Open Science – Page 6 – DigitalKoans

"Interoperable Infrastructure for Software and Data Publishing"

Achieving scalable, high-quality, interoperable data and software publishing is possible. There are already builders, some represented by the authorship of this article, that are on the right path, building tools that effectively meet the needs of researchers in an open and pluggable way. One example is InvenioRDM, a flexible and turn-key next-generation research data management repository built by CERN and more than 25 multi-disciplinary partners world-wide; InvenioRDM leverages community standards and supports FAIR practices out of the box. Another example of agnostic, pluggable tooling, in this case for software submission, are the submission workflow tools currently developed in the HERMES project. These allow researchers to automate the publication of software artifacts together with rich metadata, to create software publications following the FAIR Principles for Research Software.

http://bit.ly/42Lc5Oe

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Study on the Readiness of Research Data and Literature Repositories to Facilitate Compliance With the Open Science Horizon Europe MGA Requirement

In this study we analysed 220 repositories and, via a structured methodology, we identified 165 trusted repositories and tested their readiness to facilitate the compliance with the HE MGA Open Science requirements.

We show that it is not straightforward to assess whether a given repository is suitable to facilitate compliance with the HE MGA requirements. This is mainly due to varying interpretations of definitions and requirements, whether information on repository specifications is publicly available, and the high level of technical expertise needed to assess all requirements.

We highlight that repository registries, such as FAIRsharing, re3data or the CoreTrustSeal (CTS) website, are not sufficient on their own to assess the readiness of repositories to facilitate compliance with the HE MGA requirements, as the definition of what constitutes a trusted repository is subtle and varied and needs to be carefully interpreted and applied to repositories. This is also the case for related concepts such as community endorsement or for policy requirements in terms of preservation, curation and security of the repository contents.

https://doi.org/10.5281/zenodo.7728016

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"The Rapid Growth of Mega-Journals: Threats and Opportunities"

Mega-journals, those that publish large numbers of articles per year,¹ are growing rapidly across science and especially in biomedicine. Although 11 Scopus-indexed journals published more than 2000 biomedical full papers (articles or reviews) in 2015 and accounted for 6% of that year’s literature, in 2022 there were 55 journals publishing more than 2000 full articles, totaling more than 300 000 articles (almost a quarter of the biomedical literature that year). In 2015, 2 biomedical research journals (PLoS One and Scientific Reports) published more than 3500 full articles. In 2022, there were 26 such prolific journals (Table). The accelerating growth of mega-journals creates both threats and opportunities for biomedical science.

http://bit.ly/3nfZhio

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Open Access Policies in Latin America, the Caribbean and the European Union Progress towards a Political Dialogue

Latin America and the Caribbean and the European Union are strategic regions for one another and natural partners to collaborate in the development of research and innovation policy priorities such as open science. This work describes the open access policies for scientific production that have been developed in LAC and in the EU, analyses the common challenges and convergence avenue for both regions to establish a policy dialogue, and proposes specific recommendations for a joint policy action on which to base intra-LAC and EU-LAC collaboration. These are structured into 4 priority objectives broken down into 7 actions and 19 concrete measures.

https://op.europa.eu/s/yefB

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Only 10% Fully Understand "Preprint": "Framing COVID-19 Preprint Research as Uncertain: A Mixed-Method Study of Public Reactions"

Unlike hedging, preprint disclosure had no impact on audience message evaluations, nor vaccine attitudes and intentions. In one sense, this is a positive finding in that transparency about preprint status is unlikely to produce negative public reactions. Yet a likely explanation for the null effects is that most participants lacked the knowledge to differentiate between preprints and peer-reviewed research and did not understand this disclosure as an indicator of preliminary science. The qualitative data supported this explanation. When asked how they interpret the term "preprint" when they see it in a scientific news article, participants’ responses indicated that most had a limited understanding of the concept, even among those who received the preprint disclosure message with a brief explanation of the term. In total, only 10% of participants provided definitions of preprint that aligned with those accepted by the scholarly community. Only 15% described the term as an indicator of uncertain or preliminary evidence.

