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Trust markers - the explicit statements on a paper such as funding, data availability, conflict of interest, author contributions, and ethical approval - represent a contract between authors and readers that proper research practices have been observed. Trust markers highlight research a level of transparency within a publication and reduce the reputational risks of allowing non-compliance to research integrity policies to go unobserved. Dimensions Research Integrity introduces a new ability to measure the uptake and usage of trust markers across the global published landscape, based on the analysis of 33M full text articles. This paper outlines how the Research Integrity dataset was created from algorithms developed at Ripeta. Also we show why it is important for publishers, funders, and institutions to systematically measure trust markers across their articles.

The Association of Research Libraries (ARL) has released the results of a questionnaire, developed with the US National Committee for CODATA, intended to identify potential areas of synergy and interests among US-based research data organizations. This report is a first step in building community among US-based research data organizations. The report will inform the US National Committee for CODATA’s plans for a series of virtual convenings to discuss shared interests among cross-sector research data organizations, culminating in an in-person US Research Data Summit. The aim is to create a shared agenda that reduces duplication of effort within the United States and that positions research data organizations from the US to engage effectively in international discussions. The questionnaire was distributed to 80 organization representatives with national and international research data goals, including organizations that are cross-functional, disciplinary, representative of scholars, government, industry, nonprofit organizations, and underrepresented communities.

The Realities of Academic Data Sharing (RADS) Initiative’s public-access data management and sharing (DMS) activities are the result of categorizing services and support across the institution that are likely needed to make public access to research data available. The RADS project team categorized these activities by life-cycle phases for public access to research data, and used the activities in RADS surveys of publicly funded campus researchers and institutional administrators whose departments likely provide support in these areas. The result of categorizing and defining these activities not only delineated questions for RADS’s retrospective studies, but, consequently, may also help researchers, administrators, and librarians prepare for upcoming federal and institutional policies requiring access to publicly funded research data. This report presents version 1 of the RADS public access DMS activities. Additional versions are expected to be released as more institutions engage in implementing new federal policies in the coming months. Community engagement and feedback on the RADS DMS activities is critical to (1) validate the activities and (2) parse out the activities, as sharing and refining them will benefit stakeholders interested in meeting new federal open-access and sharing policies.

Open access (OA) and the broad sharing of research outputs has been empirically shown to accelerate scientific progress and benefit society and individuals at scale through improved health outcomes, socioeconomic mobility, and environmental well-being, to name a few. Academic research libraries, for their part, have made significant investments in opening up research and scholarship—particularly research conducted on their campuses and made available through journal subscriptions. Yet these investments are difficult to collect given their distribution across many budget lines, the lack of standardized reporting categories, and inconsistent data collection practices. In May–June 2022 the Association of Research Libraries (ARL) undertook a survey of its US-based academic research libraries to better understand OA expenses. This report presents the survey results.

The identification and subsequent analysis of research articles for machine learning and natural language processing is a complicated task given the lack of consistent article organization principles and heading naming conventions across publishers and journals. Given this, an understanding of how research articles organizationally follow a common function and their use of various heading terms, or forms, is a critical step in applying machine learning techniques for data and information mining across a corpus of articles. To address this need, the authors developed and implemented an article heading form and function analysis across 12 publishers including both research articles and nonresearch articles. Our aim was to (a) identify each of the labeled sections used by research articles, define these sections based on their rhetorical function, and determine frequency of use; (b) within the given data set, determine all of the alternative labels used to identify these sections; and (c) determine whether these sections can be used to consistently determine (1) whether an article is a true research article, or (2) whether an article is not a research article. The results indicated wide variability in the organization of research articles with 24 common sections, known by 186 different names both within and across publishing houses.

This is the first report of a six-month pilot cohort program from 2021, Accelerating the Social Impact of Research (ASIR). The pilot engaged small teams from eight ARL member libraries who wanted to share strategies to accelerate the adoption and implementation of open-science principles for social-impact research and scholarship. The report, Accelerating Social Impact Research: Libraries at the Intersection of Openness and Community-Engaged Scholarship, sets the context for this confluence, draws examples from the participating members of the cohort, and identifies the opportunities available for research library leaders. The next installments of this publication series will include additional profiles of the cohort libraries and how they are advancing open scholarship and community engagement.

