Sharing data at the end of the research

M1 Research Data Management M2 Visibility of the activity and networking Orientation module M4 Advice and technical support M3 CAS in DATA STEWARDSHIP SHARING DATA AT THE END OF THE RESEARCH Storing, preserving and sharing data at the end of the research Marielle Guirlet (UNIL) 2024-2025 2 ABOUT THIS PRESENTATION This presentation is released under a CC BY 4.0 license, which means that you are free to reuse, distribute, remix, adapt, and build upon the material in any medium or format only so long as attribution is given to the creator. If you remix, adapt, or build upon the material, we highly recommend to license the modified material under identical terms. This course is part of the CAS in Data Stewardship. Author Dr. Marielle Guirlet Provider University of Lausanne Title Sharing data at the end of the research Education level Graduates Language English License CC BY 4.0 Estimate total time 1h Version v20241120 How to attribute GUIRLET, Marielle (University of Lausanne) 2024. Storing, preserving and sharing data at the end of the research: Sharing data at the end of the research. [Lausanne]. CAS Data Stewardship UNIL. 22 November 2024. 3 PLAN OF THIS PART This sub-lesson aims to address: •what is data sharing •why •when •where •how … to share data at the end of the research 4 PREPARATION WORK Tasks Institutional strategy, recommendations, resources Role and tasks of support professionals for sharing data Readings Open research data: a first look at sharing practices (Gorin et al. 2024) Data sharing, management, use and reuse: Practices and perceptions of scientists worldwide (Tenopir et al. 2020) 5 CONTEXT OS and (O)RD CAS in Data Stewardship UNIL 2024-2025 (Credit: CC BY, https://www.aukeherrema.nl) OPEN SCIENCE Source: UNESCO Recommendation on Open Science (2021). UNESCO’s vision OPEN SCIENCE Efficiency (reusability, RoI) Innovation Visibility Uniqueness of data UNESCO’s vision Source: UNESCO Recommendation on Open Science (2021). 8 Research Data Main sources of research Produced in different ways From and for research New research Validate research Documentation Different kinds Various formats and supports RESEARCH DATA 9 WHAT IS SHARING DATA (AND WHAT IS IT NOT) ? Some further definitions CAS in Data Stewardship UNIL 2024-2025 Policy on Open Research Data The SNSF values research data sharing as a fundamental contribution to the impact, transparency and reproducibility of scientific research. In addition to being carefully curated and stored, the SNSF believes research data should be shared as openly as possible … Funding regulations Article 47: Publication and accessibility of research results Grantees are obliged to make available to the public in an appropriate manner the research results obtained with the help of SNSF funding … … the data collected with the aid of an SNSF grant must also be made available to other researchers for further research and integrated into recognised scientific data pools; (provided no restrictions for confidential reasons …) 16 I have to do it - research funders HE Programme Guide (2024) Mandatory open science practices (p.41) “Some open science practices are mandatory for all beneficiaries per the grant agreement. They concern: •open access to scientific publications under the conditions required by the grant agreement; •responsible management of research data in line with the FAIR principles of ‘Findability’, ‘Accessibility’, ‘Interoperability’ and ‘Reusability’, notably through the generalised use of data management plans, and open access to research data under the principle ‘as open as possible, as closed as necessary’, under the conditions required by the grant agreement”; Horizon Europe (HORIZON) 17 I have to do it - research funders UNIL: Directive 4.5 de la Direction - handling and management of research data: •in order to publish and/or share data, data should be organised and managed following international standards (e.g., FAIR principles) (art. 13) •data should be archived after the end of the project in a non-commercial repository (art. 15) 18 I have to do it - institution PLOS ONE – Data availability policy “PLOS journals require authors to make all data necessary to replicate their study’s findings publicly available without restriction at the time of publication. When specific legal or ethical restrictions prohibit public sharing of a data set, authors must indicate how others may obtain access to the data.” Springer Nature – Data policy FAQs “We strongly encourage that all research data are made available to readers without undue restrictions. For some types of data, submission to a community-endorsed, public repository is mandatory.” Publisher Data Availability Policies index 19 I have to do it - editors “Funders of Research will support open research data by appropriately acknowledging and supporting its costs, and by supporting the wider agenda with appropriate policy and investment activities.” (Concordat on Open Research Data 2016, Principle #1) SNSF: General implementation regulations for the Funding Regulations § 2.13: Costs for granting access to research data (Open Research Data): “The research data is deposited in recognised scientific, digital data archives (data repositories) that meet the FAIR principles and do not serve any commercial purpose. ” “preparation of research data in view of its archiving, and to the archiving itself in data repositories … … The maximum charge per grant is generally CHF 10,000.” HES-SO (in 2020): Call for Open Data projects: funding for preparing and depositing data in a FAIR repository (20’000.