer hands-on experience in working with and manipulating data. Anyone who attends one (or more) workshops will earn a unique badge to certify their attendance and skill training.
IN PERSON: Building Your Programming Toolbox: Version Control with Git (1:00pm)
This workshop is for those beginning to explore the concept of version control, as well as anyone seeking to refine their skills. Git is a version control system that lets you manage and track changes to files on your computer through the command line interface. Topics covered will include configuring a local repository on your computer, modifying files and committing changes, and exploring version histories.
VIRTUAL: Text Mining with TDM Studio Workbench: An Introduction (3:30pm)
In this 1-hour workshop, TDM Studio experts will provide an overview of what TDM Studio is and how to get started with TDM Studio Workbench for your research project. You will have the opportunity to create a dataset related to your research topic and to begin analyzing that dataset within TDM Studio. We will use and run sample Jupyter Notebooks, written in Python, to look at word counts and word co-occurrences in your project dataset. No coding experience is needed
VIRTUAL: Data Storytelling (9:00am)
When working with data, the ways in which we communicate about or discuss analysis is as important as the act of research itself. A large part of being able to effectively use data is to understand what stories are contained within data sets, and what information may play a key role in analysis. In this workshop, we will go over strategies to develop research questions tied to specific data sets, identify core elements of data that may lead to successful and fruitful analysis, as well as how to use both data and results from analysis to communicate ideas to academic and public audiences.
VIRTUAL: Introduction to Electronic Lab Notebooks (10:00am)
Join us for a demonstration on LabArchives ELN. LabArchives is a cloud-based platform that you can use to securely store, search, share and publish your research and data. As a Carnegie Mellon affiliate, you have free access to the platform. We’ll go over notebook creation and access, adding and managing data, and other features to help integrate LabArchives into your team's workflow.
VIRTUAL: Qualitative Research Design (12:00pm)
This workshop is part of the Qualitative Research series. This workshop discusses the fundamentals of Qualitative Research Design and gives an introduction to how to conduct a qualitative research data collection and analysis.
Wednesday Feb. 14th
VIRTUAL: Introduction to R Part 1: Getting started with R and RStudio (9:00am)
This 2-part introductory workshop aims to teach basic concepts, skills, and tools for working with data in R so that you can get more done in less time, and apply concepts of reproducibility to your research. This is an introduction to R designed for participants with no programming experience.
IN PERSON: Introduction to Python for Data Science: Analyzing Data with Logic and Iteration (1:00pm)
In the final part of the 3-part workshop series, "Introduction to Python for Data Science," we offer an overview of Python fundamentals for performing iterative tasks with for loops and conditional tasks using logic and if statements. We will then show how to apply these programming techniques to analyze and visualize multiple tabular datasets with Pandas. The content covered in this workshop will be a continuation of the content covered in part 1, "Introduction to Basic Programming with Data" and part 2, "Plotting and Analyzing Tabular Datasets".
Thursday Feb. 15th
VIRTUAL: Cleaning Untidy Data with OpenRefine (12:00pm)
Tired of spending hours and hours cleaning messy data in Excel spreadsheets? Come learn OpenRefine, an easy-to-use, open source tool for data cleaning. OpenRefine (formerly Google Refine) helps you prepare your data for analysis. Quickly and easily transform data, split and merge columns, remove whitespace, and perform many more common data cleaning tasks. With OpenRefine, you can also easily create JSON scripts for repeating series of tasks across multiple datasets.
No previous experience is required. This will be a hands-on workshop--please bring a laptop.
Friday Feb. 16th
VIRTUAL: ICPSR: A Source for Secondary Data and More! (10:00am)
As one of the world's oldest and largest social science data archives, ICPSR is a go-to source for data for analysis, resources for teaching and learning, and support for collecting and sharing one's own data. This webinar will provide a brief overview of the 19,000+ data collections in the ICPSR catalog and instruction on how to search and evaluate the data held therein. One way to approach the catalog is through a set of "thematic data collections" or topical archives -- we will show where to find those and highlight collections related to policy and arts management. Participants will also be introduced to the Summer Program in Quantitative Methods and ICPSR resources related to collecting and sharing primary data.
IN PERSON: Mapping Accessibility: Enriching sidewalk data using Project Sidewalk (11:30 am, Hunt Library)
Do you think sidewalk data or sidewalk accessibility are important? Join us for a workshop on the importance of sidewalk data and a tutorial on Project Sidewalk, a tool that allows you to enrich sidewalk data with accessibility information. Project sidewalk is a project of the Make Ability Lab at the University of Washington and currently has data for 11 cities, including Pittsburgh PA. The labels you add during the workshop or later impact city planning in the city you enrich, and help build mapping tools and algorithms that are accessibility-aware. We hope you will continue to add data throughout the semester and beyond.
No previous experience is required. This will be a hands-on workshop--please bring a laptop.