Data services at the academic library: a natural history of horses and unicorns

Authors : Jeffrey Oliver, Fernando Rios, Kiriann Carin, Chun Ly


Increases in data-intensive research at colleges and universities is driving demand for data services provided by academic libraries. The current work investigates the distribution of library data services, how such services are offered, and the effect of resourcing on the amount of services offered by a library.


We used a web-based inventory of 25 academic libraries at U.S. Research 1 (R1) Carnegie institutions to assess the state of data services at university libraries. We categorized and quantified services, and tested for an effect of library resourcing on the size of library data service portfolios.


Support for data management and geospatial services was relatively widespread, with increasing support in areas of data analyses and data visualization. There was significant variation among services in the modality in which they were offered (web, consult, instruction) and library resourcing had a significant effect on the number of data services a library offered.


While a core subset of these data services are offered at most academic libraries, more specialized topics are restricted to well-resourced libraries. In light of the influence of resource scarcity on the number of services a library can offer, intra- and inter-campus partnerships will be critical to ensure campus support for data service needs.

URL : Data services at the academic library: a natural history of horses and unicorns


Developing Data Services Skills in Academic Libraries

Author : Justin Fuhr

Research data services are increasingly offered by academic libraries. As a result, librarians may need to upskill to provide data services and build capacity. This study measures the current level of data services skills of academic librarians and explores preferred methods of continuing education.

An online survey was circulated asking respondents to self-assess data skills in four categories. The results capture a baseline of self-assessed data skills and show statistical significance between the percentage of time a librarian provides data services and higher levels of technical skill sets.

The findings support the hiring of data librarians in academic libraries offering data services and providing training for librarians who provide any level of data services.

URL : Developing Data Services Skills in Academic Libraries


Bringing All the Stakeholders to the Table: A Collaborative Approach to Data Sharing

Authors : Megan N. O’Donnell, Curtis Brundy


This paper examines a unique data set disclosure process at a medium sized, land grant, research university and the campus collaboration that led to its creation.


The authors utilized a single case study methodology, reviewing relevant documents and workflows. As first-hand participants in the collaboration and disclosure process development, their own accounts and experiences also were utilized.


A collaborative approach to enhancing research data sharing is essential, considering the wide array of stakeholders involved across the life cycle of research data. A transparent, inclusive data set disclosure process is a viable route to ensuring research data can be appropriately shared.


Successful sharing of research data impacts a range of university units and individuals. The establishment of productive working relationships and trust between these stakeholders is critical to expanding the sharing of research data and to establishing shared workflows.

URL : Bringing All the Stakeholders to the Table: A Collaborative Approach to Data Sharing


Why Won’t They Just Adopt Good Research Data Management Practices? An Exploration of Research Teams and Librarians’ Role in Facilitating RDM Adoption

Authors: Clara Llebot, Hannah Gascho Rempe

Adoption of good research data management practices is increasingly important for research teams. Despite the work the research community has done to define best data management practices, these practices are still difficult to adopt for many research teams.

Universities all around the world have been offering Research Data Services to help their research groups, and libraries are usually an important part of these services. A better understanding of the pressures and factors that affect research teams may help librarians serve these groups more effectively.

The social interactions between the members of a research team are a key element that influences the likelihood of a research group successfully adopting best practices in data management.

In this article we adapt the Unified Theory of the Acceptance and Use of Technology (UTAUT) model (Venkatesh, Morris, Davis, & Davis, 2003) to explain the variables that can influence whether new and better, data management practices will be adopted by a research group.

We describe six moderating variables: size of the team, disciplinary culture, group culture and leadership, team heterogeneity, funder, and dataset decisions.

We also develop three research group personas as a way of navigating the UTAUT model, and as a tool Research Data Services practitioners can use to target interactions between librarians and research groups to make them more effective.

URL : Why Won’t They Just Adopt Good Research Data Management Practices? An Exploration of Research Teams and Librarians’ Role in Facilitating RDM Adoption


Reading the fine print: A review and analysis of business journals’ data sharing policies

Authors : Brianne Dosch, Tyler Martindale

Business librarians offer many data services to their researchers. These services are often focused more on discovery, visualization, and analysis than general data management. But, with the replication crisis facing many business disciplines, there is a need for business librarians to offer more data sharing and general data management support to their researchers.

To find evidence of this data need, 146 business journal’s data sharing policies were reviewed and analyzed to uncover meaningful trends in business research. Results of the study indicate data sharing is not mandated by business journals.

However, data sharing is often encouraged and recommended. This journal policy content analysis provides evidence that business researchers have opportunities to share their research data, and with the right data management support, business librarians can play a significant role in improving the data sharing behaviors of business researchers.


Data librarian et services aux chercheurs en bibliothèque universitaire : de nouvelles médiations en émergence

Auteur/Author : Florence Thiault

Les services à destination des chercheurs se développent dans les bibliothèques universitaires françaises. L’augmentation de la quantité de données de recherche produites et réutilisées par les chercheurs pose des défis importants aux bibliothèques universitaires.

De nouvelles compétences associées à un profil professionnel spécifique celui de datalibrarian sont nécessaires pour assurer ces missions d’accompagnement à la recherche. Ce spécialiste des données à vocation à accompagner les chercheurs dans le cycle de vie de la recherche en assurant une collaboration active avec une série d’acteurs internes et externes.

Cette communication présente trois cas d’études emblématiques dans le registre des médiations à destination des chercheurs : l’analyse de la production scientifique, l’accompagnement à la recherche et à la publication ainsi que la gestion des données de recherche.


How are we Measuring Up? Evaluating Research Data Services in Academic Libraries

Authors : Heather L. Coates, Jake Carlson, Ryan Clement, Margaret Henderson, Lisa R Johnston, Yasmeen Shorish


In the years since the emergence of federal funding agency data management and sharing requirements (, research data services (RDS) have expanded to dozens of academic libraries in the United States.

As these services have matured, service providers have begun to assess them. Given a lack of practical guidance in the literature, we seek to begin the discussion with several case studies and an exploration of four approaches suitable to assessing these emerging services.


This article examines five case studies that vary by staffing, drivers, and institutional context in order to begin a practice-oriented conversation about how to evaluate and assess research data services in academic libraries.

The case studies highlight some commonly discussed challenges, including insufficient training and resources, competing demands for evaluation efforts, and the tension between evidence that can be easily gathered and that which addresses our most important questions.

We explore reflective practice, formative evaluation, developmental evaluation, and evidence-based library and information practice for ideas to advance practice.


Data specialists engaged in providing research data services need strategies and tools with which to make decisions about their services. These range from identifying stakeholder needs to refining existing services to determining when to extend and discontinue declining services.

While the landscape of research data services is broad and diverse, there are common needs that we can address as a community. To that end, we have created a community-owned space to facilitate the exchange of knowledge and existing resources.

URL : How are we Measuring Up? Evaluating Research Data Services in Academic Libraries