This study investigated the roles of Library and Information Science (LIS) lecturers in supporting Open Science and Data Stewardship in federal universities in North-Central Nigeria. A mixed-methods case study design was adopted, combining a structured questionnaire, semi-structured interviews, and document analysis. The study targeted the entire population of 96 LIS lecturers across seven federal universities, of whom 79 participated, representing an 82.3% response rate. Quantitative data were analyzed using descriptive statistics, while qualitative data from interviews and institutional documents were analyzed thematically to complement and contextualize the survey findings. The findings indicate that LIS lecturers demonstrate moderate to high awareness of Open Science and Data Stewardship and actively promote these practices through teaching, research supervision, advocacy for open access and support for institutional repositories. However, the integration of Open Science into the LIS curriculum remains partial, while inadequate professional development, weak institutional policies, limited technological infrastructure and insufficient incentives continue to hinder effective implementation. The interview and document analysis findings corroborated the survey results, revealing that Open Science initiatives are largely driven by individual commitment rather than coordinated institutional frameworks. The study concludes that strengthening curriculum integration, institutional policies, professional capacity building and digital infrastructure is essential for advancing Open Science and Data Stewardship in LIS education. It recommends coordinated efforts by universities, the National Universities Commission and the Nigerian Library Association to institutionalize Open Science competencies and foster a sustainable culture of open and collaborative research in Nigerian universities.
Introduction: This is a discussion of data services at R2 libraries in the United States. Environmental scan data was collected from summer 2021 through 2023. Objectives: Our paper focuses on comparisons within four Carnegie Classification categories due to the limited literature about data services at R2 institutions. This analysis was done on a subset of the more comprehensive Library Data Services (LiDS) dataset (Kahl, Skaggs, and Newport 2025). Our research question was broad and general—what does the data service landscape of R2 institutions look like? Methods: Data gathering was done by utilizing website analysis, after which we created and compared descriptive statistics for data services at R2 libraries within four categories of Carnegie Classifications. Results and Discussion: Control Classification offered few insights; Enrollment Profile Classification had a bimodal effect on Data Service Types; Undergraduate Profile Classification offered much more complexity and needed a subset cross comparison to tease out the relative impact of component variables such as Selectivity; and Undergraduate Instructional Program Classification was less complex to observe than the prior classification but still benefitted from a subset cross comparison to clarify the relative impact of the variables such as Graduate Coexistence. Conclusion: Since Selectivity and Graduate Coexistence seem to indicate greater levels of difference in data service support it may be worthwhile for future studies to examine the impact of those specific types of institutions on the provision of Data Service Types at R2 institutions. Data Availability: Kahl, Chad, Lindsey Skaggs, and Joshua Newport. 2025. The LIbrary Data Services (LIDS) Dataset. https://ir.library.illinoisstate.edu/fpml/271. Referenced appendices are available under the article Supplementary Files.
