Top 10 FAIR Data & Software Things

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

The Top 10 FAIR Data & Software Global Sprint was held online over the course of two-days (29-30 November 2018), where participants from around the world were invited to develop brief guides (stand alone, self paced training materials), called "Things", that can be used by the research community to understand FAIR in different contexts but also as starting points for conversations around FAIR. The idea for "Top 10 Data Things" stems from initial work done at the Australian Research Data Commons or ARDC (formerly known as the Australian National Data Service).

The Global Sprint was 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, Center for Digital Scholarship at the Leiden University, and DANS. Anyone could join the Sprint and roughly 25 groups/individuals participated from The Netherlands, Germany, Australia, United States, Hungary, Norway, Italy, and Belgium. See the full list of registered Sprinters.

Sprinters worked off of a primer that was provided in advance together with an online ARDC webinar introducing FAIR and the Sprint titled, "Ready, Set, Go! Join the Top 10 FAIR Data Things Global Sprint." Groups/individuals developed their Things in Google docs which could be accessed and edited by all participants. The Sprinters also used a Zoom channel provided by ARDC, for online calls and coordination, and a Gitter channel, provided by Library Carpentry, to chat with each other throughout the two-days. In addition, participants used the Twitter hashtag #Top10FAIR to communicate with the broader community, sometimes including images of the day.

Participants greeted each other throughout the Sprint and created an overall welcoming environment. As the Sprint shifted to different timezones, it was a chance for participants to catch up. The Zoom and Gitter channels were a way for many to connect over FAIR but also discuss other topics. A number of participants did not know what to expect from a Library Carpentry/Carpentries-like event but found a welcoming environment where everyone could participate.

Authoring Person(s) Name: 
Tim Dennis
Jael Garcia
Mateusz Kuzak
Paula Andrea Matinez
Liz Stokes
Tom Honeyman
Sharyn Wise
Joshua Quan
Scott Peterson
Amy Neeser
Elena Karvosvskaya
Otto Lange
Fiona Bradley
Kristina Hettne
Peter Verhaar
Ben Companjen
Laurents Sesink
Fieke Schoots
Erik Shultes
Rajaram Kaliyaperumal
Erzsébet Tóth-Czifra
Ricardo De Miranda Azevedo
Sanne Muurling
John Brown
Janice Chan
Niamh Quigley
Lisa Federer
Douglas Joubert
Allissa Dillman
Kenneth Wilkins
Ishwar Chandramouliswaran
Vivek Navale
Silvia Di Giorgio
Akinyemi Mandela Fasemore
Konrad U. Forstner
Till Sauerwein
Eva Seidlmayer
Dr. Ilja Zeitlin
Katie Hannan
Richard Ferrers
Keith Russell
Deidre Whitmore
Authoring Organization(s) Name: 
Library Carpentry
License - link to legal statement specifying the copyright status of the learning resource: 
Creative Commons Attribution 4.0 International - CC BY 4.0
Access Cost: 
No fee
Primary language(s) in which the learning resource was originally published or made available: 
More info about
Keywords - short phrases describing what the learning resource is about: 
Accessible data - FAIR Data Principle
Cyberinfrastructure to enable FAIR data principles
Findable data - FAIR Data Principle
Interoperable data - FAIR Data Principle
Re-usable data - FAIR Data Principle
Published / Broadcast: 
Friday, February 1, 2019
Publisher - organization credited with publishing or broadcasting the learning resource: 
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Collection - a group or set of items that comprise a single learning resource, e.g., a PDF version of a slide presentation, an audio file of the presentation and a textual representation of the oral transcription of the presentation.
Contributor Name: 
Carlos Martinez-Ortiz
Anna-Lena Lamprecht
Bia Villas Boas
Guilherme Castelao
Ryan Johnson
Stephanie Labou
Reid Otsuji
Natasha Simons
Christopher Erdmann
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Instruction - detailed information about aspects or processes related to data management or data skills.
Target Audience - intended audience for which the learning resource was created: 
Data manager
Data policymaker
Data professional
Data supporter
Repository manager
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
More than 1 hour (but less than 1 day)