- max). Institution UNIL: archiving costs covered (Directive 4.5 de la Direction art.16) 20 I am incentivized to do it – financial support Cost calculator for data management (Research Data Management Team, EPFL; Masson 2019) Estimate costs for data publishing 21 I am incentivized to do it - tools “Employers of Researchers will foster a research environment which recognises the value of open data and will seek to provide appropriate access to infrastructure systems and services to enable their researchers to make research data open and usable, having due regard to value for money. They will also recognise good data management as an important aspect of researchers’ duties”. (Concordat on Open Research Data (2016), Principle #1) Infrastructure (institutional repository) Recommendations, guidelines, information Services (training, coaching, …) … 22 I am incentivized to do it – institutional support Good practices Data and work: centralized, managed and stored safely (repository) Quality increase for one’s own possible future reuse Visibility •Data visible, citable, reusable •Publications more cited (Piwowar et al. 2007; Colavizza et al. 2020) •Academic profile: •Data Champions (EPFL, TU Delft) •DataShare Awards (University of Edinburgh) I can benefit from it 23 Ward, The Edinburgh DataShare Awards! (2017). Scientific recognition Community practices (Bongi et al. 2022) Academic recognition •San Francisco Declaration on Research Assessment: «recognizing additional products, such as datasets, as important research outputs …” (DORA (2012)) •Agreement on reforming research assessment (COARA Principles): «Consider also the full range of research outputs, such as scientific publications, data, software, models, methods, …” [for the assessment of research] (COARA principles (2022), p.4) I can benefit from it 24 I would like to do it Personal beliefs and values: OS and reproducible science Reproducibility ECOSYSTEM SNSF Data Management Plan –content of the mySNF form … as soon as possible, but at the latest at the time of publication of the respective scientific output. Horizon Europe (HORIZON) – HE Programme Guide (2024) … as soon as possible after data production and at the latest by the end of the project. Embargo Horizon Europe -DMP template If an embargo is applied to give time to publish or seek protection of the intellectual property (e.g. patents), specify why and how long this will apply, bearing in mind that research data should be made available as soon as possible. Commercial agreement (partners, sponsors) Fixed and reasonable duration AS SOON AS POSSIBLE 33 DMP -Data sharing section How and where, limitations, license, PIDs, metadata, repository Twenty Questions for Research Data Management (Shotton) Data publication 15: For how long will you embargo your research data before it is published for others to see and use? 16: Why is public access to your research data to be restricted (if indeed it is)? 17: Under what data-sharing license will you publish your research data? 18: What persistent identifiers will be used to permit correct citation of your datasets? 19: What metadata will be published with the data to make them interpretable and reusable? SNSF Data Management Plan –content of the mySNF form How and where will the data be shared? Are there any necessary limitations to protect sensitive data? Horizon Europe -DMP template and practical guide 5. Data sharing and long-term preservation a. How and when will data be shared? Are there possible restrictions to data sharing or embargo reasons? b. How will data for preservation be selected, and where will data be preserved long-term (for ex. a data repository or archive)? PLAN EARLY 34 DMP -other sections Types of data, formats, volumes -documentation and metadata ethics, legal and security issues, copyright and IP issues Twenty Questions for Research Data Management (Shotton): The nature of your data Data descriptions (metadata) SNSF Data Management Plan –content of the mySNF form Data collection and documentation Ethics, legal and security issues Horizon Europe -DMP template and practical guide Data description - Documentation and data quality Legal and ethical requirements, codes of conduct PLAN EARLY 35 Good practices: Organise, name, use suitable formats, document, … Personal data: conditions for sharing; impact at several steps (info, consent form, protocols, protection…) A CONTINUUM… 36 Data openness level Research progression Data Curation Continuum Treloar et Klump (2019) Store, share and manage all research (Figshare, OSF, Dataverse) Horizon Europe -DMP template How long will the data remain available and findable? Deletion of data (retracted article, privacy restriction, legal