Open Research Data in H2020 Webinar Summary
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Open Research Data in Horizon 2020 Emilie Hermans, UGent webinar, May 9 2018
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Open Research Data in H2020 Webinar Summary
- 1. @openaire_eu OpenAIRE webinar: Open Research Data in H2020 Webinar May9th,2018 HermansEmilie GhentUniversity OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018
- 3. Adapted original source: The University of California, Santa Cruz, Data Management LibGuide, Research Data Management Lifecycle, diagram, viewed 5th May 2018 http://guides.library.ucsc.edu/datamanagement Challenge: Adapted original source: The University of California, Santa Cruz, Data Management LibGuide, Research Data Management Lifecycle, diagram, viewed 5th May 2018 http://guides.library.ucsc.edu/datamanagement From liniar process to research data lifecycle!
- 4. OpenAIREwebinar:OpenResearchDatainH2020 –09/05/2018 Whatisdatamanagement? EXPLAIN IT STORE IT SAFELY OPEN IT • CONTEXTUALIZE YOUR MATERIAL • DESCRIBE YOUR RESEARCH PROCESS • PROVIDE INFORMATION ABOUT DATASETS • MAKE COPIES • CONTROL ACCESS TO FILES • DECIDE WHAT DATA TO KEEP AND WHAT TO DELETE • GAIN MORE IMPACT • USE DATA REPOSITORIES • INCREASE TRANSPARENCY
- 5. Free to access reuse, repurpose, and redistribute Restricted access to limited amount of people under certain conditions Open Data Data sharing Whatisopendata?
- 6. 1. e.g. Piwowar HA, Vision TJ. (2013) Data reuse and the open data citation advantage. PeerJ 1:e175 https://doi.org/10.7717/peerj.175, Piwowar HA, Day RS, Fridsma DB (2007) Sharing Detailed Research Data Is Associated with Increased Citation Rate. PLoS ONE 2(3): e308. doi:10.1371/journal.pone.0000308 Prevents data loss Maximize usefulness Write a data paper Credit & longer shelf life 1 Increases transparency Promote integrity Citizens science DATAMANAGEMENT AND OPENDATA
- 7. OpenAIREwebinar:OpenResearchDatainH2020 –09/05/2018 EC:TheOpenResearchDataPilot Flexible ORD pilot: From limited to default in 2017 • Avoid duplication of research and loss of resources • Foster Open Science Open Access to research data (or partially opt-out) Data Management Planning
- 8. OpenAIREwebinar:OpenResearchDatainH2020 –09/05/2018 Whichareasareparticipating? • DMP/Dataset Costs eligible (Article 6.2.D.3 of the Model Grant Agreement) Projects started in 2014-2016 Limited ORD Pilot From 2017 Extended ORD Pilot • Limited ORD pilot: some areas: Check Article 29.3 • Participating is default option for all projects • Possibility to opt-out• Possibility to opt-in or opt-out • 1 DMP/Project
- 9. (PARTIALLY) OPTING-OUT OpenAIREwebinar:OpenResearchDatainH2020 –09/05/2018 Reasons e.g. • Exploitation of results • Confidentiality • Protection of personal data • Would jeopardize the main aim of the action • No data generated • Any other legitimate reason As open as possible as closed as necessary Projects can opt out at any stage: • Complete opt-out via project amendment • Complete or partially opt-out: describe issues in project DMP
- 10. FAIR Data Management guidelines 10 http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf • Notes the extension of the pilot • Clarifies concept of FAIR data • Explains what a DMP is and when they should be updated • Notes what happens at proposal, submission and evaluation stage • Explains costs are eligible • Provides a DMP template
- 11. 11 RequirementsoftheDataPilot 1. Data Management Plan (DMP) 2. Deposit data in data repository 4. Open up data3. Provide information to validate results
- 12. PROPOSALSTAGE 12 Applications should address: 1. Standards e.g. file formats, metadata scheme’s, licenses….. 2. How to make data available. If not, why? 3. How will data be curated and preserved 4. Current state of agreements on data management Plan your budget! 5. Be consistent with IPR requirements ≠ DMP Note: not required to submit DMP at proposal stage. A DMP is therefore a deliverable, and NOT part of the evaluation.
