Assessing the FAIRness of Metadata Schemas
Creators: name: Miranda Soares, Filipi
name: Ferreira Pires, Luís
name: Bonino da Silva Santos, Luiz Olavo
name: Calhau, Rodrigo Fernandes
name: Coura Moreira dos Santos Maculan, Benildes
name: Coyle, Karen
name: Wang, Shenghui
name: Folmer, Erwin
name: Drucker, Debora
name: de Almeida Campos, Maria Luiza
name: Marcondes, Carlos Henrique
name: Barcellos Almeida, Maurício
name: Braghetto, Kelly Rosa
name: Ataíde Dias, Guilherme
name: Salim, José Augusto
name: Correa, Fernando Elias
name: Abreu Moreira, Dilvan de
name: Botazzo Delbem, Alexandre Cláudio
name: Saraiva, Antonio Mauro
Publisher: name: Zenodo
Year: 2025

description: This assessment evaluates the FAIRness of metadata schemas based on the FAIR-related concepts addressed in the paper's conceptual model.

We assessed the FAIRness level of three metadata schemas: Darwin Core, D-CAT, and Almes Core. However, this analysis was preliminary. A more detailed assessment should be performed by the authority managing these schemas.



Methodology


The concepts from the conceptual model representing FAIR indicators were associated with one of the Refined FAIR principles presented in Table 1. The FAIR principles were assessed based on the presence or absence of specific FAIR indicators, with each FAIR indicator receiving a score from 0.25 to 1. The scores within a principle were then summed to calculate the total score for that principle. Details on the scores of each element are shown in Table 1A.




Ref. FAIR
FAIR P.
Indicator Score




RF1
F
Namespace (0.5); version unique identifier (0.5)


RF2
F
Landing page (0.5); metadata record for humans (0.25); metadata record for machines (0.25)


RF3
F
Indexing in vocabulary catalog (1)


RF4
A
URLs use universally accessible protocols (1)


RF5
A
Backup (1)


RF6
I
Machine-actionable serialization (1)


RF7
I
Schema Conceptual model (1)


RF8
I
Data Properties (0.5); Range and Domain (0.5)


RF9
I
Object Properties (0.5); Range and Domain (0.5)


RF10
R
Term name (0.5); Definition (0.5)


RF11
R
Open License (1)


RF12
R
Documentation of Modifications (1)


RF14
I (50%) R (50%)
Schema reuse (1)




Table 1A – Template for calculating the FAIRness level of metadata schemas.

The declaration of the schema authority determined by principle RF13 should be included in the metadata record (principle RF2).

Each indicator related was scored based on its presence (true) or absence (false). If a indicator is present, it contributes its full score; if absent, it contributes zero. For example, for Principle F (Findability):

RF1 = Namespace (0.5) (true) + version unique identifier (0.5) (true) RF1 = 0.5 + 0.5 = 1

RF2 = Landing page (0.5) (true) + metadata record for humans (0.25) (true) + metadata record for machines (0.25) (true) RF2 = 0.5 + 0.25 + 0.25 = 1

RF3 = Indexing in vocabulary catalog (1) (false) = 0 RF3 = 0

The total score for each principle is the sum of its components' scores:

Total Score for F = RF1 + RF2 + RF3 = 1 + 1 + 0 = 2

The fulfillment percentage for each principle (PF%) is calculated by dividing the total score (TS) by the maximum possible score (MPS) for that principle, then multiplying by 100.

PF% = (TS / MPS) * 100 PF% = (2 / 3) * 100 PF% = 66.67%

The overall FAIR compliance score (OFC%) is the average of the fulfillment percentages of all principles.



Validation


To validate the FAIR assessment proposed, we evaluated three metadata schemas: Darwin Core, D-CAT, and Almes Core.



FAIRness assessment of the Darwin Core schema





Ref. FAIR Principle
FAIR Principle
Indicator present
Indicator absent
Score




RF1
F
Namespace (0.5); version unique identifier (0.5)
 
1


RF2
F
Landing page (0.5); metadata record for humans (0.25)
metadata record for machines (0.25)
0.75


RF3
F
Indexing in vocabulary catalog (1)
 
1


RF4
A
URLs use universally accessible protocols (1)
 
1


RF5
A
Backup (1)
 
1


RF6
I
 
Machine-actionable serialization (1)
0


RF7
I
Schema Conceptual model (1)
 
1


RF8
I
Data Properties (0.5)
Range and Domain (0.5)
0.5


RF9
I
Object Properties (0.5)
Range and Domain (0.5)
0.5


RF10
R
Term name (0.5); Definition (0.5)
 
1


RF11
R
Open License (1)
 
1


RF12
R
Documentation of Modifications (1)
 
1


RF13
I (50%) R (50%)
Schema reuse (1)
 
1






 

Calculation (results also shown in Fig. 1):