obligations, consent withdrawn or other protective measures) metadata still available –FAIR principles Preservation SNSF recommendation (UNIL): store research data for 10 years at minimum SNSF DMP –content of the mySNF form Please outline a long-term preservation plan for the datasets beyond the lifetime of the project. In particular, comment on the choice of file formats and the use of community standards. Reliability and long-term sustainability of infrastructures For how long 37 38 WHERE TO SHARE DATA? Various options, but mainly in data repositories … CAS in Data Stewardship UNIL 2024-2025 Web sites and cloud Long-term sustainability and right issues Editors Article and data underlying the article Data papers in data/mixed journals «Open Data» repositories OPTIONS 39 In most cases, research data can be made accessible via data repositories … (Concordat on Open Research Data 2016, Principle #7) SNSF -Policy on Open Research Data The SNSF therefore expects all its funded researchers: •to deposit their data and metadata onto existing public repositories in formats that anyone can find, access and reuse without restriction. Horizon Europe (HORIZON) – HE Programme Guide (2024) Data should be deposited in a trusted repository as soon as possible after data production and at the latest by the end of the project. DMP template (2021) Making data accessible Repository: will the data be deposited in a trusted repository ? DATA REPOSITORIES 40 •Technical infrastructure •Stores data, ensures data integrity and makes them accessible in the long-term •With appropriate services •Allows for deposit •Manages content and metadata •Offers a minimum set of basic services (put, get, search, access control) •Is sustainable and trusted, well-supported and well-managed (Heery and Anderson 2005) Data repository - definition, mission, basic functions 41 42 OAIS Reference Model (ISO 14721) (2002) CoreTrustSeal (2017): certification TRUST principles (Lin et al. 2020) Transparency Responsibility User focus Sustainability Technology Functionalities and services useful for sharing data •Reliable and long-term maintenance •Principles on data: F, A, available, citable •Metadata and documentation •Support staff Data repository – norms, certifications, principles 49 “Whenever possible, data should be deposited in subject-specific repositories. These are geared to the needs of the subject area, are familiar with specific data formats and often also offer subject-specific metadata.” Universität Bern “Data should be submitted to discipline-specific, community-recognised repositories where possible.” Springer Nature Data repositories – disciplinary, specialised 50 “A university-based institutional repository [is a] set of services that a university offers to the members of its community for the management and dissemination of digital materials created by the institution and the members.” Clifford A. Lynch, “Institutional Repositories: Essential Infrastructure for Scholarship in the Digital Age,” ARL Bimonthly Report226 (February 2003), 1-7. In cases where a suitable discipline-specific resource does not exist, data may be submitted to a generalist data repository, including any generalist data repositories provided by universities, funders or institutions for their affiliated researchers”. Springer Nature Data Management Plan –content of the mySNF form: If there are no repositories complying with these requirements in your research field, please deposit a copy of your data on a generic platform. Data repositories – institutional, general 51 Pros Cons Disciplinary, specialised • Deep knowledge of the discipline (needs and practices) • Specialised expertise (data curators) (formats, metadata, sensitive data, …) • Co-location with similar data More work needed to prepare data, metadata and documentation (to make them compliant with the standards) Institutional •Good knowledge of local research context • Possible adaptation to needs and practices of researchers of the institution •Seamless transfer with storage of active RD •Links with other research products •Institutional support staff No colocation with similar data from another institution Low visibility outside institution for a specific research domain Data repositories – pros and cons OLOS (generalist) SWISSUbase (discipline-specific & multi-disciplinary) DaSCH Service Platform (humanities) National nodes of ERICs (European Research Infrastructure Consortia): CESSDA-CH: social sciences (FORS) DARIAH-CH: arts and humanities (consortium) CLARIN-CH: language (consortium) ELIXIR-CH: life sciences (SIB) 52 Data repositories – Swiss national NSIDC: National Snow and Ice Data Center Pangea: Earth and Environmental Science WDCC: Earth System model data and products (climate research) GEOSS: Earth Observation data PDB: Protein Data Bank HEP: High-Energy Physics And for other ones: Open Research Europe guidelines 53 Data repositories – community Gorin et al. (2024) See also Milzow et al. (2020) Adapted from Guirlet (2020, Table 24) ORD: a first look at sharing practices 54 What exists What is required ? 