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      Aligning restricted access data with FAIR: a systematic review

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          Abstract

          Understanding the complexity of restricted research data is vitally important in the current new era of Open Science. While the FAIR Guiding Principles have been introduced to help researchers to make data Findable, Accessible, Interoperable and Reusable, it is still unclear how the notions of FAIR and Openness can be applied in the context of restricted data. Many methods have been proposed in support of the implementation of the principles, but there is yet no consensus among the scientific community as to the suitable mechanisms of making restricted data FAIR. We present here a systematic literature review to identify the methods applied by scientists when researching restricted data in a FAIR-compliant manner in the context of the FAIR principles. Through the employment of a descriptive and iterative study design, we aim to answer the following three questions: (1) What methods have been proposed to apply the FAIR principles to restricted data?, (2) How can the relevant aspects of the methods proposed be categorized?, (3) What is the maturity of the methods proposed in applying the FAIR principles to restricted data?. After analysis of the 40 included publications, we noticed that the methods found, reflect the stages of the Data Life Cycle, and can be divided into the following Classes: Data Collection, Metadata Representation, Data Processing, Anonymization, Data Publication, Data Usage and Post Data Usage. We observed that a large number of publications used ‘Access Control‘ and ‘Usage and License Terms’ methods, while others such as ‘Embargo on Data Release’ and the use of ‘Synthetic Data’ were used in fewer instances. In conclusion, we are presenting the first extensive literature review on the methods applied to confidential data in the context of FAIR, providing a comprehensive conceptual framework for future research on restricted access data.

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          The FAIR Guiding Principles for scientific data management and stewardship

          There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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            GenBank

            GenBank® (http://www.ncbi.nlm.nih.gov) is a comprehensive database that contains publicly available nucleotide sequences for almost 260 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and GenBank staff assigns accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI home page: www.ncbi.nlm.nih.gov.
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              Open Science Framework (OSF)