Principle F
Principle A
Principle I
Principle R




F = 1 + 0.75 + 1
A = 1 + 1
I = 0 + 1 + 0.5 + 0.5 + 0.5
R = 1 + 1 + 1 + 0.5


F = 2.75
A = 2
I = 2.5
R = 3.5


PF% = (2.75 / 3) * 100
PF% = (2 / 2) * 100
PF% = (2.5 / 4.5) * 100
PF% = (3.5 / 3.5) * 100


PF% ≅ 92%
PF% = 100%
PF% ≅ 55.5%
PF% = 100%






 

Overall FAIR compliance score (OFC%):


OFC% = (92 + 100 + 55.5 + 100) / 4

OFC% ≅ 87%



Comments:


For the F principle, the standard lacks a machine-actionable serialization of the metadata record on the landing page, although it provides a very detailed record in HTML format. Regarding the I principle, the schema is not available in semantic web formats such as RDF or OWL, despite documentation suggesting how to use Darwin Core as RDF. As noted on their page, "No terms defined within the Darwin Core namespace have range or domain declarations.” This omission hinders the creation of OWL or RDF serializations of the schema. Additionally, the lack of semantic annotations impedes automated data integration and interoperability across different systems, which are critical to achieving the I principle in the FAIR framework.

Overall, the schema performed well in most aspects of FAIR, reflecting the intense and diligent efforts of the managing authority. This demonstrates a strong commitment to ensuring that the schema meets high standards of findability, accessibility, interoperability, and reusability. Such performance highlights the authority's dedication to maintaining and improving the quality and usability of the schema, which is crucial for supporting diverse data management and integration needs within the community.



FAIRness assessment of the Data Catalog Vocabulary (DCAT) - Version 3





Ref. FAIR Principle
FAIR Principle
Indicator present
Indicator absent
Score




RF1
F
Namespace (0.5); version unique identifier (0.5)
 
1


RF2
F
Landing page (0.5); metadata record for humans (0.25); metadata record for machines (0.25)
 
1


RF3
F
Indexing in vocabulary catalog (1)
 
1


RF4
A
URLs use universally accessible protocols (1)
 
1


RF5
A
Backup (1)
 
1


RF6
I
Machine-actionable serialization (1)
 
1


RF7
I
Schema Conceptual model (1)
 
1


RF8
I
Data Properties (0.5); Range and Domain (0.5)
 
1


RF9
I
Object Properties (0.5); Range and Domain (0.5)
 
1


RF10
R
Term name (0.5); Definition (0.5)
 
1


RF11
R
Open License (1)
 
1


RF12
R
Documentation of Modifications (1)
 
1


RF13
I (50%) R (50%)
Schema reuse (1)
 
1






 

Calculation (results also shown in Fig. 2):





Principle F
Principle A
Principle I
Principle R




F = 1 + 1 + 1
A = 1 + 1
I = 1 + 1 + 1 + 1 + 0.5
R = 1 + 1 + 1 + 0.5


F = 3
A = 2
I = 4.5
R = 3.5


PF% = (3 / 3) * 100
PF% = (2 / 2) * 100
PF% = (4.5 / 4.5) * 100
PF% = (3.5 / 3.5) * 100


PF% = 100%
PF% = 100%
PF% = 100%
PF% = 100%






 

Overall FAIR compliance score (OFC%):


OFC% = (100 + 100 + 100 + 100) / 4

OFC% = 100%



Comments:


DCAT Version three is a 100% FAIR metadata schema. All the concepts included in this metrics have been found in the schema documentation.



FAIRness assessment of the Almes Core schema





Ref. FAIR
FAIR P.
Indicator present
Indicator absent
Score




RF1
F
Namespace (0.5); version unique identifier (0.5)
 
1


RF2
F
Landing page (0.5); metadata record for humans (0.25); metadata record for machines (0.25)
 
1


RF3
F
Indexing in vocabulary catalog (1)
 
1


RF4
A
URLs use universally accessible protocols (1)
 
1


RF5
A
Backup (1)
 
1


RF6
I
Machine-actionable serialization (1)
 
1


RF7
I
Schema Conceptual model (1)
 
1


RF8
I
Data Properties (0.5); Range and Domain (0.5)
 
1


RF9
I
Object Properties (0.5); Range and Domain (0.5)
 
1


RF10
R
Term name (0.5); Definition (0.5)
 
1


RF11
R
Open License (1)
 
1


RF12
R
Documentation of Modifications (1)
 
1


RF13
I (50%) R (50%)
Schema reuse (1)
 
1






 

Calculation (results also shown in Fig. 3):





Principle F
Principle A
Principle I
Principle R




F = 1 + 1 + 1
A = 1 + 1
I = 1 + 1 + 1 + 1 + 0.5
R = 1 + 1 + 1 + 0.5


F = 3
A = 2
I = 4.5
R = 3.5


PF% = (3 / 3) * 100
PF% = (2 / 2) * 100
PF% = (4.5 / 4.5) * 100
PF% = (3.5 / 3.5) * 100


PF% = 100%
PF% = 100%
PF% = 100%
PF% = 100%






 

Overall FAIR compliance score (OFC%):


OFC% = (100 + 100 + 100 + 100) / 4

OFC% = 100%