The FAIR Principles are vital to enabling the use of data, not just for people, but more importantly for machines.
The FAIR principles are designed to address the necessary steps to make research data and the metadata attached to it FAIR (Findable, Accessible, Interoperable, and Reusable). FAIR enables the use of data and metadata for a wide range of use cases and without it, data is not consumable in a way that is needed to build upon research, to make it reproducible, or to provide it as a trusted source of verified information to new technologies such as artificial intelligence. While the principles were not specifically designed to be applied to metadata schema, or not in isolation, this 4-part blog series will address each of the interlinked FAIR principles and, how Ringgold Data is FAIR Data for organization identification.
The first post in our series explores how Ringgold data and metadata are Findable.
Findable
The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services, so this is an essential component of the FAIRification framework.
F1. (Meta)data are assigned a globally unique and persistent identifier
Ringgold IDs are globally unique and persistent, they do not change when an organization changes name or location, and they have been persistent for 20 years. Ringgold IDs are not always used as a resolvable unique ID in that the number can be used independently of the URL for the ID. However a globally unique persistent ID (PID) does exist in the current user interface: https://ido.ringgold.com/institution/1848 which will be transformed to a resolvable globally unique persistent ID in our new interface: https://ringgold-identify.copyright.com/organization/1848 and provided in other services.
F2. Data are described with rich metadata
Ringgold includes rich metadata. If a user or machine is looking for data but does not know the ID or the name of the organization, it is still able to locate the data using the rich metadata. It is also possible to search and filter on any metadata element and locate records which agree with those search/filter parameters. Customers can pull in additional metadata using the linked PIDs in the Ringgold Identify Database (e.g., ISNI IDs) as well as their own data mapped to Ringgold IDs. The context of the metadata is clearly identifiable, such as the deprecation of an ID when organizations merge will point to the new organization into which it was subsumed.
F3. Metadata clearly and explicitly include the identifier of the data they describe
This is inherent in the Ringgold data as the Ringgold ID is the linking point between metadata elements, e.g., in the data exports and APIs. For customer use, the Ringgold ID is linked to all Ringgold metadata and can be imported, extracted, and used in many ways alongside and in conjunction with additional metadata within the client’s systems.
F4. (Meta)data are registered or indexed in a searchable resource
Ringgold Data is registered in a searchable resource, Ringgold Identify Database, which is available on the internet and linked to from multiple pages indexed by all major search engines. Ringgold licensees and registered interested parties can query the data directly and verify the data about an organization held in metadata.
Comprehensive Data Management: Beyond FAIR Principles
When thinking about data we should also consider other data principles in addition to FAIR, including but not limited to systems and data security such as SOC2 and ISO standards certification, privacy standards including application of all national and regional legislation and best practices, and best practices around business models and sustainability to ensure the longevity of data access. Not least we should consider data quality and apply metrics in the form of dimensions of data appropriate to the context and develop certificates of data quality.
While “quality issues are not addressed by the FAIR principles,” for over 20 years, publishers have relied on the excellence of Ringgold data. All records in the Ringgold Identify Database are created, maintained and quality-controlled by a team of data experts. This data maintenance is done in accordance with rigorous, up-to-date editorial policies, and changes are structured, tracked, and made available within the dataset. CCC adheres to best practices for data quality, security, and compliance. Ringgold Solutions provides a robust, sustainable solution that continues to evolve with the industry.
Learn about how Ringgold data and metadata are Accessible.
Learn about how Ringgold data and metadata are Reusable.
Learn about how Ringgold data and metadata are Interoperable.