Models for Sustainable and Inclusive Data Science Consulting and Collaboration in Higher Education  

Driven by an interest in approaches to structuring data science consulting in higher education and a relative dearth of recent literature on the topic, the NC State Data Science Academy (DSA), the NC State Libraries, and the Academic Data Science Alliance (ADSA) convened a workshop with experts from a variety of institution types. The workshop participants enthusiastically engaged with different facets of administrative models for data science consulting to identify considerations for structuring programs. 

The workshop consisted of a series of virtual pre-sessions to help participants get to know each other and begin discussing specific topics of interest. At the in-person workshop, participants broke into groups to work on academic papers exploring different aspects of the administration of consulting programs. 

The goal of the series was to identify, develop, and communicate successful models for consulting/collaboration in an academic setting, with a focus on power dynamics between tenured/tenure-track faculty, non-tenure-track faculty, research staff, and students; funding and sustainability; and graduate student training and education. Participants identified and shared models for effective data science consulting and unique consulting models present on their own campuses. 

The scholarly output of the workshop was a special issue of the journal Stat focused on data science consulting models for use in academic institutions (published in July 2024). 

*Available in an open-access format. 

• *Brown, C., Di, Y., & Slone, S. (2024). Considerations in developing a financial model for an academic statistical consulting centre. Stat, 13(2), e688. https://doi.org/10.1002/sta4.688
• Brown, C. T., Mehta, M., Ryali, M., Dong, X., Shadfar, I., Dominquez Davalos, J., Culich, A., & Suen, A. (2024). The data science discovery program: A model for data science consulting in higher education. Stat, 13(2), e677. https://doi.org/10.1002/sta4.677

• *Huebner, M., Bond, L., Stukes, F., Herndon, J., Edwards, D. J., & Pomann, G.-M. (2024). Developing partnerships for academic data science consulting and collaboration units. Stat, 13(1), e644. https://doi.org/10.1002/sta4.644

• *Maimone, C., Sharp, J. L., Schwartz-Soicher, O., Oliver, J. C., & Beltran, L. (2024). Do good: Strategies for leading an inclusive data science or statistics consulting team. Stat, 13(2), e687. https://doi.org/10.1002/sta4.687

• *Huebner, M., Pierce, S. J., Dennhardt, A. J., Akaeze, H., Jess, N., & Ma, W. (2024). What matters to graduate students? Experiences at a statistical consulting center from pre- to post-COVID-19 pandemic. Stat, 13(1), e659. https://doi.org/10.1002/sta4.659

• Peskoe, S., Slade, E., Rende, L., Boulos, M., Desai, M., Gandhi, M., Gelfond, J. A. L., Khalatbari, S., Schulte, P. J., Snyder, D. C., Taylor, S. L., Troy, J. D., Vaughan, R., & Pomann, G.-M. (2024). Methods for building a staff workforce of quantitative scientists in academic health care. Stat, 13(2), e683. https://doi.org/10.1002/sta4.683

• *Peterson, R. A., Slade, E., Pomann, G.-M., & Ambrosius, W. T. (2024). Working well with statisticians: Perceptions of practicing statisticians on their most successful collaborations. Stat, 13(2), e694. https://doi.org/10.1002/sta4.694

• *Platt, A., Truong, T., Boulos, M., Carlson, N. E., Desai, M., Elam, M. M., Slade, E., Hanlon, A. L., Hurst, J. H., Olsen, M. K., Poisson, L. M., Rende, L., & Pomann, G.-M. (2024). A guide to successful management of collaborative partnerships in quantitative research: An illustration of the science of team science. Stat, 13(2), e674. https://doi.org/10.1002/sta4.674
• *Slade, E., Robbins, S. J. K., McQuerry, K. J., & Mangino, A. A. (2024). The value of flexible funding for collaborative biostatistics units in universities and academic medical centres. Stat, 13(2), e679. https://doi.org/10.1002/sta4.679

• Vasilopoulos, T., Crisp, A., Garvan, G., Howell, K., Janelle, G., & Garvan, C. (2024). Documenting and communicating the contributions of embedded statisticians: Show me the value!. Stat, 13(2), e691. https://doi.org/10.1002/sta4.691

• Vasilopoulos, T., & Tumin, D. (2024). Biostatistics deserts and scholarly productivity among US medical schools. Stat, 13(2), e693. https://doi.org/10.1002/sta4.693

Based on feedback from workshop participants, Co-Is Emily Griffith and Mara Blake organized a webinar for participants focusing on how to develop a pitch for a statistical and/or data science consulting program that is directed to university administrators. Facilitated by PI Rachel Levy, the speakers were Jill Sexton, Associate Director for Digital & Organizational Strategy at the NC State Libraries, and Dr. Alyson Wilson, Associate Vice Chancellor for National Security and Special Research Initiatives. 

Co-Investigators Emily Griffith and Mara Blake presented about the NC State consulting model and some of the results of this workshop at the Academic Data Science Alliance Annual Meeting (October 2023) and the Conference on Networked Information (December 2023).

• Academic Data Science Alliance Annual Meeting (October 2023):
  • At the annual meeting at the University of Texas, San Antonio, Co-PIs Emily Griffith and Mara Blake led an interactive session titled “Organizing and Sustaining Data Science Consulting and Collaboration in Higher Education” in which they described the concept of collaborative consulting and the conference and the participants each described related efforts or aspirations in their organizations. 
• Coalition for  Networked Information Membership Meeting (December 2023): 
  • At the membership meeting in Washington, DC, Co-PIs Emily Griffith and Mara Blake delivered a briefing to about 90 participants that provided an update on the “Models for Sustainable and Inclusive Data Science Consulting and Collaboration in Higher Education” project.

Additional funding was used to support travel to share models for data science consulting in higher education by workshop participants at conferences including the Conference on Statistical Practice (February 2024), International Association for Social Science Information Service & Technology (IASSIST, May 2024), the Joint Statistical Meetings (August 2024), Women in Statistics and Data Science (October 2024), and the Academic Data Science Alliance Annual Meeting (October 2024).