This chapter contributes to academic library institutions currently engaged in or formulating their strategy for engaging in data science. The chapter provides academic library institutions, and library and information science students, with a context in which to consider how they can collaborate locally and internationally to advance the use of data by scholars (students, researchers, and the public). Presented from the perspective of an association of research libraries, the chapter explores how, together, research libraries work with others to convene, inform, shape, and influence data science and data research policies and practices. The chapter provides examples of data and data science collaborations in teaching, learning, and research so the reader can identify specific skills and knowledge they may need or want to develop in order to collaborate, and they can learn about at least one existing or emerging type of collaboration they would like to explore further.

Появляющиеся технологии революционизируют сферу научной коммуникации. Поэтому ученые все больше нуждаются в особой поддержке на всех этапах исследовательского процесса. На примере академической (научной) библиотеки, взятой в качестве единицы анализа, рассматриваются два понятия из теории «Диффузия инноваций» (DOI) Роджерса и литературы по организации инноваций, чтобы оценить возможность устойчивой работы по научной коммуникации в библиотеках. Это понятия организационной реструктуризации и формализации. Анализируются данные по сотрудникам Ассоциации научных библиотек (Association of Research Libraries, ARL) с соответствующими названиями занимаемой должности и трем документам о навыках в цифровом кураторстве. Результаты исследования предполагают, что информационные организации ARL реструктурированы, чтобы обеспечивать дополнительную поддержку исследований и чтобы навыки, связанные с должностью в научной коммуникации, становились более унифицированными. Делается вывод, что информационные специалисты в области научной коммуникации являются частью устойчивой практической области в рамках информационных организаций ARL, доминирующей последние десятилетия, и что подобная тенденция, скорее всего, продолжится, по крайней мере, в краткосрочной перспективе.

With increasing world-wide emphasis on providing access to research data, data management plans (DMPs) have emerged as the expected way for researchers to formalise and communicate their intentions to stakeholders, including to their funders. This review paper focuses on a thematic analysis and presentation of empirical research on DMPs, a literature that is surprisingly limited, likely due to the young age of the field. Research shows that, despite the benefits associated with data sharing, DMPs have potential that is not being realised to the fullest. Researchers in scholarly communication and information science primarily have evaluated DMPs using text analysis methodologies, often supplementing them with surveys or interviews. Future study, especially in areas of machine-actionable DMPs is promising; such research is needed to further explore how DMPs can best be utilised to support data sharing.

Research data curation is a set of scientific communication processes and activities that support the ethical reuse of research data and uphold research integrity. Data curators act as key collaborators with researchers to enrich the scholarly value and potential impact of their data through preparing it to be shared with others and preserved for the long term. This special issues focuses on practical data curation workflows and tools that have been developed and implemented within data repositories, scholarly societies, research projects, and academic institutions.

Data curation, discovery, reuse, and citation are accelerating scholarship across diverse fields and disciplines, but fall far short of the potential. Stakeholders across campuses are asked to “do better” at managing research data outputs. Often this comes with jargon-filled mandates that are difficult to translate into concrete action. In the summer of 2019, NSF published a clear, concrete call to action for researchers in a Dear Colleague Letter. In an effort to amplify that call and offer clarity to campus stakeholders, ARL, AAU, APLU, and CDL partnered to convene 40 experts in order to create clear, actionable, easy-to-understand guidance.The resulting report Implementing Effective Data Practices: Stakeholder recommendations for collaborative research support was recently released. This report provides specific recommendations for adopting and implementing persistent identifiers and supporting machine readable data management plans across an institution and within an organization or technology platform. It also provides key considerations for funders in adopting and requiring these critical infrastructure components. While the adoption and implementation of these best practices may be straightforward for some, communication about the importance of this infrastructure and the ease with which it may be implemented is needed. To support institutional and organizational efforts in the adoption of this infrastructure, the project team has developed a communication toolkit that includes various slide decks and talking points. This presentation will introduce these key areas and provide attendees with an introduction to toolkit and how they can leverage it to promote adoption of persistent identifiers for various stakeholders.

The novel coronavirus, COVID-19, has sparked an outflow of scientific research seeking to understand the virus, its spread, and best practices in prevention and treatment. If this international research effort is going to be as swift and effective as possible, it will need to rely on a principle of open science. When researchers share data, code, and software and generally make their work as transparent as possible, it allows other researchers to verify and expand upon their work. Furthermore, it allows public officials to make informed decisions. In this study, we analyzed 535 preprint articles related to COVID-19 for eight transparency criteria and recorded study location and funding information. We found that individual researchers have lined up to help during this crisis, quickly tackling important public health questions, often without funding or support from outside organizations. However, most authors could improve their data sharing and scientific reporting practices. The contrast between researchers’ commitment to doing important research and their reporting practices reveals underlying weaknesses in the research community’s reporting habits, but not necessarily their science.

