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 fourth post in our series explores how Ringgold data and metadata are Reusable.
Reusable
The ultimate goal of FAIR is to optimize the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings. 
R1. (Meta)data are richly described with a plurality of accurate and relevant attributes
Ringgold Data is fully tagged and labelled, including descriptive elements, and documentation. Metadata is provided independent of use case and clients decide on their own the utility of a given piece of metadata and how it may be used in their authorized systems. External data is only provided if under a clear open license or with full permission to release the data. Variability in data is clearly marked both within the data itself and all documentation with clear vocabularies. This enables interactions between systems and use cases across the scholarly research workflow. 
R1.1. (Meta)data are released with a clear and accessible data usage license
Ringgold IDs are effectively in the public domain, e.g., in JATS and PubMed data, although are not released under a specific license attached to the data. All other Ringgold Data is provided under license with clear authorization for onward transfer, enabling clients and users to utilize the data for use cases that enable Ringgold data to become part of the scholarly record. 
R1.2. (Meta)data are associated with detailed provenance
Where Ringgold Data contains data owned or controlled by another party, it is clearly labelled as external metadata and named using the owning parties naming convention. All Ringgold proprietary data is researched internally and transformed to Ringgold standards for naming, taxonomies, and ontologies.
R1.3. (Meta)data meet domain-relevant community standards
Ringgold Data is used in domain relevant community standards for metadata such as JATS and other NISO standards. It also includes ISO 27729 standard ISNI IDs for the identification of public identities of parties in the media content industries.
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.  Â
Learn about how Ringgold data and metadata is Findable.Â
Learn about how Ringgold data and metadata are Accessible. Â
Learn about how Ringgold data and metadata are Interoperable. Â