Persistent Identifiers as Open Research Infrastructure to Reduce Administrative Burden

Persistent Identifiers, or PIDs, are emerging as a key aspect of research infrastructure. They act as connective tissue, exposing the relationships between different entities that make up the research ecosystem. One of the major promises of PIDs is that they can help to reduce researcher administrative burden by automating the exchange of information that currently relies on manual entry. This benefit is not well understood by researchers, in part because it can only be realized when PIDs are adopted by a critical mass of researchers, funders, and research administrators. This article will outline the defining characteristics of identifiers, articulate the major benefits of research identifiers, discuss some of the main implementation challenges, provide an overview of existing and emerging identifiers, and summarize some key recommendations for expediting the adoption of PIDs around the globe.

Embedded Librarians to Support Data Management Needs of a Multidisciplinary Research Program

<p>This presentation describes the establishment of a partnership between the Libraries and a multidisciplinary research program, and some of the products and outcomes from immersive and embedded roles within that program. Several factors contributed to the development of this partnership: outreach efforts by the Engineering Library and the Data Services Librarian to faculty, staff, students, and research administrators; a research program director who has a history of engagement with the Libraries; and the funder’s data management and sharing mandates in the funding opportunity announcement for the research program.</p>

The rhythms of scholarly publication: suggestions for academic research administrators making bibliometric comparisons across disciplines

In the tables presented here (https://osf.io/myaut/), we show data pertaining to publication rates and publication venues across 170 academic disciplines. We model the publication patterns of faculty members at U.S. research universities at different career stages, and in so doing we hope to provide a nuanced and up-to-date reference for faculty members, administrators, and staff charged with interpreting publication outputs across disciplines and in a comparative context. Not all active scholars in any field will follow the same pattern of publication, and not all articles or books are of equal value: these data do not reflect quality measures. Our goal is not to establish a template against which individual scholars should be measured, but to contextualize a general picture of publication patterns representative of each discipline, with the knowledge that there will be notable individual variations.

Data Sharing in the High-throughput University - Mobility and Precarity

The nascent field of data science and the expansion of the higher education sector share surprising affinities. The emergence of the “entrepreneurial university” has brought increasing differentiation of the work roles of academics in addition to increased mobility and, for some, precarity. At the same time, researchers are dealing with unprecedented amounts of data. The present article describes how policies and infrastructures implemented to support researchers with data curation tasks might be repurposed by research administrators to tackle problems of academic mobility rooted in increasing precarity of non-tenured research staff. Findings suggest that the organizational benefit of research data management (RDM) is not increased efficiency or reusability of research, but rather increased control over data left behind by non-tenured staff. Recent interest in data mobility needs to be understood by reference to increased researcher mobility. While the view of data as context-independent evidence has been challenged by reference to the investments necessary to mobilize data as evidence in the first place, the material presented here suggests that RDM is repurposed by universities as a strategy to manage, not data, but rather increasing rates of staff turnover. The mobility of data producers and the immobility of data are frequently in tension. Handing over data is problematic irrespective of domain, data type, and funding source. The term “high-throughput university” is introduced in opposition to “high-throughput” data production techniques to suggest that findability and reusability of data need to be recontextualized with reference to increased academic mobility.

Stakeholders' perspectives on research integrity training practices: a qualitative study

Background Even though research integrity (RI) training programs have been developed in the last decades, it is argued that current training practices are not always able to increase RI-related awareness within the scientific community. Defining and understanding the capacities and lacunas of existing RI training are becoming extremely important for developing up-to-date educational practices to tackle present-day challenges. Recommendations on how to implement RI education have been primarily made by selected people with specific RI-related expertise. Those recommendations were developed mainly without consulting a broader audience with no specific RI expertise. Moreover, the academic literature lacks qualitative studies on RI training practices. For these reasons, performing in-depth focus groups with non-RI expert stakeholders are of a primary necessity to understand and outline how RI education should be implemented. Methods In this qualitative analysis, different focus groups were conducted to examine stakeholders’ perspectives on RI training practices. Five stakeholders' groups, namely publishers and peer reviewers, researchers on RI, RI trainers, PhDs and postdoctoral researchers, and research administrators working within academia, have been identified to have a broader overview of state of the art. Results A total of 39 participants participated in five focus group sessions. Eight training-related themes were highlighted during the focus group discussions. The training goals, timing and frequency, customisation, format and teaching approach, mentoring, compulsoriness, certification and evaluation, and RI-related responsibilities were discussed. Although confirming what was already proposed by research integrity experts in terms of timing, frequency, duration, and target audience in organising RI education, participants proposed other possible implementations strategies concerning the teaching approach, researchers' obligations, and development an evaluation-certification system. Conclusions This research aims to be a starting point for a better understanding of necessary, definitive, and consistent ways of structuring RI education. The research gives an overview of what has to be considered needed in planning RI training sessions regarding objectives, organisation, and teaching approach.

Making Data and Workflows Findable for Machines

Research data currently face a huge increase of data objects with an increasing variety of types (data types, formats) and variety of workflows by which objects need to be managed across their lifecycle by data infrastructures. Researchers desire to shorten the workflows from data generation to analysis and publication, and the full workflow needs to become transparent to multiple stakeholders, including research administrators and funders. This poses challenges for research infrastructures and user-oriented data services in terms of not only making data and workflows findable, accessible, interoperable and reusable, but also doing so in a way that leverages machine support for better efficiency. One primary need to be addressed is that of findability, and achieving better findability has benefits for other aspects of data and workflow management. In this article, we describe how machine capabilities can be extended to make workflows more findable, in particular by leveraging the Digital Object Architecture, common object operations and machine learning techniques.

The work of university research administrators: Praxis and professionalization

As part of a project on the social production of social science research, 19 research administrators (RAs) in five Canadian universities were interviewed about work, careers, and professionalization. While rarely featured in the higher education literature, RAs have become an important source of assistance to academics, who are increasingly expected to obtain and manage external research funding. RAs perform multiple roles, notably assisting with the complexities of grant-hunting as well as managing ethical clearance, knowledge mobilization, and related activities. Aspects normally associated with professionalization include organizations that control entry, higher degrees in the field, and clear career paths, all of which are somewhat compromised in the case of RAs. Nevertheless, most of the participants regard research administration as a profession, and we argue that it is more important to focus on the sensemaking and identity formation of these mostly female staff than to apply abstract criteria. Although their efforts do little to challenge a culture of performativity in the academy, and indeed may be regarded as supporting it, the RAs have defined for themselves a praxis dedicated to easing the burdens of the academics, helping one another, and contributing to the greater good of the university and the research enterprise.