Open Science goes FAIR
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Presentation about FAIR data and Open Science given at Åbo Akademi University Faculty meeting 4 Dec 2020
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Open Science goes FAIR
- 1. Open Science goes FAIR - what does it mean? Jessica Parland-von Essen 4.12.2020
- 2. OPEN DATA Open means anyone can freely access, use, modify, and share for any purpose (subject, at most, to requirements that preserve provenance and openness). https://opendefinition.org/od/2.1/en/ 2
- 3. OPEN SCIENCE • Reprodacibility • Data management • Responsible research • Integrity 3
- 4. LINK ROT
- 7. FAIR principles for data – requirements for research data Findable F1. (Meta)data are assigned a globally unique and persistent identifier F2. Data are described with rich metadata (defined by R1 below) F3. Metadata clearly and explicitly include the identifier of the data they describe F4. (Meta)data are registered or indexed in a searchable resource Accessible A1. (Meta)data are retrievable by their identifier using a standardised communications protocol A2. Metadata are accessible, even when the data are no longer available Interoperable I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation I2. (Meta)data use vocabularies that follow FAIR principles I3. (Meta)data include qualified references to other (meta)data Reusable R1. Meta(data) are richly described with a plurality of accurate and relevant attributes
- 8. 8 F A I R FINDABLE • Described in relevant catalog with enough detail • Landing page with globally unique persistent identifier ACCESSIBLE • Can be retrieved over the internet • Versioning and lifecycle are documented • Tombstone page if data is deleted INTEROPERABLE • Common, documented, and open formats RE-USABLE • Well documented and intelligible • Rights clearly stated https://doi.org/10.5281/zenodo.4045402
- 9. Persistent identifiers are unique and unambiguous Catalog Resol ver Datafile Contract Configration Read me PID
- 10. A PID is a PromisePID
- 11. Shallow FAIR and Deep FAIR 11 Necessary research information, PIDs, machine readable license All data elements are machine accessible Research Information Research Data
- 12. ACTIVE DATA Raw, continuously updated DYNAMIC RESEARCH DATA Version controlled, possible to cite RESEARCH DATASET PUBLICATION Immutable Documentation, validation Research Research Data Types https://doi.org/10.23978/inf.77419
- 13. FAIR Ecosystem Components and FAIR Digital Objects 13 http://doi.org/10.5281/zenodo.3565428 https://doi.org/doi:10.2777/1524
- 14. 05/12/202014 • Don’t try to do this alone, contact your data stewardsResearchers • Talk to researchers about reproducibility and semantic artefactsData stewards • Co-develop and co-create, support FAIR and document thoroughly Service providers
- 15. URN USE identifiers! THINK about reproducibility! VISIT research.csc.fi! USE the fairdata.fi services!
- 16. Use research data services and fairdata.fi 16 Fairdata.fi Research.fi
- 17. EOSC and other services 17
- 18. • Requirement from many funders to publish data • GDPR and rights management • Ensure good reproducibility • More citations and visibility • Good documentation supports your own future work Why data management planning 18
- 19. Co-creation & co-development 05/12/202019 Always design a thing by considering it in its next larger context – a chair in a room, a room in a house, a house in an environment, an environment in a city plan. Eliel Saarinen, Finnish architect (1873--1950) LA2 / CC BY-S. Wikimedia (https://creativecommons.org/licenses/by-sa/4.0)
Editor's Notes
- F = Findable, kun aineistolla on pysyvä tunniste esim doi, linkki aineistoon toimii aina vaikka säilytyspaikka muuttuisi A = Accessible, tutkimusaineiston tunniste toimii hyperlinkkinä jonka avulla dataan ja sen kuvailutietoihin pääsee käsiksi verkkoselaimella I = Interoperable yhteentoimivuuden periaate edellyttää avoimia tiedostomuotoja ja yhteisiä standardeja, ei enää tiedostoja jotka eivät aukea R = Re-usable (datan kuvailu tukee tätä), dataa voidaan käyttää kun sillä on metatietoja ja käyttöehdoista kertova lisenssi
- The first use case is the visibility of your work and outputs. When reporting on your work, to funders, and publishing outputs, a basic level of FAIRness and PID use is sufficient to enable findability, simple citation and output registration with core descriptive metadata. This is the context of what is usually called research information (sometimes referred to as current research information). The most common and useful PIDs for this are the research output DOI and the ORCID for the creator(s)/contributor(s). There are also other systems available to identify other kinds of entities to help further linking of information, such as organisations or protocols. Funders and employers might for instance require linking to some other contextual reference data like lists of grants, funders and affiliated organisations. This kind of information is becoming more important, but the actual data quality is depending on the functionalities each service provides. If the services used for dataset publication or reporting don’t require PIDs or don’t offer reference (meta)datasets or integration with PIDs for these kinds of things, it is difficult for the researcher to provide this information in an unambiguous way. The other use case for PIDs is the management of the research data itself. Here the PIDs can have different functions: (a) creating deep FAIR research datasets as research outputs, where all individual data elements are machine accessible, see panel F in Figure 1, or (b) when managing and documenting the actual workflow and data and related information during research to ensure reproducibility of research results.
- The archive or generic repository usually operates with research dataset publications, that are are a sort of publication, albeit complex, but immutable, archived as output and evidence for research. This case is quite easy, pid wise. But in real life there are many steps and varieties of data before this- This should be taken into account when citing, for instance. How can we support sufficient reproduciblity without overflowing all systems with PID – that should be kept and maintained forever!?
- Figure 8 lähde: TFiR https://doi.org/doi:10.2777/1524 Diagram 2 lähde : http://doi.org/10.5281/zenodo.3565428
- Researchers: don’t try to do this alone, contact your data-stewards. Data-stewards: talk to researchers about reproducibility and semantic artefacts. Service providers: co-develop and co-create, support FAIR and document thoroughly.