Enhancing Metadata Editor Support for Dual-Task Datasets (Credit + Carbon Scoring) in Rural Inclusion Contexts

[Deezpa]

Enhancing Metadata Editor Support for Dual-Task Datasets (Credit + Carbon Scoring) in Rural Inclusion Contexts

Hello World Bank Metadata-Editor Team,

I am Dr. Deepa Shukla, Chief Strategic AI/ML Integrator at AgAutomate Pvt. Ltd. and a PhD Research Scholar in Computer Science (Jaipur National University, India).
Recently, I have submitted a paper at the World Bank–ECB–Bank of Italy Conference on Trade, Value Chains, and Financial Linkages, titled
“AI-Enabled Financial Linkages in Sustainable Value Chains: Integrating Credit and Carbon Scoring Microdata from Rural India.”

💡 Context

Our research focuses on integrating financial inclusion datasets (credit scoring of thin-file farmers) with environmental metrics (soil carbon, climate resilience).
We use Harvard Dataverse for open dataset dissemination (DOIs: 10.7910/DVN/6MLVVI and 10.7910/DVN/YGEJSE) and aim to align our metadata pipelines with World Bank Metadata Editor for interoperability and FAIR compliance.

🔧 Proposal

Could Metadata Editor support a metadata template or module for dual-task datasets that combine financial (credit) and environmental (carbon) indicators?
Specifically:

• Fields or controlled vocabularies for CreditScoreModelInputs and CarbonScoreModelInputs.
• Tags for alternative data sources (remote sensing, IoT, digital finance traces).
• Interoperable export between DDI-Lifecycle XML and Dataverse JSON formats.
• Support for Responsible AI metadata: fairness metrics, bias testing notes, explainability summaries.

🌍 Why It Matters

• Enables interoperability between open-data ecosystems (World Bank, Harvard Dataverse, AgAutomate datasets).
• Supports ESG-aligned research integrating finance + sustainability.
• Facilitates dataset transparency and reuse in Responsible AI for digital credit and carbon scoring models in rural economies.

🤝 Offer to Contribute

I can share:

• JSON schema mappings for the dual-domain metadata model.
• Example datasets and documentation based on our published work.
• Feedback on Responsible AI metadata fields relevant to NABARD and World Bank projects.

Would the maintainers consider such a contribution or template proposal?
Are there ongoing metadata schema efforts addressing financial–environmental dataset interoperability?

Thank you for maintaining this vital tool for global data governance.
Warm regards,
Dr. Deepa Shukla
Chief Strategic AI/ML Integrator – AgAutomate Pvt. Ltd.
PhD Research Scholar – Jaipur National University, India
ORCID: 0000-0003-3016-1633