https://doi.org/10.1080/10410236.2023.2164954

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"Revisiting Methodology for Identifying Open Access Advantages"

This study revisited the methodology for identifying the effects of open access and revealed the causes for contradictory conclusions using four indices for journals that transitioned from subscription to open access. . . . Although the aggregated data of the eight journals indicated that open access had a positive effect, the effect varied across journals. A few journals produced different results between the two citation scores as well as between citation scores and number of citations or articles. Furthermore, a publisher’s choice of which journal to shift to open access influenced their performance after the shift.

https://doi.org/10.1007/s12109-023-09946-0

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"Ten Lessons for Data Sharing with a Data Commons"

A data commons is a cloud-based data platform with a governance structure that allows a community to manage, analyze and share its data. Data commons provide a research community with the ability to manage and analyze large datasets using the elastic scalability provided by cloud computing and to share data securely and compliantly, and, in this way, accelerate the pace of research. Over the past decade, a number of data commons have been developed and we discuss some of the lessons learned from this effort.

https://doi.org/10.1038/s41597-023-02029-x

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Paywall: "Open Data and the 2023 NIH Data Management and Sharing Policy"

As the largest public funder of biomedical research in the world, the National Institutes of Health’s (NIH) new Data Management and Sharing (DMS) Policy is a large step toward shifting the culture of medical research toward a broader sharing of scientific data. . . . This article will serve as a primer on open data, data sharing, the NIH’s DMS Policy and its implications, and how librarians can support researchers in this landscape.

https://doi.org/10.1080/02763869.2023.2168103

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"Geospatial Open Data Usage and Metadata Quality"

The Open Government Data portals (OGD), thanks to the presence of thousands of geo-referenced datasets, containing spatial information are of extreme interest for any analysis or process relating to the territory. For this to happen, users must be enabled to access these datasets and reuse them. An element often considered as hindering the full dissemination of OGD data is the quality of their metadata. Starting from an experimental investigation conducted on over 160,000 geospatial datasets belonging to six national and international OGD portals, this work has as its first objective to provide an overview of the usage of these portals measured in terms of datasets views and downloads. Furthermore, to assess the possible influence of the quality of the metadata on the use of geospatial datasets, an assessment of the metadata for each dataset was carried out, and the correlation between these two variables was measured. The results obtained showed a significant underutilization of geospatial datasets and a generally poor quality of their metadata. In addition, a weak correlation was found between the use and quality of the metadata, not such as to assert with certainty that the latter is a determining factor of the former.

https://doi.org/10.3390/ijgi10010030

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"China and Open Access"

In December 2022, the International Association of STM Publishers and the China Association for Science and Technology (CAST) released a report: Open Access Publishing in China. The report is openly available in both English and Chinese. This interview with Mark Robertson, consultant to the STM Association on the project, highlights the findings of the report and their implications for the scholarly publishing industry as well as providing background on the STM/CAST collaboration.

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"Research Data Management Needs Assessment for Social Sciences Graduate Students: A Mixed Methods Study"

The complexity and privacy issues inherent in social science research data makes research data management (RDM) an essential skill for future researchers. Data management training has not fully addressed the needs of graduate students in the social sciences. To address this gap, this study used a mixed methods design to investigate the RDM awareness, preparation, confidence, and challenges of social science graduate students. A survey measuring RDM preparedness and training needs was completed by 98 graduate students in a school of education at a research university in the southern United States. Then, interviews exploring data awareness, knowledge of RDM, and challenges related to RDM were conducted with 10 randomly selected graduate students. All participants had low confidence in using RDM, but United States citizens had higher confidence than international graduate students. Most participants were not aware of on-campus RDM services, and were not familiar with data repositories or data sharing. Training needs identified for social science graduate students included support with data documentation and organization when collaborating, using naming procedures to track versions, data analysis using open access software, and data preservation and security. These findings are significant in highlighting the topics to cover in RDM training for social science graduate students. Additionally, RDM confidence and preparation differ between populations so being aware of the backgrounds of students taking the training will be essential for designing student-centered instruction.

