GRC-20 Hackathon 1

Space

Review proposal

Accepted
Add data criteria

Arturas

·Accepted
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Hackathon data quality criteria
Current version
Proposed edits

3. Ontology alignment

4. Proper attribution

- Reliable sources: Make sure your data comes from trustworthy sources. - Practical value: Your data should clearly provide useful information or insights.

- Visual representation: Include visuals like covers and avatars when appropriate. - The data should in general look presentable

- Relational structure: Organize your data [relationally](https://www.geobrowser.io/space/DhLWPc7fgChKdDCYHBfiRu/DZ2YiGX7uQGv993pZM3ypA) whenever possible. - Creative use: Feel free to creatively structure your data, find new ways to represent it that would make sense.

- List your sources: Clearly list all sources you used for your dataset. - It should be easy to check the accuracy of your data by checking your sources

5. Clear visualization

2. Organized data

1. Useful data

- **Match the ontology**: Your data must follow Geo ontology specification. Use the exact types and properties listed in the ontology specification by their IDs. - If the provided list of types & properties lacks a type or a property that you need for your data, let us know before publishing to mainnet.

Name
Name
Hackathon data quality criteria
GRC-20 Hackathon 1
Current version
Proposed edits
General
Current version
Proposed edits