“KEY RESULTS: • Open Science principles: over half (59%) of the surveyed institutions rated Open Science’s strategic importance as very high or high. Open Access to research publications was considered to be highly important for 90% of institutions, but only 60% considered its implementation level to be high. However, the gap between importance and implementation is much wider in data-related areas (RDM, FAIR and data sharing): high importance at between 55-70% of the institutions surveyed, with high levels of implementation at 15-25%. • Open Science policies: 54% of institutions have an Open Science policy and 37% are developing one. Only 9% of surveyed institutions lack an Open Science policy or are not planning to draft one. • Monitoring Open Access to research publications: 80% of institutions monitored the number of publications in their repository and 70% monitored articles published by their researchers in Open Access journals. In addition, almost 60% reported monitoring the cost of publications by their researchers in Open Access journals. • Infrastructure for Open Access to research publications: 90% of the institutions surveyed have their own repository, participate in a shared repository or both. For journal hosting or publishing platforms this figure reaches 66%, and levels out at 57% for monograph hosting/publishing. In addition, 66% of those surveyed reported that their institution has participated in or supported non-commercial Open Access publishing. Data-related skills: over 50% of the surveyed institutions reported that research data skills were only partially available. Moreover, all of the institutions that indicated the absence or partial availability of data skills, considered that more of these skills are needed at institutional level. • Emerging areas of Open Science: Approximately 50% of the respondents know of citizen science and open education activities at their institutions. • Open Science in academic assessment: In 34% of institutions, none of the Open Science elements examined by the survey were included in academic assessments. Amongst the institutions that included Open Science activities in their academic assessments, 77% took into consideration article deposition in a repository. …”
Science and research are the building blocks connecting us with knowledge. As these are chiefly financed by the public sector, their results should be accessible to as many people as possible. Open Science describes the various efforts and activities which aim to reach this goal of bringing science to all.
“The Association of Research Libraries (ARL) has named Micah Vandegrift as a visiting program officer in the Scholars & Scholarship program for July 2021–July 2022. Vandegrift is the open knowledge librarian at NC State University Libraries.
As visiting program officer, Vandegrift will design and deliver a pilot experience for a cohort of eight ARL member libraries that are advancing open research practices at their institutions. The pilot Accelerating the Social Impact of Research (ASIR) program will help participants develop a strategic approach for advancing the social impact of science, aimed at building and reinforcing institutional points of influence for open research practices. This initiative is in coordination with the US National Academy of Sciences, Engineering, and Medicine (NASEM) roundtable on Aligning Incentives for Open Science and with the NASEM Board on Research Data and Information (BRDI)….”
By Agata Morka & Tom Mosterd
In May 2021, together with the Open Access Scholarly Publishing Association (OASPA), OPERAS hosted a series of three European workshops on business models for open access books targeted specifically at small and medium-sized academic book publishers1. As part of the OPERAS-P project work package 6 (Innovation) OPERAS was looking into innovative, non-BPC business models. The feedback gathered in the course of these three workshops informed a report The Future of scholarly communications, published at the end of June 2021 as an OPERAS-P project deliverable.
“Do you deliver Open Science and Research Data Management (RDM) training? Are you interested in integrating tools and creating engaging training sessions? Are you looking to prepare in-depth sessions and avoid any disasters? The SSHOC Open Science and Research Data Management Train-the-Trainer Bootcamp held on Monday 10th of May and Wednesday 12th of May 2021 was set to aid trainers in finding resources and tools they can re-use in their training planning and activities. This blogpost reviews the highlights of the bootcamp….”
“We often discuss publications and publishing open access (OA) materials in these news items, but the OA movement can be a part of many other steps of the research process. Many researchers choose to make the datasets their research is based on open access as well. This can be done as part of a funding institution’s requirements, to increase transparency and reproducibility, or simply because they wish to make their data easily available to other researchers.
One way students and faculty can find these datasets is through Google Dataset Search. Out of beta in early 2020, Google Dataset Search can be used to find links to datasets that have been published on the web and described via the schema.org standard. The internet does not include all datasets, and not all are described using this standard, but Google does claim that over 25 million datasets are indexed for searching….”
