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Ready, Set, Go! Join the Top 10 FAIR Data Things Global Sprint



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Webinar - top 10 fair data global sprint.
Slides from the kickoff webinar. The Global Sprint will be happening 29-30 November 2018

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Ready, Set, Go! Join the Top 10 FAIR Data Things Global Sprint

  1. 1. Ready, Set, Go! Join the Top 10 FAIR Data Things Global Sprint! Webinar - 20 November 2018 Sprint - 29-30 November 2018
  2. 2. Today’s webinar 1. The Top 10 FAIR Data Global Sprint: who, what, why - Natasha Simons, ARDC 2. Brief overview of the FAIR Data Principles - Keith Russell, ARDC 3. The Top 10 FAIR Data Global Sprint: how - Chris Erdmann, Library Carpentry 4. Where do I start? - Liz Stokes, ARDC 5. Questions Link to this slide deck:
  3. 3. Top 10 FAIR Data Global Sprint Who, what and why?
  4. 4. Top 10 FAIR Data Global Sprint 29-30 November 2018 Organised by: Library Carpentry, Australian Research Data Commons and the Research Data Alliance Libraries for Research Data Interest Group In collaboration with FOSTER Open Science, OpenAire, RDA Europe, Data Management Training Clearinghouse, California Digital Library, Dryad, AARNet, DANS, and Centre for Digital Scholarship at Leiden University Library. See:
  5. 5. Global sprint - what and why? What is the purpose of the Sprint? To create a wide range of Top 10 FAIR Data Things by research disciplines and/or themes. What is a Top 10 FAIR Data Things resource? "Things" is a neat concept for creating packaged content on any topic. Each “Thing” is a self-directed learning activity for anybody who wants to know more about FAIR research data. The Top 10 FAIR Data Things resources we create during the Sprint can be used by the research community to understand FAIR in different discipline and theme contexts as well as providing some initial steps to consider.
  6. 6. Example hings/10-medical-and-health-things
  7. 7. Primer (instructions) Use this primer to help prepare and guide you through the creation of your Top 10 FAIR Data resource for a research discipline:
  8. 8. Top 10 FAIR Data Global Sprint What are the FAIR Data Principles?
  9. 9. F.A.I.R. Data Principles • Drafted in a workshop in 2015 and in Nature article • Received international recognition • Making data usable by humans and machines • Technology agnostic • Both the data and the metadata • Discipline independent… Image by Sanja Pundir CC-BY-SA
  10. 10. … but what does it mean in a discipline?
  11. 11. Findable F1. (meta)data are assigned a globally unique and eternally persistent identifier. F2. data are described with rich metadata. F3. (meta)data are registered or indexed in a searchable resource. F4. metadata specify the data identifier. ● What Persistent identifier is used? ● What discovery metadata is common and relevant? ● What discipline specific repositories and registries are there out there?
  12. 12. Accessible A1 (meta)data are retrievable by their identifier using a standardized communications protocol. A1.1 the protocol is open, free, and universally implementable. A1.2 the protocol allows for an authentication and authorization procedure, where necessary. A2 metadata are accessible, even when the data are no longer available. ● How Open is data in the discipline, are there considerations and protocols for sensitive data? ● Are there platforms and solutions to provide access to sensitive data? ● What data services are used to deliver the data?
  13. 13. Interoperable I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (meta)data use vocabularies (and ontologies) that follow FAIR principles. I3. (meta)data include qualified references to other (meta)data. ● Are there standard file formats? ● Are there standard vocabularies and ontologies for data and metadata? Where can they be found? ● Are there identifiers for related information (projects, samples, authors)
  14. 14. Reusable R1. meta(data) have a plurality of accurate and relevant attributes. R1.1. (meta)data are released with a clear and accessible data usage license. R1.2. (meta)data are associated with their provenance. R1.3. (meta)data meet domain-relevant community standards. ● Is there a licence standard? ● Is there a discipline specific approach around provenance? ● Are there community standards for the data and metadata?
  15. 15. Discipline context ● Are there relevant policies from funders, journals, associations, societies, etc. in the discipline? ● Are there standard approaches, templates for Data Management Plans, etc.
  16. 16. Top 10 FAIR Data Global Sprint How will the Sprint work?
  17. 17. Monash Zoom We have check-ins everyone hour, on the top of the hour, where you can discuss what you are working on, ask questions and get feedback, and/or get a summary of what others are working on. Top10FAIR Gitter We have a chat room where you can discuss your work outside of the check-ins above. This can a quicker way to get an answer. Use @ to chat with someone specifically. Registration & Coordination This folder contains all the relevant Sprint material. Register your discipline/theme thing ( DMMtUM6M/edit) and create your collaborative document in the group folder (
  18. 18. Code of Conduct We will be using The Carpentries Code of Conduct. This is a welcoming place. Please be kind and professional. #Top10FAIR Tweets Collaborators and partners are listed along with the hashtag for the event #Top10FAIR. Leiden University now a partner. Check @ands_nectar_rds and @LibCarpentry to see if more partners/collaborators have joined. Make sure you use the hashtag though! Top 10 FAIR Data Things GitHub Repository We will collect and post the Top 10 FAIR Data Things Resources in a Library Carpentry repository under the same name. This will allow for reuse and further contributions from the wider research & library communities.
  19. 19. Top 10 FAIR Data Global Sprint Where to start?
  20. 20. Where to start? Photo by David Marcu on Unsplash
  21. 21. What does FAIR look like for you? Photo by Eric Muhr on UnsplashPhoto by Anthony DELANOIX on Unsplash
  22. 22. What does FAIR look like for you? ● Discipline focussed resources ● Repositories that are really really ridiculously good looking ● Useful metadata standards ● Demystifying identifiers ● Examples of FAIR in practice ● Validate a vocabulary!
  23. 23. Sprint “driver reviver” stations Drop in places at various locations where you can go at any (daylight!) time during the Sprint to: ● Catch up with others doing the Sprint ● Work on a Top 10 FAIR Data resource ● Eat cake! The Australian stations will be listed shortly on the ARDC website: If you want to volunteer a station location, get in touch with us! Contact: or Images: roamthegnome, pumpkin-machine, gify-cat
  24. 24. Disambiguation “Fair Data is a certification launching in Australia in November 2018 by the Australian Market & Social Research Society (AMSRS) to show which companies handle their customer’s personal data fairly.” Just to be clear, is not us. Even though they’ve got 10 things in a list and have registered a domain name.
  25. 25. Join our next webinar on November 27 Make Data Count! Hear from Daniella Lowenberg (California Digital Library) and Patricia Cruse (DataCite) about how you can capture and display data usage metrics in your repository More information and registration at: