Learning Outcomes
- Explain the 4 principles in the acronim FAIR
- Differentiate FAIR and OPEN science and application in training material
- Discuss the advantages of FAIR and OPEN training
What is FAIR and why do I car ?
1.1 Presentation
Here you can find the presentation for this session:
The full presentation can be downloaded here.
1.2 What is FAIR
In the Cambrige dictionary the word fair can stand for something that you expected or deserved, but I’d like to elaborate more about the acronym FAIR. In this case each letter stands for something different: _
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I would say that expecting that training material is FAIR is just fair, don’t you agree?
Before you can decide if you agree or not maybe I should tell you more about each part of this acronym. From the need of reusing scholar data in research was born the idea of a consise and mesurable set of principles to endorse reusability, the FAIR principles. The idea is that those need to be available for individuals but also in a machine redable format.
Challenge
Before looking for the answers bellow, try to answer with your current knoledge and perspective
“How would you interpret each of this principles?”
Elaborate shortly how you see each of them (in general and for training) and thenn compare with the text bellow:
- Findable:
- Accessible:
- Interoperable:
- Reusable:
The main goal of the FAIR principals is to SHARE. For training material this includes extending, updating and modifiing the material to a certain audiance or circustances. To achieve this final goal the for principals can be organized in 10 rules Garcia et al. 2020. Findable:
For data, including training material, to be considered FINDABLE it needs to take in consideration 3 rules . First the material needs to be described in such a way that humans and machines can find the material and its metadata, it needs to have a unique identifier and to be registered online in a catalogue or repositorie.
Accessible:
To be condered ACCESSIBLE, the most importante thing is to define access rules. It can be through lisces, document stating the rules or a policy, any of those will allow the person who finds it to know how it can be access and what is authorized to do like sharing, re-using, modifing. In some cases the material might be restrict or closed, but its metadata can still be found and the rules for the accessibility are clearly stated.
Interoperable:
Working as expected in different operational systems (OS) and different plataforms is the main idea behing Interoperability ! For now I take the liberty to say that , maybe, this is one level more complicated from training material then it is for scientific data, just because we’ve been worring about it for longer when it comes to data analysis. But as you will see in the session for training material, there are several types of training material and some of them will be easy to execute in any OS, but not easily editable, extended or updated. While other can fufill this needs but be a little trickier to execute in one or the other system/platform. You must be asking yourself : “So what is the perfect solution?” , in this case some solutions are possible, some are preferable but a it will vary according to considerations as you will see later in this lesson.
Reusable:
After carrefuly considering all the above, you want to reuse some material or make your material reusable. Consider that when it comes to training there are two main groups that can reuse the materia (1) the trainers & (2) the trainees, so annotate, describe and make it all clear so they can read, listen or watch and know what you mean independently of your presence. And keep your material up-to-date! That is probably easier by welcoming contributions, by using a colaboratie plataform as GitHub or similar, and by making clear statements of how someone cna contribute.
In case is not yet clear, all this steps also consider that the ones involved need to be auknoledge, as author or contributors, sharing material and reusing as much as in science needs to provide proper recognition for those who dedicate their time and effort to do so, unless they assing a CC0 license or similar. But we will talk more about this in the following chapters.
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Ten simple rules for making training materials FAIR. (Illustration from Luc Wiegers and Celia van Gelder:https://doi.org/10.5281/zenodo.3593257.)
1.3 How are FAIR different then OPEN ?
Now that you know a bit about what the acronym for FAIR states for, you can try to about this question, “how are FAIR and OPEN different ?”.
OPEN is related to the rules to access and share the material, clear rules will define if you can freely access, modify and share, or state that there are restrictions for a specific group or under registration in a platfomr and might make restrictions about how to share and with whom. Many are the possibilities. Last but not least, it can have closed access and still be FAIR. You can find metadata, and information about it, but you cannot access.
From the course: RDM: your aly in your way to your publication
1.4 Why to create FAIR training material?
When you make your material FAIR you enable the community exchange while alowing to this material to live beyond! It makes easier the content data share and the maintanence, updated and reuse by others. You also reinforce practices to you ensure trainers and content creators recognition.