https://doi.org/10.1371/journal.pone.0282152

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"How and Why Do Researchers Reference Data? A Study of Rhetorical Features and Functions of Data References in Academic Articles"

Data reuse is a common practice in the social sciences. While published data play an essential role in the production of social science research, they are not consistently cited, which makes it difficult to assess their full scholarly impact and give credit to the original data producers. Furthermore, it can be challenging to understand researchers’ motivations for referencing data. Like references to academic literature, data references perform various rhetorical functions, such as paying homage, signaling disagreement, or drawing comparisons. This paper studies how and why researchers reference social science data in their academic writing. We develop a typology to model relationships between the entities that anchor data references, along with their features (access, actions, locations, styles, types) and functions (critique, describe, illustrate, interact, legitimize). We illustrate the use of the typology by coding multidisciplinary research articles (n=30) referencing social science data archived at the Inter-university Consortium for Political and Social Research (ICPSR). We show how our typology captures researchers’ interactions with data and purposes for referencing data. Our typology provides a systematic way to document and analyze researchers’ narratives about data use, extending our ability to give credit to data that support research.

https://arxiv.org/abs/2302.08477

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2.6 Billion Total Downloads: arXiv Annual Report 2022

Our critical priorities during 2022 were to secure additional funding, hire technical and program directors, and ramp up our efforts to modernize arXiv’s software by moving it to the cloud, which will provide better stability, scalability and maintainability. I’m pleased to report that we were able to make significant progress on all of these fronts. arXiv brought in more funding than expected in the form of grants, memberships, and donations, and we hired Stephanie Orphan as program director and Charles Frankston as technical director. Both bring strong and complementary expertise to the team. Moving the technical operations of arXiv—a service with a 30 year history—off of Cornell’s on-premises servers is a major, complicated task. The move to the cloud is currently in progress and on track

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"Data Management Librarians Role in a Large Interdisciplinary Scientific Grant for PFAS Remediation: Considerations and Recommendations"

This article explores the conflicts, disparities, and inequalities experienced by two librarians when collaborating on a federal grant proposal. The authors discuss concerns related to time and salary expectations and the inequities that can occur during faculty and staff collaborations on research grants. The bureaucratic structure and the job classifications of staff at academic institutions in addition to the contract limitations of non-faculty status librarian positions can hinder successful collaborations. The authors also describe data management needs that may occur when working with interdisciplinary research teams and detail the type of work that is included in writing a data management grant. This article concludes with considerations and recommendations for other data librarians who may undertake similar projects with a focus on ways to create parity between faculty and staff collaborators.

https://doi.org/10.7191/jeslib.616

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"There’s No “I” in Research Data Management: Reshaping RDM Services Toward a Collaborative Multi-Stakeholder Model"

Objective: This article examines a reshaped service model for research data management (RDM) founded on centralized and cohesive collaboration between multiple stakeholders at a large research university in Canada. This initiative, along with a newly formed team dedicated to RDM service provision, is a joint effort by the institution’s Vice-Principal Research and Innovation (VPRI), Library, IT Services, and Research Ethics units.

Methods: This article presents a single case study methodology. The authors reflect on services such as "query the panel" sessions where researchers across all disciplines bring their questions to representatives from the Library, IT, Research Ethics, and VPRI. This case study also highlights the use of Jira’s service desk software as a user management system. The authors also present descriptive statistics representing engagement with this new unit and our services.

Results: Support for RDM requires expertise from multiple domains. With a collaborative approach as a guiding principle and a focus on establishing a small, but agile team comprised of a librarian along with stakeholders from IT and VPRI, it is possible to leverage resources and support for RDM from a broad range of units across an institution.

Conclusions: At many institutions, RDM services are siloed within the library or an adjacent campus unit. New digital technologies have profoundly transformed academic research across all disciplines, necessitating the evolution of corresponding research data-related services. The authors will conclude by outlining specific lessons learned in reshaping digital research infrastructure-related services at their institution.

https://doi.org/10.7191/jeslib.624

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"Are Institutional Research Data Policies in the US Supporting the FAIR Principles? A Content Analysis"

Objective: The FAIR principles were created with the goal of enhancing the reusability of research data and to give guidance on how to make data Findable, Accessible, Interoperable and Reusable. In this article we explore the role of institutional research data policies in enabling and encouraging researchers at their institutions to generate FAIR data.

