Airtable News Impact Database
Budget / Salary$750–1,500
TypeFreelance project
LocationRemote
Posted1 hour ago
We need an Airtable specialist to build a comprehensive, structured database designed to organize thousands of news stories and positive-action initiatives. The database will serve as the foundation for a larger AI-powered story classification system, with external integrations and automation handled separately by our team.
Each story will eventually be categorized across three interconnected classification systems:
• WHO: Generations, economic classes, races, education levels, income brackets, professions, and BLS occupational categories.
• WHAT: 14 transition domains (80 subcategories), 17 UN Sustainable Development Goals, and 152 social, political, and economic issues.
• WHERE: Continents, countries, U.S. states, counties, congressional districts, and ZIP codes.
These datasets contain approximately 48,500 classification records, which must be populated and organized into hierarchical, interconnected tables without unnecessary duplication.
What we need:
1. Design and build a scalable Airtable database with properly linked tables for stories and all three classification systems.
2. Populate the classification tables with the complete WHO, WHAT, and WHERE taxonomies, including their hierarchical relationships.
3. Create intuitive views, filters, and search tools to identify stories by any combination of classification criteria.
4. Develop a simple request/export process allowing users to retrieve matching stories as CSV or PDF files.
5. Provide basic documentation or training so our team can independently maintain and expand the database.
Scope: This project is strictly Airtable database development. No story uploads, AI integrations, or external workflow automation are required.
Our goal is a single, streamlined, easily searchable and expandable Airtable base that consolidates these classifications alongside additional fields, such as AI-generated summaries, classification confidence assessments, and human-review status. We have a working proof of concept available for reference and can provide further specifications for these additional features during the project.
Each story will eventually be categorized across three interconnected classification systems:
• WHO: Generations, economic classes, races, education levels, income brackets, professions, and BLS occupational categories.
• WHAT: 14 transition domains (80 subcategories), 17 UN Sustainable Development Goals, and 152 social, political, and economic issues.
• WHERE: Continents, countries, U.S. states, counties, congressional districts, and ZIP codes.
These datasets contain approximately 48,500 classification records, which must be populated and organized into hierarchical, interconnected tables without unnecessary duplication.
What we need:
1. Design and build a scalable Airtable database with properly linked tables for stories and all three classification systems.
2. Populate the classification tables with the complete WHO, WHAT, and WHERE taxonomies, including their hierarchical relationships.
3. Create intuitive views, filters, and search tools to identify stories by any combination of classification criteria.
4. Develop a simple request/export process allowing users to retrieve matching stories as CSV or PDF files.
5. Provide basic documentation or training so our team can independently maintain and expand the database.
Scope: This project is strictly Airtable database development. No story uploads, AI integrations, or external workflow automation are required.
Our goal is a single, streamlined, easily searchable and expandable Airtable base that consolidates these classifications alongside additional fields, such as AI-generated summaries, classification confidence assessments, and human-review status. We have a working proof of concept available for reference and can provide further specifications for these additional features during the project.
Apply on Freelancer →
Project sourced from Freelancer.com. Applications happen directly on the original platform — we never collect your data.