FAIR vs OPEN Data Principles

The produced research data serves its intended purpose upon creation. However, once its primary usage is fulfilled, it is frequently discarded, forgotten, or lost. Such circumstances can result in substantial financial implications for our organization or the funding entity, funds that could be more effectively allocated. Hence, it becomes imperative for us to take comprehensive measures in producing data that enables its future utilization. This includes reproducibility of research to validate results as well as the proactive sharing of our data with others.

By adhering to the FAIR Principles, we can ensure that the data, which has required significant financial and energy investments, will not only be preserved but also made available for potential future reuse, regardless of the purpose we may identify later.

On the other hand, making the research data OPEN improves the quality, efficiency, and responsiveness of research as a field. Research is inherently a collaborative endeavor, and the opportunity to utilize others' data should always be available. The OPEN Data Principles collectively strive to establish an environment in which data can be freely accessed, shared, and utilized for the advancement of society, science, and innovation.

FAIR Principles

The acronym FAIR stands for:

• Findability: The data should have unique and persistent identifiers that allow for easy discovery and retrieval. Metadata (information about the data) should be richly described and searchable.
• Accessibility: The data should be easily accessible to both humans and machines. This means that the data should be retrievable by standard protocols and in a usable format.
• Interoperability: The data should be structured in a way that allows for seamless integration with other datasets and tools. This involves using standardized data formats and vocabularies.
• Reusability: The data should be well-documented and come with clear and comprehensive metadata. This documentation should enable other researchers to understand and use the data effectively.

By creating a Data Management Plan using an effective tool, such as the FAIR Wizard, which can incorporate established FAIR metrics, we can ensure that the project we are working on and all its associated data will adhere to the FAIR Principles, thus creating data that has more excellent value than its sole intended usage. If you want to learn more about Data Management Planning, check out our other blogpost.

OPEN Principles

The OPEN stands for:

• Openly available: The data should be made available in its entirety, without any modifications, and should be published as soon as possible. There should be no additional costs associated with accessing the data. Furthermore, the data should be provided in a user-friendly format that allows for effective reuse.
• Reusable: The data should be offered with conditions that allow for both reuse and redistribution, including the option to combine it with other datasets.
• Redistributable: Everyone should have the capability to utilize, reuse, and distribute the data without any bias towards specific areas of work or individuals or groups. For instance, limitations such as 'non-commercial' restrictions that hinder 'commercial' utilization, or constraints on usage for particular intentions (such as solely in educational contexts), are prohibited.

To follow the OPEN Principles, we should check that our data can in fact be OPEN, for example that they don't include any personal data allowing any individual identification, and if we are able to OPEN the data, we should do so.

Conclusion

The FAIR and OPEN Principles are complementary, not mutually exclusive. When embarking on a new research project, we should always consider making our data FAIR and OPEN to ensure that the valuable research we engage in can be used by others to benefit our civilization. It is vital to embrace these principles from the very start, as attempting to fulfill them later can be challenging and costly.

That can be done using the FAIR Wizard, which offers usage of metrics for your Data Management Plan, that can measure how much the planned project would fulfill OPEN and FAIR Principles.

Overall, it is good practice to adhere to the FAIR and OPEN Principles, as they also enable us to generate data with greater value beyond its initial usage. It is important to recognize that not only can others benefit from aspects like reusability, but it can also prove advantageous to our organization. For instance, if there is a requirement for repeated measurements to validate results later, or in the event that errors are discovered, these principles can be invaluable. Ultimately, embracing these best practices will benefit everyone involved.