Methods: We identified the research data policies in place for “very high research activity” institutions (as defined by Carnegie classification) in the United States. We created a list of 31 criteria, based on previous work by Davidson et al. (2019) and Briney et al. (2015), and evaluated the 40 policies using a content analysis methodology.

Results: The guiding principles and the definitions for research data in the policies support the idea that institutional policies are a potential tool for the implementation of the FAIR principles. However, our analysis indicates that they are not generally used for that purpose. Only one policy mentions FAIR. Data sharing is mentioned in half of the policies, but 11 of these only note this concept in the context of funder requirements. Access and retention sections are mostly written without considering publicly available data. Twenty-nine policies do not mention data documentation.

Conclusions: We discuss ways in which these institutional policies represent a missed opportunity to implement the FAIR principles and suggest ways policies could be modified to encourage researchers to follow them. We also discuss future research opportunities to examine how policy implementation may affect what institutional support researchers receive.

https://doi.org/10.7191/jeslib.614

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Rethinking Data and Rebalancing Digital Power

This report highlights and contextualises four cross-cutting interventions with a strong potential to reshape the digital ecosystem:

Transforming infrastructure into open and interoperable ecosystems.

Reclaiming control of data from dominant companies.

Rebalancing the centres of power with new (non-commercial) institutions.

Ensuring public participation as an essential component of technology policymaking.

http://bit.ly/40WNbKA

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"The Role of Open Data in Digital Society: The Analysis of Scientific Trending Topics through a Bibliometric Approach"

The analysis of contemporary society, characterized by technological, economic, political, social, and cultural changes, has become more challenging due to the development of the internet and information and communication technologies, which provide a vast and increasingly valuable source of information, knowledge, and data. Within this context, so-called open data—that is, data that are made public, especially by public administrations, through an open governance model (transparent and accessible to citizens) are assuming a significant role. This is a topic of growing importance that scientific research is addressing in an attempt to discern the multiplicity of social, educational, legal, technological, statistical, and methodological issues that underlie the creation and use of such data. This article aims to provide insights into understanding scientific trends on the topic of open data through a bibliometric approach. Specifically, a total of 3,110 publications related to the disciplinary fields of the social sciences and humanities published from 2013 to 2022 were collected. The data was then analyzed using network and factorial analysis techniques to detect the conceptual structure to identify the trends of topics and perspectives of research that characterize open data studies.

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"Data Archive for the BRAIN Initiative (DABI)"

Data sharing is becoming ubiquitous and can be advantageous for most biomedical research. However, some data are inherently more amenable to sharing than others. For example, human intracranial neurophysiology recordings and associated multimodal data have unique features that warrant special considerations. The associated data are heterogeneous, difficult to compare, highly specific, and collected from small cohorts with treatment resistant conditions, posing additional complications when attempting to perform generalizable analyses across projects. We present the Data Archive for the BRAIN Initiative (DABI) and describe features of the platform that are designed to overcome these and other challenges. DABI is a data repository and portal for BRAIN Initiative projects that collect human and animal intracranial recordings, and it allows users to search, visualize, and analyze multimodal data from these projects. The data providers maintain full control of data sharing privileges and can organize and manage their data with a user-friendly and intuitive interface. We discuss data privacy and security concerns, example analyses from two DABI datasets, and future goals for DABI.

https://doi.org/10.1038/s41597-023-01972-z

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Data Preservation in High Energy Physics: DPHEP Global Report 2022

This document summarizes the status of data preservation in high energy physics. The paradigms and the methodological advances are discussed from a perspective of more than ten years of experience with a structured effort at international level. The status and the scientific return related to the preservation of data accumulated at large collider experiments are presented, together with an account of ongoing efforts to ensure long-term analysis capabilities for ongoing and future experiments. Transverse projects aimed at generic solutions, most of which are specifically inspired by open science and FAIR principles, are presented as well. A prospective and an action plan are also indicated.

