Short Description
With the data now FAIRified you need to decide the conditions for researchers to get access to the data. Furthermore, you will need to decide whether they are allowed to re-share your data, use the data commercially, etc [ru].
Data should be shared as open as possible and as closed as necessary [H2020] – closed, to safeguard the privacy of the subjects, and open to allow the data to be reused [AofFAIR]. If data are not open access, access to the data can governed by a Data Access Committee (DAC), a formal or informal group of individuals with the responsibility of reviewing and assessing data access requests [DAC]. The access conditions are described in the data access policy [FAIRopoly].
The conditions for reuse of the data are specified in either a license or data usage agreement (DUA). A license specifies a standard set of terms and conditions under which data can be shared and reused, whereas a DUA can be customised with specific conditions [ru2].
Access can be layered. For example, in a dataset, the metadata could be open and available for reuse under a CC0 license, but access to the data could require explicit approval – see [De Novo]. Ideally, accessibility is specified in such a way, that a machine can automatically understand the requirements and perform an appropriate action [GOFAIR2]. By requesting users to create a user account for a repository, access to a dataset can be controlled more easily.
We can also add something about different types of access (e.g. open access, registered access, controlled access, …) , see https://rdmkit.elixir-europe.org/human_data and https://libguides.library.usyd.edu.au/datapublication/access
Working Group
Why is this step important
Accessibility in FAIR implies that one should provide the exact conditions under which the data are accessible. These exact conditions should be clear to machines and humans. By completing this step, access to the data should be well defined.
Expertise requirements for this step
This section could describe the expertise required. Perhaps the Build Your Team step could then be an aggregation of all the “Expertise requirements for this step” steps that someone needs to fulfil his/her FAIRification goals.
How to
This could be interesting:
https://direct.mit.edu/dint/article/2/1-2/66/9993/Ontology-based-Access-Control-for-FAIR-Data
https://rdmkit.elixir-europe.org/human_data
Selecting suitable access modes for sharing human data:
Human data often carries restrictions to its use and it would need to be shared in a manner that obeys such restrictions. There are three access modes for sharing research data:
Open access: Data is shared publicly. Open-access is a rarely used access mode for the sharing of human data. To use open-access researchers need to ensure that the shared data cannot be traced back to individual study participants. In other words the data needs to be anonymised, which is difficult in practice.
Registered access: Data is shared with researchers, whose “researcher” status has been vouched for by their institution and who agree to abide by data usage policies of repositories that serve the shared data. Datasets that are shared via registered-access would typically have no restrictions besides the condition that data is to be used for research.
Controlled access: Data can only be shared with researchers, whose research is reviewed and approved by a data access committee (DAC). Typically researchers, who were involved in the primary collection of data will form the DAC. Use conditions for controlled-access could be a multitude and includes allowed research topics, allowed geographical regions, allowed recipients e.g. non-profit organisations.
https://libguides.library.usyd.edu.au/datapublication/access
Open access – There are no restrictions on access to the data; anyone can view and download a copy.
Embargoed access – A description of your dataset is published, including information such as the dataset title, who created it, and what the data are; however, the dataset is inaccessible until after a specified period of time has elapsed. At the end of the embargo period, data will become available by either open or mediated access, depending on the option that you’ve selected.
Mediated access – A description of your dataset is published, including information such as the dataset title, who created it, and what the data are; however, others won’t be able to access the data until after they apply and have their application approved. Conditions of access are usually set by the owner or submitter of the data and may include providing proof that the requester is a genuine researcher and that they have ethical approval from their own institution to undertake the research.
Closed access – A description of your dataset is published, including information such as the dataset title, who created it, and what the data are; however, the dataset is inaccessible and there is no process in place to allow others to apply for access to it.
Practical Examples from the Community
This section should show the step applied in a real project. Links to demonstrator projects.
References & Further reading
[FAIRopoly] FAIRopoly https://www.ejprarediseases.org/fairopoly/
[Generic] A Generic Workflow for the Data FAIRification Process: https://direct.mit.edu/dint/article/2/1-2/56/9988/A-Generic-Workflow-for-the-Data-FAIRification
[Elixir] https://faircookbook.elixir-europe.org/content/recipes/introduction/fairification-process.html
[Elixir2] A framework for FAIRification processes: https://faircookbook.elixir-europe.org/content/recipes/introduction/metadata-fair.html
[GOFAIR] https://www.go-fair.org/fair-principles/f2-data-described-rich-metadata/
[RDMkit] https://rdmkit.elixir-europe.org/machine_actionability.html
[De Novo] https://ojrd.biomedcentral.com/articles/10.1186/s13023-021-02004-y
[GOFAIR2] https://www.go-fair.org/fair-principles/r1-1-metadata-released-clear-accessible-data-usage-license/
[DAC] https://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-020-0453-z
[H2020] European Commission. Directorate-General for Research & Innovation. H2020 Programme Guidelines on FAIR Data Management in Horizon 2020. Version 3.0. 26 July 2016.
[AofFAIR] https://direct.mit.edu/dint/article/2/1-2/47/9998/The-A-of-FAIR-As-Open-as-Possible-as-Closed-as
[ru] https://data.ru.nl/doc/help/helppages/best-practices/bp-selecting-dua.html?0
[ru2] https://www.ru.nl/rdm/vm/licenses-data-use-agreements/
Authors / Contributors
Experts who contributed to this step and whom you can contact for further information