Open Science
Open research data
Open access to research data is a topical issue. In addition to open access to publication outputs, funders are increasingly recognising the importance of open data disclosure. For example: In its framework projects since Horizon 2020, the European Commission has made it mandatory to keep, manage and publish research data.
Opening up research data means making data available online to anyone, provided that the data can or will be further used, modified or shared, not only for the purpose of verifying research results. On the other hand – not all research data may be openly accessible and restrictions may be granted for various reasons – commercial barriers, privacy, sensitive data, etc. But at the same time, research data should be in principle published as open as possible and as closed as necessary.
In excellent research, it is nowadays necessary to pay close attention to research data.
FAIR data
In order to maximise the usability of your data, it is ideal when the data you generate and share meet the FAIR principles. The data journal Scientific Data published an article back in 2016 that looked at how to best facilitate the sharing of research data (The FAIR Guiding Principles for scientific data management and stewardship). Four basic properties of data have been defined – Findable, Accessible, Interoperable and Reusable. These principles were then adopted and applied in projects such as those of the European Commission.
15 principles of FAIR data:To be Findable
If you want your data to be reusable, then you need to ensure that both humans and machines can find them. Machine-readable metadata are crucial for this purpose.
| 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 |
To be Accessible
Data should be openly accessible, ideally through a repository. If access to the data is restricted, then at least the metadata should be freely available.
| 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 |
To be Interoperable
If you want to be able to integrate your data with other datasets, then it is advisable to use standardised terms to describe the data.
| 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 |
To be Reusable
The main goal of the FAIR principles is to increase the reusability of scientific data. To achieve this, it is important that the data are sufficiently described and shared under the least restrictive licence possible, so that users of the data know how it was created, what it describes and how they can use it.
| R1. | (meta)data have a plurality of accurate and relevant attributes |
| R1.1 | (meta)data are released with a clear and accessible data usage licence |
| R1.2 | (meta)data are associated with their provenance |
| R1.3 | (meta)data meet domain-relevant community standards |
Responsibility: Bc. Jan Skůpa