- 13. basic idea ≠ DMP Timeline 1st version DMP Changes in data, policy, consortium Update DMP Final version UPDATE PERIODIC EVALUATION 6 MONTHSPROPOSAL FINAL REVIEW
- 14. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 WhatisaDMP? Living document: update Reflects on curation, preservation, sustainability and security What parts will be open and how? Handling of data during and after project
- 15. 15 OpenAIREwebinar:OpenResearchDatainH2020 –09/05/2018 ContentofH2020DMP Data summary FAIR Data principles Resources Data security Ethical aspects Template: EC guidelines on FAIR Data Management http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf
- 16. 16 • How to discover your data? • How to understand your data? • Where to find your data? • Can people access your data? • Metadata • Persistent identifier • Naming convention • Keywords • Versioning • Software, documentation • Data repository • Standards • Vocabulary • Methodologies • Licensing Findable ReusableInteroperable Accessible
- 17. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 17 HowtowriteaDMP online tool dmponline.dcc.ac.uk
- 18. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 18 Createandconfirmplan
- 19. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 19 PlanDetails
- 20. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 20 Versions Share with partners
- 21. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 21 Guidance Guidance based on guidelines EC Guidance and links from DCC
- 22. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Export to various formats
- 23. recommendations
- 24. Research can define what is appropriate Don’t have to share data if inappropriate – exemptions apply What datasets to mention? Data and metadata needed to validate the results presented in scientific publications. Other (as specified in DMP: raw/curated data) WhichdatadoestheORDpilotapplyto? Does not apply to ALL data OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018
- 25. • Types e.g. digital/non-digital data, qualitative/quantitative, audio files, surveys, databases, field notes….. Data summary • Re-use? Provide the source and check IPR DataCollection • Does similar data exists? What about reintegration or reuse? Origin: generated, collected, reused
- 26. Datafilesformats Use data formats that are: • Are not proprietary, open standard possible? • In an easily re-usable format • Commonly used by research community Examples of preferred format choices: Text .odt, .txt, .xml, .html, .rtf Tabular Data .csv (comma separated values), .xml, .rdf, .SPSS portable Images .tif, .jpeg2000, .png, .svg, Structured data .xml, .rdf Any standard used in your field Data summary Use consequent naming convention Structured organizing of files OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018
- 27. For personal data of EU citizens (compliance by May 25, 2018) • EU General Data Protection Regulation (GDPR): Broad interpretation of personal data: e.g. name, IP address, cookies ONLY collect what is absolutely necessary and only use for the purpose indented. Consent Right to be forgotten Right to data correction Notification if data is at risk Privacy by default: any divergence on original agreement asks for an additional agreement Ethical aspects Ethical aspects
- 28. Considerethicalissuesearly: • Consent form: sharing, preservation and re-use • Anonymization • Privacy Ethical aspects Ethical aspects Include in Ethic deliverables/Ethics chapter of Description of the Action
- 29. Filesharingandstorage • Back-up procedures • Befriend your ICT department Data security • Strategy for file sharing: servers, synchronization, secure storage, encrypting, …. - What is needed? - Who can access? especially important if you deal with: • Large data files: storage capacity or • Personal data: protection (passwords, encryption,…) OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018
- 30. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Documenting data • Make your data understandable: project level (context) and data level (e.g. codebooks, protocol) • E.g. lab notebook, end-to-end code/scripts for statistics • Software can help: R, MatLab, Python… • Be clear what methods you use Accessible • Decide on a clear and consisting naming- system • Who has access and editing privilege? • Version tracking software/ file sharing services can help • Version control
- 31. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Createsearchabledata:METADATA Findable CC-BY ERESEARCHSA www.ersa.edu.au/wp-content/uploads/2014/06/understanding-metadata.jpg
- 32. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Createsearchabledata:METADATA • Data about data • Machine readable making data findable Using metadata • Consists of set of attributes • Helps prevent inappropriate use • Use metadata standards of your domain CC-BY ERESEARCHSA www.ersa.edu.au/wp-content/uploads/2014/06/understanding-metadata.jpg
- 34. Use standards of your domain Digital Curation Centre General • Dublin Core (DC) • Datacite metadata schema • Metadata Object Description Schema (MODS) Humanities • Text Encoding Initiative (TEI) • Visual Resources Association Core (VRA) Archives/Repositories • DatastaR minimD-space metadata • um Metadata Social Science • Data Documentation Initiative (DDI) Life Sciences • Darwin Core • Integrated Taxonomic information System (ITIS) Earth Science • Directory Interchange Format (DIF) • Standard for the Exchange of Earthquake Data (SEED) Ecology • Ecological Metadata Language (EML) Geographic/Geospatial • Federal Geographic Data Committee (FGDC) • ISO 19115 • Geospatial Interoperability Framework (GIF) METADATA STANDARDS
- 35. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Where to store data?
- 36. What about our project page? 36 Sustainable? Services? Legal aspects? Technical standards? Metadata standards? Findable?
