Rethinking the author name ambiguity problem and beyond: The case of the Chinese context

The perennial problem of author name ambiguity has attracted increasing attention in the academic community. Drawing on the literature, this article first highlights the pervasiveness of the problem and discusses its adverse consequences. It then analyzes the behavioral causes of the problem in the Chinese context and attributes them to personal, cultural, and institutional factors. Informed by this analysis and recognizing ORCID as a promising solution, we propose an ORCID-based "Prevention plus Cure" campaign against author name ambiguity. The prevention objective relies on researchers' consistent use of ORCID, while the cure objective involves retrospectively integrating ORCIDs into backfile publications. We also outline the responsibilities of various stakeholders to ensure the success of the campaign. Furthermore, we argue that universal adoption of ORCID can help curb authorship-related misconduct, discern predatory journals and publishers, and track researchers' undesirable records of academic publishing. We then analyze the current status of ORCID adoption in China, identify potential challenges, propose tentative solutions to address them, and highlight ORCID as a tool that can be utilized to empower China's combat against research misconduct. In conclusion, we emphasize the importance of conducting empirical research to inform more effective promotion of ORCID adoption in China.

Computational reproducibility of Jupyter notebooks from biomedical publications

BACKGROUND

Jupyter notebooks facilitate the bundling of executable code with its documentation and output in one interactive environment, and they represent a popular mechanism to document and share computational workflows, including for research publications. The reproducibility of computational aspects of research is a key component of scientific reproducibility but has not yet been assessed at scale for Jupyter notebooks associated with biomedical publications.

APPROACH

We address computational reproducibility at 2 levels: (i) using fully automated workflows, we analyzed the computational reproducibility of Jupyter notebooks associated with publications indexed in the biomedical literature repository PubMed Central. We identified such notebooks by mining the article's full text, trying to locate them on GitHub, and attempting to rerun them in an environment as close to the original as possible. We documented reproduction success and exceptions and explored relationships between notebook reproducibility and variables related to the notebooks or publications. (ii) This study represents a reproducibility attempt in and of itself, using essentially the same methodology twice on PubMed Central over the course of 2 years, during which the corpus of Jupyter notebooks from articles indexed in PubMed Central has grown in a highly dynamic fashion.

RESULTS

Out of 27,271 Jupyter notebooks from 2,660 GitHub repositories associated with 3,467 publications, 22,578 notebooks were written in Python, including 15,817 that had their dependencies declared in standard requirement files and that we attempted to rerun automatically. For 10,388 of these, all declared dependencies could be installed successfully, and we reran them to assess reproducibility. Of these, 1,203 notebooks ran through without any errors, including 879 that produced results identical to those reported in the original notebook and 324 for which our results differed from the originally reported ones. Running the other notebooks resulted in exceptions.

CONCLUSIONS

We zoom in on common problems and practices, highlight trends, and discuss potential improvements to Jupyter-related workflows associated with biomedical publications.

Measuring the Concept of PID Literacy: User Perceptions and Understanding of PIDs in Support of Open Scholarly Infrastructure

The increasing centrality of persistent identifiers (PIDs) to scholarly ecosystems and the contribution they can make to the burgeoning “PID graph” has the potential to transform scholarship. Despite their importance as originators of PID data, little is known about researchers’ awareness and understanding of PIDs, or their efficacy in using them. In this article, we report on the results of an online interactive test designed to elicit exploratory data about researcher awareness and understanding of PIDs. This instrument was designed to explore recognition of PIDs (e.g. Digital Object Identifiers [DOIs], Open Researcher and Contributor IDs [ORCIDs], etc.) and the extent to which researchers correctly apply PIDs within digital scholarly ecosystems, as well as measure researchers’ perceptions of PIDs. Our results reveal irregular patterns of PID understanding and certainty across all participants, though statistically significant disciplinary and academic job role differences were observed in some instances. Uncertainty and confusion were found to exist in relation to dominant schemes such as ORCID and DOIs, even when contextualized within real-world examples. We also show researchers’ perceptions of PIDs to be generally positive but that disciplinary differences can be noted, as well as higher levels of aversion to PIDs in specific use cases and negative perceptions where PIDs are measured on an “activity” semantic dimension. This work therefore contributes to our understanding of scholars’ “PID literacy” and should inform those designing PID-centric scholarly infrastructures that a significant need for training and outreach to active researchers remains necessary.

