Purpose: The last few years have seen a surge of interest in artificial intelligence (AI). The purpose of this paper is to capture a snapshot of perceptions of the potential impact of AI on academic libraries and to reflect on its implications for library work. Design/methodology/approach: The data for the study were interviews with 33 library directors, library commentators and experts in education and publishing. Findings: Interviewees identified impacts of AI on search and resource discovery, on scholarly publishing and on learning. Challenges included libraries being left outside the focus of development, ethical concerns, intelligibility of decisions and data quality. Some threat to jobs was perceived. A number of potential roles for academic libraries were identified such as data acquisition and curation, AI tool acquisition and infrastructure building, aiding user navigation and data literacy. Originality/value: This is one of the first papers to examine current expectations around the impact of AI on academic libraries. The authors propose the paradigm of the intelligent library to capture the potential impact of AI for libraries.

The scientific literature peer review workflow is under strain because of the constant growth of submission volume. One response to this is to make initial screening of submissions less time intensive. Reducing screening and review time would save millions of working hours and potentially boost academic productivity. Many platforms have already started to use automated screening tools, to prevent plagiarism and failure to respect format requirements. Some tools even attempt to flag the quality of a study or summarise its content, to reduce reviewers’ load. The recent advances in artificial intelligence (AI) create the potential for (semi) automated peer review systems, where potentially low-quality or controversial studies could be flagged, and reviewer-document matching could be performed in an automated manner. However, there are ethical concerns, which arise from such approaches, particularly associated with bias and the extent to which AI systems may replicate bias. Our main goal in this study is to discuss the potential, pitfalls, and uncertainties of the use of AI to approximate or assist human decisions in the quality assurance and peer-review process associated with research outputs. We design an AI tool and train it with 3300 papers from three conferences, together with their reviews evaluations. We then test the ability of the AI in predicting the review score of a new, unobserved manuscript, only using its textual content. We show that such techniques can reveal correlations between the decision process and other quality proxy measures, uncovering potential biases of the review process. Finally, we discuss the opportunities, but also the potential unintended consequences of these techniques in terms of algorithmic bias and ethical concerns.

This paper reports research carried out at the end of 2012 to survey UK universities to understand in detail the ways in which libraries are currently involved in research data management and the extent to which the development of research data management services is a strategic priority for them. The research shows that libraries were offering limited research data management services, with highest levels of activity in large research-intensive institutions. There were major challenges associated with skills gaps, resourcing and cultural change. However, libraries are currently involved in developing new institutional research data management policies and services, and see this as an important part of their future role. Priorities such as provision of research data management advisory and training services are emerging. A systematic comparison between these results and other recent studies is made in order to create a full picture of activities and trends. An innovation hype-cycle framework is deployed to understand possible futures and Abbott’s theory of professions is used to gain an insight into how libraries are competing to extend their jurisdiction whilst at the same time working collaboratively with other stakeholders.

This article reports an international study of research data management (RDM) activities, services, and capabilities in higher education libraries. It presents the results of a survey covering higher education libraries in Australia, Canada, Germany, Ireland, the Netherlands, New Zealand, and the UK. The results indicate that libraries have provided leadership in RDM, particularly in advocacy and policy development. Service development is still limited, focused especially on advisory and consultancy services (such as data management planning support and data‐related training), rather than technical services (such as provision of a data catalog, and curation of active data). Data curation skills development is underway in libraries, but skills and capabilities are not consistently in place and remain a concern. Other major challenges include resourcing, working with other support services, and achieving “buy in” from researchers and senior managers. Results are compared with previous studies in order to assess trends and relative maturity levels. The range of RDM activities explored in this study are positioned on a “landscape maturity model,” which reflects current and planned research data services and practice in academic libraries, representing a “snapshot” of current developments and a baseline for future research.

As open‐access (OA) publishing funded by article‐processing charges (APCs) becomes more widely accepted, academic institutions need to be aware of the “total cost of publication” (TCP), comprising subscription costs plus APCs and additional administration costs. This study analyzes data from 23 UK institutions covering the period 2007–2014 modeling the TCP. It shows a clear rise in centrally managed APC payments from 2012 onward, with payments projected to increase further. As well as evidencing the growing availability and acceptance of OA publishing, these trends reflect particular UK policy developments and funding arrangements intended to accelerate the move toward OA publishing (“Gold” OA). Although the mean value of APCs has been relatively stable, there was considerable variation in APC prices paid by institutions since 2007. In particular, “hybrid” subscription/OA journals were consistently more expensive than fully OA journals. Most APCs were paid to large “traditional” commercial publishers who also received considerable subscription income. New administrative costs reported by institutions varied considerably. The total cost of publication modeling shows that APCs are now a significant part of the TCP for academic institutions, in 2013 already constituting an average of 10% of the TCP (excluding administrative costs).

The management of research data is now a major challenge for research organisations. Vast quantities of born-digital data are being produced in a wide variety of forms at a rapid rate in universities. This paper analyses the contribution of academic libraries to research data management (RDM) in the wider institutional context. In particular it: examines the roles and relationships involved in RDM, identifies the main components of an RDM programme, evaluates the major drivers for RDM activities, and analyses the key factors influencing the shape of RDM developments. The study is written from the perspective of library professionals, analysing data from 26 semi-structured interviews of library staff from different UK institutions. This is an early qualitative contribution to the topic complementing existing quantitative and case study approaches. Results show that although libraries are playing a significant role in RDM, there is uncertainty and variation in the relationship with other stakeholders such as IT services and research support offices. Current emphases in RDM programmes are on developments of policies and guidelines, with some early work on technology infrastructures and support services. Drivers for developments include storage, security, quality, compliance, preservation, and sharing with libraries associated most closely with the last three. The paper also highlights a ‘jurisdictional’ driver in which libraries are claiming a role in this space. A wide range of factors, including governance, resourcing and skills, are identified as influencing ongoing developments. From the analysis, a model is constructed designed to capture the main aspects of an institutional RDM programme. This model helps to clarify the different issues involved in RDM, identifying layers of activity, multiple stakeholders and drivers, and a large number of factors influencing the implementation of any initiative. Institutions may usefully benchmark their activities against the data and model in order to inform ongoing RDM activity.