- 37. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Where to deposit data? • Disciplinary/Institutional data repository Research data repository • Zenodo cost-free data repository • Matches data needs • Directory of data repositories: www.Re3data.org Accessible
- 38. Re3data.org
- 39. @openaire_euOpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Re3data.org Trustworthy Digital repository • Persistent identifier • Licenses • Access
- 40. OpenAIREwebinar:OpenResearchDatainH2020 –09/05/2018 Whattodeposit? Everything needed to validate results presented in scientific publications DATA • Validate results • Selection METADATA DOCUMENTATION • Tools, software…. • Read_me file? OPEN DATA?
- 41. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Opendata • Apply an open license: • Keep it simple: “as open as possible, as closed as necessary” • e.g. creative commons. Recommended: • Data repositories can provide licenses • Re3data.org Reusable • License for widest reuse possible
- 42. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Example Understandable for humans Machine readable metadata Tools Open Data Open license
- 43. Zenodo.org describe publish 43 For all content types With GitHub Integration Create communities upload describe publish
- 45. (Open) Data Metadata Other tools Open Research Data Pilot Data Repositories • EC guidelines • OpenAIRE.eu • dcc.ac.uk • Standard File Formats • Standards metadata schema • (Open) Licences • 6 months • Periodic evaluation • Final review STEP 1 WRITE A DMP dmponline.dcc.ac.uk Update at FIND REPOSITORY DEPOSIT DATA Supporting infrastructure and information STEP 2 STEP 3 SUPPORT • discipline/institutional • www.re3data.org • Zenodo Matches data needs Designed by Freepik
- 46. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 Support and information? 4646 OpenAIRE- An Open Knowledge & Research Information Infrastructure • www.OpenAIRE.eu offers infrastructure, tools, information and helpdesk system on Open Science. OPENAIRE FOSTERS THE SOCIAL AND TECHNICAL LINKS THAT ENABLE OPEN SCIENCE IN EUROPE AND BEYOND.
- 47. OpenAIREwebinar:OpenResearchDatainH2020 –09/05/2018 OpenAIRE 4747 Training and support material Information on: • Open research data pilot • Creating a data management plan • Selecting a data repository • Dealing with personal data Support material: Briefing papers, factsheets, webinars, workshops , FAQs, helpdesk www.openaire.eu/opendatapilot
- 48. OpenAIRE webinar: Open Research Data in H2020 – 09/05/2018 OpenAIRE 4848 www.openaire.eu/search Link your data to publications or project
- 49. How can we help? • Guides • Factsheets • Workshops • Webinars • Helpdesk • FAQ
- 50. Regionalexperts Ask a question • The National Open Access Desks (NOADs): • Support on a national level • Country pages with local information on Open Science OpenAIREWebinarOAtopublicationsinH2020–08/05/2018
Notas do Editor
- Idea- experiment – data analyse and writing paper – finally time for some pizza while paper gets reviewed – paper: jeej, al your hard work dissapears
- FROM DATA IN A SCIENTIFIC PIPELINE TO RESEARCH DATA LIFECYCLE
- Research data management concerns the organisation of data, from its entry to the research cycle through to the dissemination and archiving of valuable results. Research Data Management is part of the research process, and aims to make the research process as efficient as possible
- Open data is data that is free to access, reuse, repurpose, and redistribute. The Open Research Data Pilot aims to make the research data generated by selected Horizon 2020 projects accessible with as few restrictions as possible, while at the same time protecting sensitive data from inappropriate access Data sharing restricted data to restricted organisations or individuals. Access to this data is usually restricted because it is sensitive in some way, either because it is personal or because its general release might cause security problems.
- Prevents data loss: 80% of data is lost after 10 years. Data is fragile and reproducibility very difficult without data. 2, Maximize usefulness and built much more efficient on previous work: Maximize usefulness: organize, make understandable, reusable and avoid duplication. Preserves data for further research by organizing, Stop drowning in irrelevant stuff. Reproducibility crisis. 3. Fosters creativity, interdisciplinary use of data and meta-analysis 4, public participation in scientific research 5. Promote integrity and increases transparency: managing data is part of good research, avoid accusations of sloppy science 4. Data tend to have a (much!) longer shelf life than interpretation After accounting for other factors affecting citation rate, we find a robust citation benefit from open data.1
- Horizon 2020 Includes a flexible pilot with opt-outs and safeguards action on open access to research data. There are two main pillars: Participating projects must develop a Data Management Plan(DMP) specifying which data will be openly accessible.
- If your project stems from one of these Horizon 2020 areas, you are automatically part of the pilot. Costs related to data management in Horizon 2020 are eligible for reimbursement during the duration of the project (see Article 6.2.D.3 of the Annotated Model Grant Agreement)
- IPR protection, no data generated and privacy are the most cited reasons.
- 3, provide information via chosen repository about tools and instruments necessary for validating the results 4, take measures to enable third parties to access, mine, exploide, reproduce and disseminate, free of charge for any user, this research data.
