Description: Metadata and data should be well-described so that they can be replicated and/or combined in different settings.
Additional information: Reusability is the central goal of FAIR and is usually the trigger for the introduction of data management and FAIR in companies. In principle, achieving F, A and I should achieve most of R - but there is another important aspect of the reusability principle that needs to be resolved. When designing data collection processes, reusability beyond the original purpose must be considered. It is usually extremely difficult to make data that is not FAIR reusable after the fact. Data reusability must be in place from the beginning, i.e. context and tacit knowledge must be built in from the start. Otherwise, there is a risk that datasets will be found and analysed under false assumptions, leading to a disruption of projects and sometimes a reluctance of researchers to share 'their' data with others.
The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets.
Publisher: ELAP
Source: https://www.go-fair.org/fair-principles/
LOST view: OV-Governance Architecture Principles
Identifier: http://data.europa.eu/2sa/elap/data-reusability
EIRA traceability: eira:EuropeanLibraryofArchitecturePrinciplesPrinciple
EIRA concept: eira:SolutionBuildingBlock
Last modification: 2023-06-27
dct:identifier: elap:data-reusability
dct:title: Data Reusability
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dct:identifier | elap:data-reusability |
eira:ABB | eira:EuropeanLibraryofArchitecturePrinciplesPrinciple |
dct:modified | 2023-06-27 |
dct:publisher | ELAP |
skos:note | Reusability is the central goal of FAIR and is usually the trigger for the introduction of data management and FAIR in companies. In principle, achieving F, A and I should achieve most of R - but there is another important aspect of the reusability principle that needs to be resolved. When designing data collection processes, reusability beyond the original purpose must be considered. It is usually extremely difficult to make data that is not FAIR reusable after the fact. Data reusability must be in place from the beginning, i.e. context and tacit knowledge must be built in from the start. Otherwise, there is a risk that datasets will be found and analysed under false assumptions, leading to a disruption of projects and sometimes a reluctance of researchers to share 'their' data with others.
The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. |
dct:title | Data Reusability |
dct:description | Metadata and data should be well-described so that they can be replicated and/or combined in different settings. |
eira:concept | eira:SolutionBuildingBlock |
eira:PURI | http://data.europa.eu/2sa/elap/data-reusability |
dct:source | https://www.go-fair.org/fair-principles/ |
eira:view | OV-Governance Architecture Principles |
eira:view | SV-Functional Architecture Principles |
eira:view | SV-Governance Architecture Principles |
eira:view | TVA-Functional Architecture Principles |
eira:view | Architecture Principles view |