Information professionals housed in academic libraries are increasingly taking a role in supporting scholarly communication activities. This article investigates the extent to which a formal role has grown in ARL libraries, the skills and competencies necessary for supporting work with data in this capacity, and how those skills and competencies relate to the research lifecycle. We find that scholarly communication has formalized in ARL libraries since 2012. We also find that the requisite skills and competencies for scholarly communication work have coalesced since 2009 in support of a core group that, when the research lifecycle is considered, also support the work of scholars.

Deletion and truncation mutations in the X-linked gene CASK are associated with severe intellectual disability (ID), microcephaly and pontine and cerebellar hypoplasia in girls (MICPCH). The molecular origin of CASK-linked MICPCH is presumed to be due to disruption of the CASK-Tbr-1 interaction. This hypothesis, however, has not been directly tested. Missense variants in CASK are typically asymptomatic in girls. We report three severely affected girls with heterozygous CASK missense mutations (M519T (2), G659D (1)) who exhibit ID, microcephaly, and hindbrain hypoplasia. The mutation M519T results in the replacement of an evolutionarily invariant methionine located in the PDZ signaling domain known to be critical for the CASK-neurexin interaction. CASK(M519T) is incapable of binding to neurexin, suggesting a critically important role for the CASK-neurexin interaction. The mutation G659D is in the SH3 (Src homology 3) domain of CASK, replacing a semi-conserved glycine with aspartate. We demonstrate that the CASK(G659D) mutation affects the CASK protein in two independent ways: 1) it increases the protein’s propensity to aggregate; and 2) it disrupts the interface between CASK’s PDZ (PSD95, Dlg, ZO-1) and SH3 domains, inhibiting the CASK-neurexin interaction despite residing outside of the domain deemed critical for neurexin interaction. Since heterozygosity of other aggregation-inducing mutations (e.g., CASK(W919R)) does not produce MICPCH, we suggest that the G659D mutation produces microcephaly by disrupting the CASK-neurexin interaction. Our results suggest that disruption of the CASK-neurexin interaction, not the CASK-Tbr-1 interaction, produces microcephaly and cerebellar hypoplasia. These findings underscore the importance of functional validation for variant classification.

Qualitative data provide rich information on research questions in diverse fields. Recent calls for increased transparency and openness in research emphasize data sharing. However, qualitative data sharing has yet to become the norm internationally and is particularly uncommon in the United States. Guidance for archiving and secondary use of qualitative data is required for progress in this regard. In this study, we review the benefits and concerns associated with qualitative data sharing and then describe the results of a content analysis of guidelines from international repositories that archive qualitative data. A minority of repositories provide qualitative data sharing guidelines. Of the guidelines available, there is substantial variation in whether specific topics are addressed. Some topics, such as removing direct identifiers, are consistently addressed, while others, such as providing an anonymization log, are not. We discuss the implications of our study for education, best practices, and future research.

SHARE, an open metadata aggregator for scholarly content launched in 2013, provides access to dispersed scholarly content through a powerful application programming interface and set of tools for r...

Background The reproducibility of research is essential to rigorous science, yet significant concerns of the reliability and verifiability of biomedical research have been recently highlighted. Ongoing efforts across several domains of science and policy are working to clarify the fundamental characteristics of reproducibility and to enhance the transparency and accessibility of research. Methods The aim of the proceeding work is to develop an assessment tool operationalizing key concepts of research transparency in the biomedical domain, specifically for secondary biomedical data research using electronic health record data. The tool (RepeAT) was developed through a multi-phase process that involved coding and extracting recommendations and practices for improving reproducibility from publications and reports across the biomedical and statistical sciences, field testing the instrument, and refining variables. Results RepeAT includes 119 unique variables grouped into five categories (research design and aim, database and data collection methods, data mining and data cleaning, data analysis, data sharing and documentation). Preliminary results in manually processing 40 scientific manuscripts indicate components of the proposed framework with strong inter-rater reliability, as well as directions for further research and refinement of RepeAT. Conclusions The use of RepeAT may allow the biomedical community to have a better understanding of the current practices of research transparency and accessibility among principal investigators. Common adoption of RepeAT may improve reporting of research practices and the availability of research outputs. Additionally, use of RepeAT will facilitate comparisons of research transparency and accessibility across domains and institutions. Electronic supplementary material The online version of this article (doi:10.1186/s12874-017-0377-6) contains supplementary material, which is available to authorized users.

