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Data availability
Data management (data curation, archiving, and sharing) are central to FROST’s scientific vision.
Our team is developing a data portal to make all research outputs FAIR (Findable, Accessible, Interoperable, and Reusable) and CARE (Collective Benefit, Authority to Control, Responsability and Ethics).
Traditional Ecological Knowledge will remain the property of the knowledge holders. All data will be stored and shared in accordance with ethical protocols and community agreements. The portal, currently under construction as part of a postdoctoral initiative, will ensure that FROST data are openly available through recognized repositories, enhancing the transparency, visibility, and impact of our research across the Arctic.
FAIR
FAIR Principles
Findability
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.
Accessibility
Once the user finds the required data, she/he/they need to know how they can be accessed, possibly including authentication and authorisation
Interoperability
The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.
Reuse of digital assets
Metadata and data should be well-described so that they can be replicated and/or combined in different settings.
FAIR
CARE Principles of Indigenous Data Governance
Collective Benefits
Data ecosystems shall be designed and function in ways that enable Indigenous Peoples to derive benefit from the data.
Authority to Control
Indigenous Peoples’ rights and interests in Indigenous data must be recognised and their authority to control such data be empowered.
Responsibility
Those working with Indigenous data have a responsibility to share how those data are used to support Indigenous Peoples’ selfdetermination and collective benefit.
Ethics
Indigenous Peoples’ rights and wellbeing should be the primary concern at all stages of the data life cycle and across the data ecosystem.
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