“UNLV University Libraries seeks nominations and applications for an innovative and collaborative tenure-track/tenured faculty member to serve as the Head, Scholarly Communication & Data Services.
UNLV’s recent designation as a Research I, Very High Research Activity University (Carnegie Classification of Institutions of Higher Education) highlights the changing direction of the University with a new and growing emphasis on the research, scholarship and creative activities of its faculty and students. This direction presents exciting opportunities for the University Libraries to lead, partner on, and contribute to institutional aspirations and strategic initiatives. To better support this climate of innovation, in which faculty and students produce high-quality, widely disseminated, and influential research, the University Libraries will implement an organizational restructuring. to create a new Scholarly Communication & Data Services department. By aligning expertise in this new department, the University Libraries will establish organizational leadership for the development of programs and tools that support UNLV researchers in creating, sharing and demonstrating the impact of their work. Existing and future programmatic areas of focus for the department will include: …”
At the beginning of June 2021, The National Strategy for Open Science 2021 – 2028, with its first Action Plan 2021 – 2022, was adopted by the Slovak government (both in the Slovak language are uploaded below, English version of the National Strategy will be available in September 2021). The creation of the National Strategy is an integral part of the Action Plan of the Open Government Partnership Initiative 2020-2021.
Abstract: The PDF Data Extractor (PDE) R package is designed to perform comprehensive literature reviews for scientists at any stage in a user-friendly way. The PDE_analyzer_i() function permits the user to filter and search thousands of scientific articles using a simple user interface, requiring no bioinformatics skills. In the additional PDE_reader_i() interface, the user can then quickly browse the sentences with detected keywords, open the full-text article, when required, and convert tables conveniently from PDF files to Excel sheets (pdf2table). Specific features of the literature analysis include the adaptability of analysis parameters and the detection of abbreviations of search words in articles. In this article, we demonstrate and exemplify how the PDE package allows the user-friendly, efficient, and automated extraction of meta-data from full-text articles, which can aid in summarizing the existing literature on any topic of interest. As such, we recommend the use of the PDE package as the first step in conducting an extensive review of the scientific literature. The PDE package is available from the Comprehensive R Archive Network at https://CRAN.R-project.org/package=PDE.
Abstract: INTRODUCTION This study explores the baseline knowledge and interest of faculty and graduate students at a Carnegie-classified Doctoral/Professional University regarding different components of scholarly communication. METHODS A survey was developed to inquire about such topics as scholarly research, scholarly publishing, access to research, copyright, measuring impact, promoting research, and open-educational resources. Responses more significantly represented the humanities and social sciences versus the natural and applied sciences. RESULTS & DISCUSSION Results showed some hesitancy in embracing the open access (OA) publishing model, especially the use of article processing charges (APCs). Faculty largely collect original data and believe public access to original data is important, but this varies by college and includes almost one-fourth of faculty who do not feel that sharing data is important. The areas in which respondents expressed the highest level of knowledge correlate directly with the areas in which respondents expressed the most interest in professional development. Preferences in professional development modality were split between virtual and in-person sessions. With virtual sessions specifically, graduate students prefer synchronous sessions while faculty prefer pre-recorded sessions. CONCLUSION Respondents were generally aware of the library’s current scholarly communications services, but additional promotion and marketing is still needed, especially for colleges with the lowest areas of engagement.
Abstract: Adoption of good research data management practices is increasingly important for research teams. Despite the work the research community has done to define best data management practices, these practices are still difficult to adopt for many research teams. Universities all around the world have been offering Research Data Services to help their research groups, and libraries are usually an important part of these services. A better understanding of the pressures and factors that affect research teams may help librarians serve these groups more effectively. The social interactions between the members of a research team are a key element that influences the likelihood of a research group successfully adopting best practices in data management. In this article we adapt the Unified Theory of the Acceptance and Use of Technology (UTAUT) model (Venkatesh, Morris, Davis, & Davis, 2003) to explain the variables that can influence whether new and better, data management practices will be adopted by a research group. We describe six moderating variables: size of the team, disciplinary culture, group culture and leadership, team heterogeneity, funder, and dataset decisions. We also develop three research group personas as a way of navigating the UTAUT model, and as a tool Research Data Services practitioners can use to target interactions between librarians and research groups to make them more effective.
