Catégories
EN

Assessing Researcher Data Sharing Practices Using Publicly Available Dataset Metadata: A Reproducible Workflow for Institutional Stakeholders

Authors : Danielle R. Kirsch, Isaac Wink

Introduction

Scholarly communities are experiencing increased emphasis on research data sharing and reuse. Given the range of available data repositories and variability in the use of persistent identifiers (PIDs) for individuals and institutions, aggregating datasets by researchers at a specific institution is a significant challenge. We developed a reproducible workflow to evaluate 1) data repository use by researchers at our institutions, 2) metrics of reuse, and 3) quality of metadata records.

Methods

We used the DataCite REST API to locate metadata records for datasets with creator affiliation names that matched our institutions. We performed substantial cleaning and deduplication before comparing repository use, citations, usage metrics, and metadata completeness.

Results

The most common data repositories were Dryad, Harvard Dataverse, figshare, Zenodo, ICPSR, and one institution’s institutional repository. View, download, and citation counts were available from a limited number of repositories, with some discrepancies between different citation reporting methods. PIDs were more frequently used for authors and affiliations than funders, and the inclusion of PIDs varied across repositories, with Dryad being the most consistent.

Discussion & Conclusion

Although broad trends in repository and PID use were similar between institutions, our analysis also surfaced examples that illustrate inconsistencies in metadata across repositories. Variable implementation of the DataCite metadata schema requires a significant amount of data cleaning to obtain meaningful results. Even then, incomplete metadata makes some datasets impossible to locate. Repositories, funders, researchers, and institutional open data advocates must coordinate to create complete and usable metadata that integrates datasets into the scholarship ecosystem.

URL : Assessing Researcher Data Sharing Practices Using Publicly Available Dataset Metadata: A Reproducible Workflow for Institutional Stakeholders

DOI : https://doi.org/10.31274/jlsc.22913

Catégories
EN

Constructing a (Meaningful) Scholarly Publishing Narrative: Bootstrapping Green Open Access Submissions for Open Access Week

Authors : Tim Ribaric, Erin Moorhead

Introduction

Green Open Access requires authors to submit appropriate versions of journal articles to a repository; the challenge for researchers is to remember to perform this task after the primary work of the publication process is done. This case study at Brock University Library shows how it is possible to bootstrap these types of submissions by crafting meaningful publishing narratives through a collection of clever Open Access Week initiatives.

Literature Review

The literature review assesses the existing scholarly material on Open Access outreach efforts and touches on Open Access in the Canadian context. It explores the dynamics of self-archiving with Green Open Access and the use of institutional repositories. The existing literature on wielding open data as a tool to serve libraries is discussed, and the potential of these tools to support librarian advocacy work is examined.

Description of Program and Benefits

By using a collection of Open Access scholarly publishing web services and APIs, two outreach campaigns were conducted by Brock University Library during Open Access Week 2025. The first was a State of Scholarly Publishing Report that showed broad trends in output from the organization, and the second was a Green Open Access Call to Action that prompted researchers to submit recently published eligible papers to the repository.

Conclusion

There was enough enthusiasm generated from these two projects that the Brock University Library will continue to run these campaigns in subsequent Open Access Weeks. The publishing report was engaging and was included in many different venues on campus, while the Green Open Access Call to Action resulted in submissions from 37% of contacted authors.

URL : Constructing a (Meaningful) Scholarly Publishing Narrative: Bootstrapping Green Open Access Submissions for Open Access Week

DOI : https://doi.org/10.31274/jlsc.21406

Catégories
EN

Recent Advances and Trends in Research Paper Recommender Systems: A Comprehensive Survey

Authors : Iratxe Pinedo, Mikel Larrañaga, Ana Arruarte

As the volume of scientific publications grows exponentially, researchers increasingly face difficulties in locating relevant literature. Research Paper Recommender Systems have become vital tools to mitigate this information overload by delivering personalized suggestions.