https://arxiv.org/abs/2302.03583

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"Data Sharing and Reuse Practices: Disciplinary Differences and Improvements Needed"

This study investigates differences and commonalities in data production, sharing and reuse across the widest range of disciplines yet and identifies types of improvements needed to promote data sharing and reuse. . . .From the 3,257 survey responses, data sharing and reuse are still increasing but not ubiquitous in any subject area and are more common among experienced researchers.

https://doi.org/10.1108/OIR-08-2021-0423

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"Analysis of U.S. Federal Funding Agency Data Sharing Policies: 2020 Highlights and Key Observations "

Federal funding agencies in the United States (U.S.) continue to work towards implementing their plans to increase public access to funded research and comply with the 2013 Office of Science and Technology memo Increasing Access to the Results of Federally Funded Scientific Research. In this article we report on an analysis of research data sharing policy documents from 17 U.S. federal funding agencies as of February 2021. Our analysis is guided by two questions: 1.) What do the findings suggest about the current state of and trends in U.S. federal funding agency data sharing requirements? 2.) In what ways are universities, institutions, associations, and researchers affected by and responding to these policies? Over the past five years, policy updates were common among these agencies and several themes have been thoroughly developed in that time; however, uncertainty remains around how funded researchers are expected to satisfy these policy requirements.

http://www.ijdc.net/article/view/791

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Forthcoming: Discoverability in Digital Repositories: Systems, Perspectives, and User Studies

It examines discoverability in digital repositories from both user and system perspectives by exploring how users access content (including their search patterns and habits, need for digital content, effects of outreach, or integration with Wikipedia and other web-based tools) and how systems support or prevent discoverability through the structure or quality of metadata, system interfaces, exposure to search engines or lack thereof, and integration with library discovery tools.

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"Cluster Analysis of Open Research Data: A Case for Replication Metadata"

Research data are often released upon journal publication to enable result verification and reproducibility. For that reason, research dissemination infrastructures typically support diverse datasets coming from numerous disciplines, from tabular data and program code to audio-visual files. Metadata, or data about data, is critical to making research outputs adequately documented and FAIR. Aiming to contribute to the discussions on the development of metadata for research outputs, I conducted an exploratory analysis to determine how research datasets cluster based on what researchers organically deposit together. I use the content of over 40,000 datasets from the Harvard Dataverse research data repository as my sample for the cluster analysis. I find that the majority of the clusters are formed by single-type datasets, while in the rest of the sample, no meaningful clusters can be identified. For the result interpretation, I use the metadata standard employed by DataCite, a leading organization for documenting a scholarly record, and map existing resource types to my results. About 65% of the sample can be described with a single-type metadata (such as Dataset, Software orReport), while the rest would require aggregate metadata types. Though DataCite supports an aggregate type such as a Collection, I argue that a significant number of datasets, in particular those containing both data and code files (about 20% of the sample), would be more accurately described as a Replication resource metadata type. Such resource type would be particularly useful in facilitating research reproducibility.

http://www.ijdc.net/article/view/833

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"Influence of Research on Open Science in the Public Policy Sphere"

This paper analyses the scientific activity related to open science in Spain and its influence on public policy from a bibliometric perspective. For this purpose, Spanish centres’ projects and publications on open science from 2010 to 2020 are studied. Subsequently, policy documents using papers related to open science are analysed to study their influence on policymaking. A total of 142 projects and 1491 publications are analysed, 15% of which are mentioned in policy documents.The publications cited in policy documents display high proportions of international collaboration, open access publication and publication in first-quartile journals. The findings underline governments’ leading role in the implementation of open science policies and the funding of open science research. The same government agencies that promote and fund open science research are shown to use that research in their institutional reports, a process known as knowledge flow feedback. Other non-academic actors are also observed to make use of the knowledge produced by open science research, showing how the open science movement has crossed the boundaries of academia.

https://doi.org/10.1007/s11192-023-04645-1

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