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Text and Data Mining: Contact Us

This guide provides guidance for users interested in doing text and data mining. It includes data sources and tools, support options, and best practices for using content licensed by the University Libraries.

Library Data Services

Library Data Services caters to researchers interested in working with data, mapping, texts, visualization, and technology. Many of these services are available online. Davis Library Data Services, located on the second floor of Davis Library, offers:

  • A computing lab with specialized software for GIS and data visualization & analysis.
  • Walk-in assistance provided by knowledgeable student consultants during set hours
  • Consultations with specialists for more in-depth inquiries (by appointment).
  • Spaces for collaboration and presentation, complete with white boards and external displays.
  • Technology short courses and programs that promote digital scholarship.

Contact Us

Rolando Rodriguez

Rolando can provide specialized assistance with textual analysis and natural language processing, data mining, and social media data. 

Click here to book a consultation with Rolando.

Michele Hayslett

Michele can provide specialized assistance with data management, numeric data, census data, and locating data.

Click here to book a consultation with Michele.

Additional Support

Support from the Licensing Team

Every vendor's policies on text and data mining are different. Often, even if a vendor prohibits text or data mining under the University's license, researchers can negotiate for permission, sometimes for a fee. Depending on the researcher's needs, The University Libraries' Licensing Team can:

  • help researchers understand licensing terms
  • provide contact information for individual vendors, or
  • lobby specific vendors for text or data mining abilities.

Researchers can contact the Licensing Team by emailing lib_access@unc.edu.

Support from Library Data Services

Text and data mining can be daunting. Library Data Services staff can assist researchers in designing and implementing technical approaches and suggest appropriate ways to analyze data. Connect with us!

Also check our events schedule for recurring sessions on programming with R, Python, and more.