Emerging technologies are revolutionizing the field of scholarly communication. Because of this, scholars increasingly need specialized support during all stages of the research process. With the academic library as the unit of analysis, two concepts from Rogers’ Diffusion of Innovation theory and organizational innovation literature are drawn upon to assess the sustainability of scholarly communication work in libraries. These concepts are organizational restructuring and formalization. Data on Association of Research Libraries (ARL) employees with relevant job titles and three digital curation competencies documents are analysed. Study findings suggest that ARL information agencies have restructured to provide added research sup-port and that skills associated with scholarly communication positions are becoming more uniform. We conclude that scholarly communication information professionals are part of a sustainable area of practice within ARL information agencies, that has matured over the past decade, and this trend is likely to continue in at least the short term.

Making Science Better: Reproducibility, Falsifiability and the Scientific Method looks at the current state of reproducibility in 2019, as well as the importance of falsifiability in the research process.The analysis comes from the Digital Science portfolio company, Ripeta, which aims to make better science easier by identifying and highlighting the important parts of research that should be transparently presented in a manuscript and other materials. The report addresses three areas including appropriate documentation and sharing of research data, clear analysis and processes, and the sharing of code.

Funders increasingly require that data sets arising from sponsored research must be preserved and shared, and many publishers either require or encourage that data sets accompanying articles are made available through a publicly accessible repository. Additionally, many researchers wish to make their data available regardless of funder requirements both to enhance their impact and also to propel the concept of open science. However, the data curation activities that support these preservation and sharing activities are costly, requiring advanced curation practices, training, specific technical competencies, and relevant subject expertise. Few colleges or universities will be able to hire and sustain all of the data curation expertise locally that its researchers will require, and even those with the means to do more will benefit from a collective approach that will allow them to supplement at peak times, access specialized capacity when infrequently-curated types arise, and stabilize service levels to account for local staff transition, such as during turn-over periods. The Data Curation Network (DCN) provides a solution for partners of all sizes to develop or to supplement local curation expertise with the expertise of a resilient, distributed network, and creates a funding stream to both sustain central services and support expansion of distributed expertise over time. This paper presents our next steps for piloting the DCN, scheduled to launch in the spring of 2018 across nine partner institutions. Our implementation plan is based on planning phase research performed from 2016-2017 that monitored the types, disciplines, frequency, and curation needs of data sets passing through the curation services at the six planning phase institutions. Our DCN implementation plan includes a well-coordinated and tiered staffing model, a technology-agnostic submission workflow, standardized curation procedures, and a sustainability approach that will allow the DCN to prevail beyond the grant-supported implementation phase as a curation-as-service model.

The COVID-19 pandemic has posed many challenges for academic and research libraries and those working within them. Nearly everything that we do has been questioned and re-envisioned, and our days are filled with new work, uncertainty, and isolation. Because of this, one of the areas that library leaders must invest in re-envisioning is how we can best support the well-being and morale of our library colleagues. This article identifies and discusses simple, informal, practical, and easy strategies that library leaders can use to support the physical, emotional, spiritual, professional, social, and mental well-being of their teams in remote and hybrid working environment.

Niche and proprietary data formats used in cutting-edge research and technology have specific curation considerations and challenges. The increased demand for subject liaisons, library archivists, and digital curators to curate this variety of data types created locally at an institution or organization poses difficulties. Subject liaisons possess discipline knowledge and expertise for a given domain or discipline and digital curation experts know how to properly steward data assets generally. Yet, a gap often exists between the expertise available within the organization and local curation needs. While many institutions and organizations have expertise in certain domains and areas, oftentimes the heterogeneous data types received for deposit extend beyond this expertise. Additionally, evolving research methods and new, cutting-edge technology used in research often result in unfamiliar and niche data formats received for deposit. Knowing how to ‘get-started’ in curating these file types and formats can be a particular challenge. To address this need, the data curation community have been developing a new set of tools - data curation primers. These primers are evolving documents that detail a specific subject, disciplinary area or curation task, and that can be used as a reference or jump-start to curating research data. This paper will provide background on the data curation primers and their content detail the process of their development, highlight the data curation primers published to date, emphasize how curators can incorporate these resources into workflows, and show curators how they can get involved and share their own expertise.