Open Science holds the promise to make scientific endeavours more inclusive, participatory, understandable, accessible, and re-usable for large audiences. However, making processes open will not per se drive wide re-use or participation unless also accompanied by the capacity (in terms of knowledge, skills, financial resources, technological readiness and motivation) to do so. These capacities vary considerably across regions, institutions and demographics. Those advantaged by such factors will remain potentially privileged, putting Open Science’s agenda of inclusivity at risk of propagating conditions of “cumulative advantage”. With this paper, we systematically scope existing research addressing the question: “What evidence and discourse exists in the literature about the ways in which dynamics and structures of inequality could persist or be exacerbated in the transition to Open Science, across disciplines, regions and demographics?” Aiming to synthesise findings, identify gaps in the literature, and inform future research and policy, our results identify threats to equity associated with all aspects of Open Science, including Open Access, Open/FAIR Data, Open Methods, Open Evaluation, Citizen Science, as well as its interfaces with society, industry and policy. Key threats include: stratifications of publishing due to the exclusionary nature of the author-pays model of Open Access; potential widening of the digital divide due to the infrastructure-dependent, highly situated nature of open data practices; risks of diminishing qualitative methodologies as “reproducibility” becomes synonymous with quality; new risks of bias and exclusion in means of transparent evaluation; and crucial asymmetries in the Open Science relationships with industry and the public, which privileges the former and fails to fully include the latter.
Abstract: The Functional Annotation of ANimal Genomes (FAANG) project is a worldwide coordinated action creating high-quality functional annotation of farmed and companion animal genomes. The generation of a rich genome-to-phenome resource and supporting informatic infrastructure advances the scope of comparative genomics and furthers the understanding of functional elements. The project also provides terrestrial and aquatic animal agriculture community powerful resources for supporting improvements to farmed animal production, disease resistance, and genetic diversity. The FAANG Data Portal (https://data.faang.org) ensures Findable, Accessible, Interoperable and Reusable (FAIR) open access to the wealth of sample, sequencing, and analysis data produced by an ever-growing number of FAANG consortia. It is developed and maintained by the FAANG Data Coordination Centre (DCC) at the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI). FAANG projects produce a standardised set of multi-omic assays with resulting data placed into a range of specialised open data archives. To ensure this data is easily findable and accessible by the community, the portal automatically identifies and collates all submitted FAANG data into a single easily searchable resource. The Data Portal supports direct download from the multiple underlying archives to enable seamless access to all FAANG data from within the portal itself. The portal provides a range of predefined filters, powerful predictive search, and a catalogue of sampling and analysis protocols and automatically identifies publications associated with any dataset. To ensure all FAANG data submissions are high-quality, the portal includes powerful contextual metadata validation and data submissions brokering to the underlying EMBL-EBI archives. The portal will incorporate extensive new technical infrastructure to effectively deliver and standardise FAANG’s shift to single-cellomics, cell atlases, pangenomes, and novel phenotypic prediction models. The Data Portal plays a key role for FAANG by supporting high-quality functional annotation of animal genomes, through open FAIR sharing of data, complete with standardised rich metadata. Future Data Portal features developed by the DCC will support new technological developments for continued improvement for FAANG projects.
Much of the CORE Team’s focus involves developing services that underpin open research. The updates for this half-year include numerous examples of this in action. You can find details about these and more news below.
Infrastructures are being developed to enhance and facilitate the sharing of cohort data internationally. However, empirical studies show that many barriers impede sharing data broadly.
Therefore, our aim is to describe the barriers and concerns for the sharing of cohort data, and the implications for data sharing platforms.
Seventeen participants involved in developing data sharing platforms or tied to cohorts that are to be submitted to platforms were recruited for semi-structured interviews to share views and experiences regarding data sharing.
Credit and recognition, the potential misuse of data, loss of control, lack of resources, socio-cultural factors and ethical and legal barriers are elements that influence decisions on data sharing. Core values underlying these reasons are equality, reciprocity, trust, transparency, gratification and beneficence.
Data generators might use data sharing platforms primarily for collaborative modes of working and network building. Data generators might be unwilling to contribute and share for non-collaborative work, or if no financial resources are provided for sharing data.