- A data management plan or DMP is a formal document that outlines how you will handle your data both during your research, and after the project is completed.[1] The goal of a data management plan is to consider the many aspects of data management, metadata generation, data preservation, and analysis before the project begins; this ensures that data are well-managed in the present, and prepared for preservation in the future. The DMP needs to be updated over the course of the project whenever significant changes arise, such as(but not limited to) - new data - changes in consortium policies (e.g. new innovation potential, decision to file for a patent) changes in consortium composition and external factors(e.g. new consortium members joining or old members leaving) DMP is a deliverable, and NOT part of the evaluation.
- 5 main topic Costs eligible and resposibilities
- Interoperability: how can my data be combined with other datasets and used in other fields? Licensing: who can access my data and for what perpuse can it be used
- - No reimbursement: Articles published before the initiative was launched are not eligible and don’t pay for it yourselves
- IPR: Identify source and ownership of third party data Establish conditions of use, copyright constraints and redistribution rights Statement on intellectual property rights of generated data
- IPR: Identify source and ownership of third party data Establish conditions of use, copyright constraints and redistribution rights Statement on intellectual property rights of generated data
- Try to make the barriers to view your data as low as possible. Use open file formats. Avoid word, pdf and excel files. You can use pdf/a for archiving/if the layout matters. Outline and justify your file format choices
- - Consent not prohibiting data sharing. Gain consent for sharing, preservation and re-use of research data Intellectual property rights Identify source and ownership of third party data - Plan and anonymise data early in research Create anonymisation log of edits, replacements, removals or aggregations made
- - Consent not prohibiting data sharing. Gain consent for sharing, preservation and re-use of research data Intellectual property rights Identify source and ownership of third party data - Plan and anonymise data early in research Create anonymisation log of edits, replacements, removals or aggregations made EU General Data Protection Regulation
- Will the data be stored and backed-up appropriately during the research project? For example on managed university filestores rather than external hard drives Know your institutional IT security arrangements and capacity for data storage Know your institutional procedure and regularity of data back-up, especially for remote and cross-institutional working Arrange backup and storage procedures which are most suited to the partners and nature of your project
- Collecting: how will data be collected? What will you do with the data? E.g. survey: will it include a disclaimer what will happen with the data? Provide links to data sets you used or if you’re allowed, lincenses and copyright, you can also upload the original data set. Provide end-to-end code/scripts for the generation of figures and statistics Keep in mind: will someone who is not familiar with the data or the research setup understand what the data is about
- metadata assures accessibility of the data, Metadata is the backbone of digital curation. Data about data to discover and disclose data: resource descriptions A metadata record consists of a set of attributes or elements, necessary to describe the data in question Structured information that describes, explains, locates or otherwise makes it easier to retrieve, use or manage an information source basically data is read by humans, metadata is read by PCs Helps prevent inappropriate use due to misunderstanding or research purpose or parameters
- metadata assures accessibility of the data, Metadata is the backbone of digital curation. Data about data to discover and disclose data: resource descriptions A metadata record consists of a set of attributes or elements, necessary to describe the data in question Structured information that describes, explains, locates or otherwise makes it easier to retrieve, use or manage an information source basically data is read by humans, metadata is read by PCs Helps prevent inappropriate use due to misunderstanding or research purpose or parameters
- Metadata standards often start as schemas developed by a particular user community to enable the best possible description of a resource type for their needs. Standards-based metadata is generally preferable, but where no appropriate standard exists, for internal use, writing “readme” style metadata is an appropriate strategy.
- Trustworthy Digital repository: either supports a repository standard or is certified
- Metadata Other data, including associated metadata, as specified and within the deadlines laid down in the Data Management Plan, that is, according to the individual judgement of each project: For instance curated data not directly attributable to a publication, or raw data. Documentation: Codebooks, lab journals, informed consents forms… required to enable reuse of the data. Will people not involved in the project understand what the data is about, how it has been processed. Read me file: in a plain text format about your data: Keep in mind: will someone who is not familiar with the data or the research setup understand what the data is about
- keep it simple: There is no requirement that every dataset must be made open right now. Keep it feasible: privacy, valorization, ownership. Starting out by opening up just one dataset, or even one part of a large dataset, is fine – of course, the more datasets you can open up the better. Open licenses: legaly sound licensing CC0: public domain, waive copyright CC-BY: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. No additional restrictions
- NUP84 proteins. MRC is a standard file format for electron density The txt explains the parameters used
- Catch all repository for all kinds of research output: data publications, presentations;, software…. For free, up to 50GB per dataset limit
- equipped with a helpdesk system. specific questions: by the subject or by your function. Questions are answered by a team of specialist, not any on a technical level but there are people of all countries involved able to answer country specific questions; The NOADs: national open access desks, are representatives of open access for their country and can help you with any country specific questions.