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Design Principles
The design principles of the catalog include
- 1.Led by hands-on Data Practitioners
- 2.Open Access, Common Good — #BeFAIRandCARE
- 3.Optimized for Speed & Scale
- 4.Align with Emerging Frameworks
- 5.Zero Knowledge Proof Location
Many frameworks and projects are initiated with a top down approach. Its important the catalog is designed together with real world practitioners and truly help them get their jobs done. This includes professionals with a data engineering, analytics, and data science backgroundd.
The Nature Data Catalog is being designed with FAIR and CARE principles.
FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability. See these principles here.
CARE data principles include collective benefit, authority to control, responsibility, and ethics. See these principles here.
Data ecosystems shall be designed and function in ways that enable Indigenous Peoples to derive benefit from the data.
- C1. For inclusive development and innovation
- C2. For improved governance and citizen engagement
- C3. For equitable outcomes
Indigenous Peoples’ rights and interests in Indigenous data must be recognized and their authority to control such data respected.
- A1. Recognizing rights and interests
- A2. Data for governance
- A3. Governance of data
Those working with Indigenous data have a responsibility to share how those data are used to support Indigenous Peoples’ self determination and collective benefit.
- R1. For positive relationships
- R2. For expanding capability and capacity
- R3. For Indigenous languages and worldviews
Indigenous Peoples’ rights and wellbeing should be the primary concern at all stages of the data life cycle and across the data ecosystem.
- E1. For minimizing harm and maximizing benefit
- E2. For justice
- E3. For future use
Given the collective urgency ever present, we are committed to moving quickly with a dedicated commitment to action and focus — some refer to this spirit as festina lente — make haste slowly
To accelerate traction and cross sector collaboration. We are committed to supporting numerous frameworks starting with the TNFD and LEAP Approach.
We recognize that location data is highly sensitive and are designing any location data disclosures to take advantage of recent innovations regarding ZKP which can protect organizations and individuals from disclosing sensitive data. More info here.