This survey provides a comprehensive analysis of Research Paper Recommender Systems developed between November 2021 and December 2024, building upon prior reviews in the field. It presents an extensive overview of the techniques and approaches employed, the datasets utilized, the evaluation metrics and procedures applied, and the status of both enduring and emerging challenges observed during the research. Unlike prior surveys, this survey goes beyond merely cataloguing techniques and models, providing a thorough examination of how these methods are implemented across different stages of the recommendation process.

By furnishing a detailed and structured reference, this work aims to function as a consultative resource for the research community, supporting informed decision-making and guiding future investigations in the advances of effective Research Paper Recommender Systems.

DOI : https://doi.org/10.48550/arXiv.2508.08828

Catégories
EN

Artificial Intelligence in Scientific Publishing: Citation Impact and Thematic Trends

Author : Mohammadamin Erfanmanesh

Introduction: The rise of artificial intelligence (AI) has a significant impact on scientific publishing and librarianship. This study explores the citation impact and thematic patterns of AI-related research in scientific publishing through four objectives: (1) to analyze bibliometric characteristics; (2) to evaluate citation performance using normalized metrics; (3) to identify major thematic trends; and (4) to review AI-related publications that specifically address librarianship and examine their implications for library practices.

Methods: A bibliometric analysis was conducted on 295 AI-related publications indexed in the Web of Science Core Collection. Citation performance was assessed using two field-normalized metrics from Clarivate’s InCites platform: the Category Normalized Citation Impact (CNCI) and the Journal Normalized Citation Impact (JNCI). To determine whether the median CNCI and JNCI values differed significantly from the category and journal benchmarks, a one-sample Wilcoxon signed-rank test was performed. Sub-themes within AI-related research were identified through thematic analysis. Additionally, to highlight important themes and professional implications, publications that specifically mention libraries, librarians, or librarianship were reviewed.

Results: The median CNCI was 2.7, and the median JNCI was 2.2, both significantly above the benchmark of 1.0 (P < .001). This indicates that AI-related research in scientific publishing receives significantly more citations than comparable publications within the same subject areas and journals. Seven sub-themes were identified, all showing above-average citation impact. Among these, themes focused on frameworks, policies, and ethical guidelines for AI integration achieved the highest normalized citation scores. Additionally, four publications focusing specifically on librarianship explored how AI intersects with open access and scholarly communication, ethics and governance, professional training, the development of machine-readable collections, and the integration of AI technologies into library services.

Discussion: These findings suggest that AI-related research has rapidly emerged as a highly influential area within scientific publishing. The variety of themes demonstrates the broad impact of AI technologies on scientific publishing.

Conclusion: Research on AI in scientific publishing is a rapidly growing and dynamic area, notable for its high citation impact, broad thematic scope, and growing influence on libraries and librarianship.

URL : Artificial Intelligence in Scientific Publishing: Citation Impact and Thematic Trends

DOI : https://doi.org/10.31274/jlsc.20363

Catégories
EN

Assessing Researcher Data Sharing Practices Using Publicly Available Dataset Metadata: A Reproducible Workflow for Institutional Stakeholders

Authors : Danielle R. Kirsch, Isaac Wink

Introduction: Scholarly communities are experiencing increased emphasis on research data sharing and reuse. Given the range of available data repositories and variability in the use of persistent identifiers (PIDs) for individuals and institutions, aggregating datasets by researchers at a specific institution is a significant challenge. We developed a reproducible workflow to evaluate 1) data repository use by researchers at our institutions, 2) metrics of reuse, and 3) quality of metadata records.

Methods: We used the DataCite REST API to locate metadata records for datasets with creator affiliation names that matched our institutions. We performed substantial cleaning and deduplication before comparing repository use, citations, usage metrics, and metadata completeness.

Results: The most common data repositories were Dryad, Harvard Dataverse, figshare, Zenodo, ICPSR, and one institution’s institutional repository. View, download, and citation counts were available from a limited number of repositories, with some discrepancies between different citation reporting methods. PIDs were more frequently used for authors and affiliations than funders, and the inclusion of PIDs varied across repositories, with Dryad being the most consistent.

