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Consultations & Drop-Ins

What are consultations at the Cushing/Whitney Medical Library?

Consultations at the Cushing/Whitney Medical Library are meetings you can schedule to discuss a particular data-related topic. These meetings can include your personal librarian in addition to the data librarian.

Consultation topics can include:

  • Data visualization
  • Data cleaning
  • Data management plans
  • Finding research data
  • Accessing data
  • The Research Data Lifecycle
  • Version Control

Request a consultation by emailing medicaldata@yale.edu or by filling out this google form.

What are drop-ins?

Drop-ins (or walk-ins) are blocks of time set aside for you to work on a specific topics, like R or Python, and discuss these topics with other participants. A librarian will be on hand to help you troubleshoot and answer questions you might have as you work through tutorials.  

Data Management Office Hours 

January Schedule:

Wednesdays: 1pm to 2pm

Location: Library Alcove

These events are also listed on the library's calendar.


If you have questions about research data management, stop by the library's Alcove room to talk with your data librarian.

Example questions might include, but are not limited to: 

  • How can I share my data securely with other researchers?

  • Can I reuse this graph or data for my research?

  • My funder requires I deposit my data into a repository. Which repository should I use?

  • How can I find data about [insert your topic here]?

  • Where can I go for statistics or analysis help?

  • Where can I learn about [insert your topic here]?

  • I have all of this research data, how should I organize it?

Cushing/Whitney Medical Library Consultation Topics

Emailmedicaldata@yale.eduto schedule a consultation


Data Management Plan Review

Would you like someone to read through, edit, and offer suggestions to improve a data management plan (DMP) you have drafted for a funding opportunity? Email a copy of your draft to the email listed below, or set up a meeting to discuss your funding party's data management plan requirements. 

To access this DMP Review service, email your data librarian: medicaldata@yale.edu or complete the intake form found on this page.

Data Processing and Transformation 

Bring your data merging, aggregation, reshaping, and aggregation questions to the Medical Library. Together, we can design a solution that fits within your existing workflow. Solutions might use the following technologies:

  • R
  • Python
  • Microsoft Excel

Past data processing and transformation consultation sessions have involved using the R Lubridate library to sumarize data by relative date-times, using R to aggregate peptide modifications by protein IDs, and using logical functions within Microsoft Excel.  

Data Visualization

The Medical Library can offer recommendations for graphs that will best illustrate the meaning behind your data, and point you towards the tools that will help you create these graphs.

Are your graphs blurry and difficult to read in your presentation? We can also help you with technical and design-based choices that make your graphs readable and impactful components of your slide presentations and research posters.

Research Database Design

If you would like to initiate a database for your research data, your data librarian can help you develop design logical and conceptual models that confrom best practises for relational database structures. Consultations can revolve around relational database logical structures, or can be used as an introduction to SQL and MySQL specifically. 


To request any of these types of data consultations at the Medical Library, email medicaldata@yale.edu

StatLab Walk-In Help

StatLab Consultants can help you with your data analysis. StatLab Consultants are available at the Cushing/Whitney Medical Library in room 101 typically once or twice per week, and at the Center for Science and Social Science Information every day during the work week.

Learn more about their services on the StatLab webpage
View the StatLab consultation schedule here