              GENERAL DESCRIPTION The Open Science Framework (OSF) is a tool that promotes open, centralized workflows by enabling capture of different aspects and products of the research lifecycle, including developing a research idea, designing a study, storing and analyzing collected data, and writing and publishing reports or papers. It is developed and maintained by the Center for Open Science (COS), a nonprofit organization founded in 2013 that conducts research into scientific practice, builds and supports scientific research communities, and develops research tools and infrastructure to enable managing and archiving research [1]. As an organization, the COS encourages openness, integrity, and reproducibility in research across scientific disciplines [2]. The OSF supports a variety of tools and services to assist in the research process. This review focuses primarily on the core functionality of the OSF, with brief descriptions of some of the other existing tools and services. FEATURES The core functionality of the OSF is its ability to create and develop projects. Very simply, a project functions as a workspace, with the design of a particular project depending on users and the type of research workflow that they are trying to manage and preserve. Users might wish to set up a project for a particular paper or specific experiment or for the work of an entire lab. To create a project, users must set up a free account with the OSF. Once logged in, users are taken to a dashboard with the option to create a project. The standard project layout includes a wiki, a log of recent activity, and spaces to upload files, add tags, and create new components (i.e., subprojects). Each user, project, component, and file is given a unique, persistent uniform resource locator (URL) to enable sharing and promote attribution. Projects can also be assigned digital object identifiers (DOIs) and archival resource keys (ARKs) if they are made publicly available. The OSF provides built-in version control that records changes to project files and previous versions through OSF Storage. The OSF is intended to be collaborative, and users can easily add contributors to projects. The OSF supports controlled access, so project members can be assigned different permissions: read only, read and write, and administrator. Contributors do not have to set up an OSF account prior to being added to projects. Unregistered contributors can be added to projects using their full names and email addresses; they will be contacted with a link to set up an OSF account. Contributors who already have an OSF account can be added to a project by searching for their names in the OSF. While the spirit of open science encourages making projects publicly available, there are options to make all or parts of a project private. The Project Overview page includes a toggle button that allows those with administrator-level permissions on the project to determine which parts of the project (if not all) will be public or private. In general, private projects are not browsable. Users can find public projects online. Certain components of a public project can be made private; those will be hidden from public view. To capture impact, the OSF also includes project-level analytics, such as unique visitors, downloads per project file, and top referrers. In addition to using unique, persistent URLs, DOIs, and ARKs, the OSF promotes sharing in a variety of additional ways. A primary one is the option to add a license. The COS links to resources for choosing a license with a variety of license options available, including Creative Commons, MIT, Apache, and GNU General Public. A user who does not wish to use any of the predetermined licenses can upload an alternative license. A license can apply to the project as a whole, or different licenses can be assigned to different parts of the project. While there are many features built into the OSF, the platform also allows third-party add-ons or integrations that strengthen the functionality and collaborative nature of the OSF. These add-ons fall into two categories: citation management integrations and storage integrations. Mendeley and Zotero can be integrated to support citation management, while Amazon S3, Box, Dataverse, Dropbox, figshare, GitHub, and oneCloud can be integrated to support storage. The OSF provides unlimited storage for projects, but individual files are limited to 5 gigabytes (GB) each. Using one of the storage add-ons eliminates this restriction. Registration is a major feature of the OSF and its efforts to preserve, provide access to, and promote transparency in research. Any OSF project can be registered, which means that a time-stamped version of the project is created that cannot be edited or deleted and is intended to act as a preserved version of a project. A user can, however, withdraw a project, which removes the content of the registered project but leaves behind a record of it. Registered projects can be made public immediately or embargoed for up to four years. Additionally, DOIs and ARKs can be created for public registrations. Any content stored on third-party servers is copied as part of the registration process and stored with the rest of the project content on OSF servers. USER COMMUNITY AND SERVICES The COS supports a diverse audience, from researchers and scientists to software developers to publishers and societies. While many of the features of the OSF are designed to help researchers create, manage, and preserve research, there are additional free OSF tools and services that can engage other user groups. OSF for Institutions allows institutions to create a landing page in the OSF to identify and connect affiliated users and projects. OSF users can identify their projects as being affiliated with particular institutions, and additional features, such as single-sign on and institutional branding of the landing page, can provide a seamless user experience for institutional affiliates using the OSF. OSF for Meetings provides a space to share posters and presentations from meetings and conferences. When a user registers a conference or meeting, the OSF will provide a branded, persistent page where conference attendees can upload posters and presentations, as well as browse content added by themselves or colleagues before, during, or after the event. OSF Preprints lets OSF users share preprints for feedback and to gain exposure. Each preprint receives a unique identifier, and users can upload supplementary files as needed. Users also have access to analytics for their uploaded preprints. In addition to engaging with user communities through these services, the COS maintains an Ambassador program, which works at local levels to promote and support open science at research institutions. These ambassadors represent the COS and can provide training and additional resources about the OSF or other COS products. A list of current COS ambassadors is available online. DOCUMENTATION AND TECHNICAL REQUIREMENTS As an open source service, the OSF has freely available documentation and support. The OSF home page has a link to support, including FAQs, contact information, and a set of OSF Guides that give step-by-step guidance and instructions on using the OSF. The COS also delivers regular workshops, webinars, and online tutorials. Past webinars can be viewed on the COS YouTube channel. Access to the OSF requires only a working computer and Internet connection. Larger collaborations such as the OSF for Institutions program require additional configuration by the COS and institutional information technology staff. CASE STUDIES One of the most prominent uses of the OSF tool is the Psychology Reproducibility Study, a collaboration between the University of Virginia and the COS. The more than 270 researchers involved in this project replicated 100 top psychology studies to see if they could produce the same results [3]. While the study results are interesting (they were able to replicate fewer than half), what is more interesting in this context is that the entire research process for each study—including data, analysis, publications, and comments—was openly shared on the OSF [4]. The Psychology Reproducibility Study highlights the strengths of the OSF, including collaboration features, the ability to create subprojects, and citation features, which allow researchers (and authors like us) to cite various components of the project. While this project is probably larger than most using the OSF, it serves as a good example of how health sciences researchers might integrate the tool into their research workflows. A smaller-scale example of OSF usage comes from the University of California–San Francisco (UCSF) Library, where, in the fall of 2015, a team of librarians used the OSF for an assessment project [5]. They selected the OSF because they needed a tool that would allow them to easily keep notes, upload files, collaborate, and share information (Figure 1). Figure 1 University of California–San Francisco (UCSF) Open Science Framework (OSF) project page Available at https://osf.io/d8nje/. While initial response to the OSF was positive, some team members found it confusing to navigate the various components and had trouble locating particular documents or wiki pages. The wiki feature also proved not to be as user-friendly as they had hoped, because the formatting options were limited and editing took some getting used to. Some of these challenges might have been due to the design of the project in the OSF; a more well-thought-out project with less hierarchy might have been easier to navigate. In the end, the team decided that while they liked some aspects of the tool, particularly the ability to assign a DOI to a project, their institutional wiki or Box account would have been a better tool for this project. They did note, however, that the OSF would provide an excellent way to collaborate with colleagues at other institutions who do not have access to UCSF-only tools. SUMMARY Because of its focus on openness and unique identifiers, the OSF can be an excellent tool for promoting best practices around reproducibility, transparency, and research data management. The high degree of flexibility means that projects can be customized easily to fit a variety of needs, from small projects to large research collaborations. Moreover, the COS is continually working to add more components and capabilities to the tool. As with all research tools, the usefulness of the OSF depends on how easily it can be adapted into a researcher’s workflow. The librarians at UCSF found it to be less useful than other tools they had available to them, but the example of the Psychology Reproducibility Study shows how the unique registration and collaboration features can provide a real benefit. Beyond researchers’ workflows, local institutional requirements or policies can also affect how the OSF can be used. For example, whether or not the OSF is Health Insurance Portability and Accountability Act (HIPAA)–compliant depends upon an institution’s security and privacy practices and would require further conversations with an institution’s information technology administration. Anyone interested in using the OSF is encouraged to create a free account and give it a try. Librarians might also consider inviting a local COS ambassador to give a presentation or contact the COS for a presentation on the OSF as a service or tool.
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                Author and article information

                Contributors
                Journal
                PeerJ Comput Sci
                PeerJ Comput Sci
                peerj-cs
                PeerJ Computer Science
                PeerJ Inc. (San Diego, USA )
                2376-5992
                20 July 2022
                2022
                : 8
                : e1038
                Affiliations
                Department of Computer Science, Vrije Universiteit Amsterdam , Amsterdam, Netherlands
                Author information
                http://orcid.org/0000-0002-1267-0234
                Article
                cs-1038
                10.7717/peerj-cs.1038
                9454861
                36091999
                a775ee2e-0294-4261-99f8-0f814bb1e53d
                © 2022 Martorana et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.

                History
                : 26 April 2022
                : 22 June 2022
                Funding
                Funded by: Netherlands Organisation of Scientific Research
                Funded by: ODISSEI Roadmap Project
                Award ID: 184.035.014
                This project is funded by the Netherlands Organisation of Scientific Research (NWO), ODISSEI Roadmap project: 184.035.014. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Data Science
                Security and Privacy

                linked data,restricted access data,fair guiding principles,fair implementation,confidential data

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