Discussion & Conclusion: Although broad trends in repository and PID use were similar between institutions, our analysis also surfaced examples that illustrate inconsistencies in metadata across repositories. Variable implementation of the DataCite metadata schema requires a significant amount of data cleaning to obtain meaningful results. Even then, incomplete metadata makes some datasets impossible to locate. Repositories, funders, researchers, and institutional open data advocates must coordinate to create complete and usable metadata that integrates datasets into the scholarship ecosystem.

URL : Assessing Researcher Data Sharing Practices Using Publicly Available Dataset Metadata: A Reproducible Workflow for Institutional Stakeholders

DOI : https://doi.org/10.31274/jlsc.22913

Catégories
EN

Are AI-Empowered Early Career Researchers Proving To Be the Harbingers of Change?

Authors : David Nicholas, Jorge Revez, Abdullah Abrizah, John Akeroyd, Marzena Swigon, Blanca Rodríguez-Bravo, David Clark, Eti Herman, Jie Xu, Tatyana Polezhaeva

The Harbingers longitudinal study of early career researchers and their pathfinding scholarly communication attitudes and practices is a decade old and much of its findings have been published in this journal.

We are now moving on to the new generation of researchers—Gen-Z and it is fitting that we draw things to a close by summing up whether our largely millennial researchers have proved to be the harbingers of change.

We focus on the data from the last two rounds of interviewing, conducted in the last 2 years, at a time when AI was (increasingly) propelling change. These two rounds covered over 150 ECRs from all subject fields and from China, Malaysia, Poland, Portugal, Russia, Spain, UK and US.

It was found that ECRs are, indeed, at the forefront of the technological adaptation in research, actively exploring the potential of AI and new communication channels. However, their ability to be truly transformative was constrained by a traditional, quantitative evaluation/reputational system.

This could change with Gen-Z because there were ECRs in their twenties included in our previous studies and they displayed higher practical integration of AI tools and appeared to be more strategically adopting AI for efficiency and career advancement.

URL : Learned Publishing – 2026 – Nicholas – Are AI‐Empowered Early Career Researchers Proving To Be the Harbingers of Change

DOI : https://doi.org/10.1002/leap.2099

Catégories
EN

Examining Persistence of European Open Repository Infrastructure and its Diffusion in the Scholarly Record

Authors : George Macgregor, Joy Davidson 

This article seeks to determine the extent to which the principle of persistence is observed by repositories and the organizations that operate them. In addition, the impact that negative repository persistence levels may be having on the scholarly record is assessed.

This is achieved by interrogating and combining data on European repositories from several repository registries and web-scraped sources, including the Internet Archive’s Wayback Machine, which creates a unique dataset of historic repository locations and their OAI-PMH endpoints.

Then, this data is used as the basis for text mining CORE, a vast corpus of scholarly outputs, to determine the extent to which impersistent European repository content has permeated the scholarly literature.

The findings indicate that over one-fifth of European repositories (greater than 20 per cent) could be classified as “dead,” with an even greater proportion (greater than 40 per cent) of the machine interfaces associated with these repositories similarly dead.

Problematically, this analysis indicates that approximately 12,000 unique scholarly works cite, refer to, or actively use this repository content, amounting to approximately 19,000 unique repository locations, all of which are now dead and unretrievable from their stated resource locations.

Partly owing to limitations in available repository registry data and the existence of “zombie” repositories, there are reasons to conclude that the total number of scholarly works referring to dead repository content is far higher. In addition, evidence of dead repository content entering the current scholarly record is found, which is described as “dead on arrival” referencing.

The implications of these observations are considered, explanations are proffered, and possible policy interventions to address repository persistence are proposed.

The dataset also enables several observations on the nature of impersistent repositories to be made, including their profile and their decay rate.

URL : Examining Persistence of European Open Repository Infrastructure and its Diffusion in the Scholarly Record

DOI : https://doi.org/10.2218/ijdc.v20i1.1116