DYSTOPIAN CASES OF ORCID IDENTIFIERS: ANIMAL-ASSOCIATED ACCOUNTS

DYSTOPIAN CASES OF ORCID IDENTIFIERS: ANIMAL-ASSOCIATED ACCOUNTS

ORCID coverage in research institutions—Readiness for partially automated research reporting

Reporting and presentation of research activities and outcome for research institutions in official, normative standards are more and more important and are the basis to comply with reporting duties. Institutional Current Research Information Systems (CRIS) serve as important databases or data sources for external and internal reporting, which should ideally be connected with interfaces to the operational systems for automated loading routines to extract relevant research information. This investigation evaluates whether (semi-) automated reporting using open, public research information collected via persistent identifiers (PIDs) for organizations (ROR), persons (ORCID), and research outputs (DOI) can reduce effort of reporting. For this purpose, internally maintained lists of persons to whom an ORCID record could be assigned (internal ORCID person lists) of two different German research institutions—Osnabrück University (UOS) and the non-university research institution TIB—Leibniz Information Center for Science and Technology Hannover—are used to investigate ORCID coverage in external open data sources like FREYA PID Graph (developed by DataCite), OpenAlex and ORCID itself. Additionally, for UOS a detailed analysis of discipline specific ORCID coverage is conducted. Substantial differences can be found for ORCID coverage between both institutions and for each institution regarding the various external data sources. A more detailed analysis of ORCID distribution by discipline for UOS reveals disparities by research area—internally and in external data sources. Recommendations for future actions can be derived from our results: Although the current level of coverage of researcher IDs which could automatically be mapped is still not sufficient to use persistent identifier-based extraction for standard (automated) reporting, it can already be a valuable input for institutional CRIS.

Understanding experiments and research practices for reproducibility: an exploratory study

Scientific experiments and research practices vary across disciplines. The research practices followed by scientists in each domain play an essential role in the understandability and reproducibility of results. The "Reproducibility Crisis", where researchers find difficulty in reproducing published results, is currently faced by several disciplines. To understand the underlying problem in the context of the reproducibility crisis, it is important to first know the different research practices followed in their domain and the factors that hinder reproducibility. We performed an exploratory study by conducting a survey addressed to researchers representing a range of disciplines to understand scientific experiments and research practices for reproducibility. The survey findings identify a reproducibility crisis and a strong need for sharing data, code, methods, steps, and negative and positive results. Insufficient metadata, lack of publicly available data, and incomplete information in study methods are considered to be the main reasons for poor reproducibility. The survey results also address a wide number of research questions on the reproducibility of scientific results. Based on the results of our explorative study and supported by the existing published literature, we offer general recommendations that could help the scientific community to understand, reproduce, and reuse experimental data and results in the research data lifecycle.

A New Research Economy: Socio-technical framework to open up lines of credit in the academic community

Journal articles have been the gold standard for research and scholarly communication. Specifically, measurements of publication and citation, particularly in high-impact journals, have long been the key means of accruing credit for researchers. In turn, these credits become the currency through which researchers acquire funding and achieve professional success. But, like global trade, tying in to a fixed standard limits wealth distribution and innovation. It is time for the research community to attribute credit for contributions that reflect and drive collaborative innovation, rewarding behaviors that produce better research outcomes.

Comprehensive Approach to Open Access Publishing: Platforms and Tools

The Open Access Initiative is gaining momentum due to the worldwide availability of advanced digital tools, online publishing platforms, and systems for tracking academic contributions. Several declarations and initiatives, including Plan S, have already laid a foundation for moving away from subscription to full and immediate open-access publishing. The global initiatives imply targeting journals satisfying the upgraded quality and visibility criteria. To meet these criteria, a comprehensive approach to Open Access is recommended. This article overviews the essential components of the comprehensive approach, increasing transparency, adherence to ethical standards, and diversification of evaluation metrics. With the increasing volume of quality open-access journals, their indexing with free databases and search engines is becoming increasingly important. The Directory of Open Access Journals and PubMed Central currently free searches of open-access sources. These services, however, cannot fully satisfy the increasing demands of the users, and attempts are underway to upgrade the indexing and archiving of open-access sources in China, Japan, Korea, Russia, and elsewhere. The wide use of identifiers is essential for transparency of scholarly communications. Peer reviewers are now offered credits from Publons. These credits are transferrable to their Open Researcher and Contributor iDs. Various social media channels are increasingly used by scholars to comment on articles. All these comments are tracked by related metric systems, such as Altmetrics. Combined with traditional citation evaluations, the alternative metrics can help timely identify and promote publications influencing education, research, and practice.

Ozymandias: a biodiversity knowledge graph

Enormous quantities of biodiversity data are being made available online, but much of this data remains isolated in silos. One approach to breaking these silos is to map local, often database-specific identifiers to shared global identifiers. This mapping can then be used to construct a knowledge graph, where entities such as taxa, publications, people, places, specimens, sequences, and institutions are all part of a single, shared knowledge space. Motivated by the 2018 GBIF Ebbe Nielsen Challenge I explore the feasibility of constructing a “biodiversity knowledge graph” for the Australian fauna. The data cleaning and reconciliation steps involved in constructing the knowledge graph are described in detail. Examples are given of its application to understanding changes in patterns of taxonomic publication over time. A web interface to the knowledge graph (called “Ozymandias”) is available at https://ozymandias-demo.herokuapp.com.