A Comprehensive Community Needs Assessment for Advancing Text Analytics Data Services in Academic Libraries
Project Leads: PI: Dr. Kun Lu; Co-PI: Dr. Soohyung Joo Graduate Students/Assistants: Sydney Fant; Susanna Spendlove |
Project Introduction
The team from the University of Alabama and the University of Kentucky aims to conduct a comprehensive assessment of community needs related to advancing text analytics data services in academic libraries. This project aims to gather substantial evidence and insights to support a subsequent, larger project focused on developing text analytics service models for academic libraries and creating tailored training resources for data librarians. This project will conduct a thorough survey of the current state of text analytics services in academic libraries and an in-depth evaluation of the needs of various stakeholders from different types of institutions, including library users, librarians, and LIS (Library and Information Studies) educators. The findings from this project will guide the follow-up effort aiming at developing text analytics service models and customized training materials for academic librarians involved in data services. Ultimately, the results of this investigation will serve as the evidence base for designing innovative data service models that incorporate text analytics and for developing practical training tools for librarians.
Methodology
This project comprises seven main tasks and methodologies.
Tasks | Objectives | Methods |
Task 1: Investigation of current services. | Assess the current state of text analytics services in academic libraries. | Content analysis of ~250 library websites; Literature review. |
Task 2: Case Studies | Identify best practices and innovative text analytics services. | In-depth analysis of selected libraries. |
Task 3: Needs assessment of users | Identify user needs for library support in text analytics. | Online survey of faculty, researchers, and students. |
Task 4: Needs assessment of Librarians | Identify existing and potential text analytics services. Assess librarians' current skills and training needs. | Nationwide survey of librarians; Semi-structured interviews. |
Task 5: Input from LIS educators | Determine the knowledge and skills required for text analytics services. Identify pedagogical approaches for librarian training. | Focus groups. |
Task 6: Library partnerships | Establish and strengthen collaborations with libraries and professionals. | Outreach to librarians; Participation in professional meetings. |
Task 7: Planning next project | Plan the next phase, which aims to design text analytics service models and develop tailored training resources. | Synthesis of evidence and takeaways from Tasks 1- 5. |
Timeline
This is a two-year project. The first year will focus on investigating current services, case studies, needs assessments of librarians, needs assessments of users, and partnerships with other academic libraries. The second year will focus on the analysis of librarian assessments, needs assessments of users, input from LIS instructors, partnerships with other academic libraries, and planning the next stages. The project team plans a follow-up project built on the foundation of this project to develop text analytics service models for academic libraries and create tailored training resources for academic librarians. These service models and training resources will have a long-term impact on advancing text analytics data services in academic libraries.
Expected Deliverables
The primary outcome of this project will be a series of research findings and reports, covering various aspects: (a) the areas of text analytics services in academic libraries; (b) the specific needs of text analytics support among users; (c) case studies and best practices of text analytics services in libraries; (d) the topics and content of text analytics tailored to librarian training; (e) pedagogical approaches to training librarians; (f) partnership agreement on developing text analytics services and training resources, among others. These findings and reports will paint a comprehensive picture of the current state of text analytics services and the perspectives of different stakeholders, including librarians, library users, and LIS educators, on advancing text analytics services in academic libraries.
Advisory Board Members
The advisory board includes four external experts who will provide valuable insights and guidance to support the project’s goals.
Borui Zhang Borui Zhang (Ph.D. in Linguistics), an NLP specialist at George A. Smathers Libraries, University of Florida, focuses on making text analytics and AI resources accessible across disciplines in her libraries. |
Isaac Wink Isaac Wink (MLIS) is a Research Data Librarian at the University of Kentucky Libraries. He provides support to UK researchers across all disciplines and at all stages of the research data lifecycle, including planning projects, developing data management workflows, preserving and sharing data, and identifying datasets for reuse. |
Kara Handren Kara Handren (Master of Information), a Data Librarian at the University of Toronto Libraries, specializes in metadata and data librarianship. |
Tara Baillargeon Tara Baillargeon (Ed.D., MLIS), Dean of Raynor Library at Marquette University, has conducted research on digital scholarship. |