Data office hours are an informal event where all students, faculty, and staff across Pittsburgh can schedule consultations with library experts in all things digital- and data-related. This can mean anything from just learning how to get working on the command line on your computer; getting an introduction to the wide array of data visualization, GIS, text analysis, and data mining research methods available; or having a brief consultation about a specific research or pedagogical project. Our team can help you across the research lifecycle, including data curation, digitization, metadata, and scholarly communications expertise including using CMU’s institutional repository, KiltHub.
Schedule a Consultation
Consultations might include but are not limited to the following:
- Connecting your data analysis problems with an external consultant, or finding datasets to work on.
- Finding, creating, and working with data, including data management, data mining & data modeling, and statistical analysis.
- Learning about the availability of tools and platforms on campus, such as ArcGIS (GIS data), Tableau (data visualization), Open Science Framework, and others. Showing you how to work with experimental digital methods.
- Connecting you to resources for self-teaching or the local networks of Digital Humanities and Digital Scholarship practitioners at CMU Helping you brainstorm, scope, and begin planning a project.
- Evaluating and offering advice on the display of visual content, such as presentations, poster designs, and web design.
- Providing feedback on your dataset, data management plan, project design, and code.
Not sure who to meet with? Fill out our Data Services consultation form and we'll connect you with the right person.
Xiangrui (Cindy) Kong, Open Science Graduate Research Consultant
Python; R; Tableau; data analysis and visualization, modeling
Mugdha Deokar, Open Science Graduate Research Consultant
Python; data science; data cleaning, analysis and visualisation
Chasz Griego, Open Science Postdoctoral Associate
Python, data cleaning and manipulation, analysis and visualization
Taiwo Olanrewaju-Lasisi, CLIR Postdoctoral Fellow in Community Data Literacy
survey design; data literacy basics; coding qualitative data; community data; MAXQDA; NVivo; focus groups; interview guide; ethics in data collection
Jessica Benner, Liaison Librarian, Sciences & Specialist for GIS
spatial data & mapping; finding spatial data; mapping and analysis using GIS desktop tools
Emma Slayton, Data Curation, Visualization, and GIS Specialist: data visualization; GIS; data analysis; data management; [Tools] R, Python, Tableau
Sarah Young, Liaison Librarian, Social Sciences
basic R; basic GitHub; OpenRefine; finding social science data; evidence synthesis; bibliometrics; Zotero
Emily Bongiovanni, Liaison Librarian, Psychology
open research practices; publishing; copyright; open educational resources; data management
Lencia Beltran, Open Science Program Coordinator
open research practices; basic python troubleshooting, analysis, and visualization; Python Plotly maps; command line interface; working with archival/historical data; Noldus Observer; SALT software, Audacity and Praat
Open Science Program Coordinator
Manage Information & Data
Work with our specialists to evaluate, select, and implement the tools to organize your data and keep your project on track.