55 Select the right repository -criteria 56 Minimum criteria (compliance with FAIR Data Principles): checklist •Are datasets (or ideally single files in a dataset) given globally unique and persistent identifiers (e.g. DOI)? •Does the repository allow the upload of intrinsic (e.g. author's name, content of dataset, associated publication, etc.) and submitter-defined (e.g. definition of variable names, etc.) metadata? •Is it clear under which licence (e.g. CC0, CC BY, etc.) the data will be available, or can the user upload/choose a licence? •Are the citation information and metadata always (even in the case of datasets with restricted access) publicly accessible? •Does the repository provide a submission form requesting intrinsic metadata in a specific format (to ensure machine readability/interoperability)? •Does the repository have a long-term preservation plan for the archived data? Criteria (trustworthy repositories): Science Europe practical guide (p.26) FAIRsharing Community Criteria: Data Repository Selection: Criteria That Matter (Sansone & al. 2020) Source: DIAZ, Pablo (Unil), PETITPREZ, Séverine (CER-VD), PETREMAND, Jannick (CER-VD), 2024. Course Research Data Ethics [Lausanne]. CAS Data Stewardship UNIL. 01 November 2024. Select the right repository -criteria Select the right repository –examples and lists from funders 58 Examples : short description of Dryad, EUDAT, Harvard Dataverse, Zenodo Which data repositories can be used? (by category) Open Research Europe-approved repositories (discipline, data-type) European Research Council: repositories and metadata standards for 3 disciplines 65 Step-by-Step Guide on Data Publication for ETH Zurich Researchers, ETH Library (2021) Metadata 66 Documentation Guide to writing «readme» style metadata and template, Cornell University Data Services README file (.txt) DMP Others … •Guidelines Deposit and preservation of research data in Canada (Austin 2015) •Checklists How FAIR are your data ? (Jones & Grootveld 2017) FAIR data self-assessment tool (Australian Research Data Commons) GUIDELINES AND CHECKLISTS 67 •AUSTIN, Claire C. Guidelines for the deposit of research data in Canada. Retrieved from: https://www.researchgate.net/publication/280303499_Guidelines_for_the_deposit_of_research_data_in_Canada •BONGI, Gaia & al. (2022). ORD capability of scientific communities. Mandate commissioned by swissuniversities. Retrieved from: https://www.swissuniversities.ch/fileadmin/swissuniversities/Dokumente/Hochschulpolitik/ORD/ORD_Mandate2_FinalRep ort_Master_VF_EN.pdf •COLAVIZZA Giovanni & al. (2020). The citation advantage of linking publications to research data, Retrieved from: https://europepmc.org/article/PMC/7176083 •GORIN, Simon & al. (2024). ). Open research data: a first look at sharing practices. Retrieved from: https://data.snf.ch/stories/open-research-data-2023-en.html •GUIRLET, Marielle (2020) Guide décisionnel et vade-mecum pour la mise à disposition d'un dépôt de données de recherche ouvertes en Suisse. Mémoire de fin d’études du Master of Science HES-SO en Sciences de l’information à la HEG de Genève, Haute Ecole de la HES-SO. Retrived from: https://zenodo.org/records/4357134 •HEERY, Rachel & ANDERSON, Sheila (2005). Digital repositories review. Retrieved from: https://www.ukoln.ac.uk/repositories/publications/review-200502/digital-repositories-review-2005.pdf •JONES, Sarah & GROOTVELD, Marjan (2017). How FAIR are your data ? Retrieved from: https://zenodo.org/records/5111307 •MASSON, Antoine (2019). Cost Calculator : a Tool for your DMP. Retrieved from: https://zenodo.org/record/3250155#.Xxk8h-fgpPY •MILZOW, Katrin & al. (2020). Open Research Data - SNSF monitoring report 2017-2018. Retrieved from: https://zenodo.org/records/3618123 REFERENCES & SOURCES 68 •PIWOWAR, Heather A., DAY, Roger S. & FRIDSMA, Douglas B. et al. (2007). Sharing Detailed Research Data Is Associated with Increased Citation Rate. Retrieved from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0000308 •RICE, Robin and SOUTHALL (2016). The data librarian’s handbook. Facet Publishing. •RILEY, Jenn et NATIONAL INFORMATION STANDARDS ORGANIZATION (U.S.), 2017. Understanding metadata: what is metadata, and what is it for? ISBN 978-1-937522-72-8. Retrieved from : http://www.niso.org/publications/understanding-metadata-riley •SHOTTON, David (2012). Twenty Questions for Research Data Management [en ligne]. 07.03.2012. Mis à jour les 22.03.2012, 11.06.2012, 09.05.2013. [Consulté le 22.07.2020]. Disponible à l’adresse : https://datamanagementplanning.wordpress.com/2012/03/07/twenty-questions-for-research-data-management/#comment1178 •TENOPIR, Carol & al. (2020), Data sharing, management, use and reuse: Practices and perceptions of scientists worldwide. Retrieved from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0229003 •TRELOAR, Andrew & KLUMP (2019). Updating the Data Curation Continuum: Not Just Data, Still Focussed on Curation, More Domain-Oriented •VON DER HEYDE, M. (2019). Open Research Data: Landscape and cost analysis of data repositories currently used by the Swiss research community, and requirements for the future [Report to the SNSF]. Retrieved from https://doi.org/10.5281/zenodo.2643460 REFERENCES & SOURCES 69