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Challenge

Build a Disaster Declaration Administrative Frequency Auditor

Correlate municipal asset portfolios against OpenFEMA disaster declarations to measure regional declaration frequency. Quantify historical administrative disaster frequencies to guide municipal infrastructure adaptation grant planning and funding applications.

Data ScienceHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Correlate municipal asset portfolios against OpenFEMA disaster declarations to measure regional declaration frequency. Quantify historical administrative disaster frequencies to guide municipal infrastructure adaptation grant planning and funding applications.

Municipal Adaptation Planner

Filter OpenFEMA DisasterDeclarationsSummaries by state, county, and incidentType 'Flood'.

Ingest municipal facility locations and match to county FIPS codes.

Calculate historical administrative declaration frequencies and mean intervals between declarations.

Produce a capital improvement grant prioritization list based on administrative declaration frequency.

Streamlit application displaying county administrative disaster timelines, declaration metrics, and facility grant priority tables.

Query OpenFEMA API endpoint /v2/DisasterDeclarationsSummaries with $filter or download historical CSV extract using $allrecords=true. Starter examples below are synthetic. They are not downloaded records.

FEMA OpenFEMA Queries OpenFEMA DisasterDeclarationsSummaries using $filter parameters state, incidentType, and declarationDate specified in OpenFEMA docs.

mastra-ai, requests, pandas. Mastra AI provides deterministic workflow orchestration and schema validation for API aggregation pipelines. Local or hosted LLM to generate narrative adaptation grant summaries based on historical administrative declaration counts.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Correctly formats OData query parameters including ISO-8601 timestamps.

Aggregates flood declarations per county over specified multi-decade windows.

Ranks public assets by county administrative disaster declaration counts for grant planning.

```json [ { "input": { "_record_type": "simplified synthetic app record", "county_fips": "12086", "state": "FL", "declarations": [ { "disasterNumber": 4001, "incidentType": "Flood", "declarationDate": "2015-01-01T00:00:00.000Z" }, { "disasterNumber": 4200, "incidentType": "Flood", "declarationDate": "2020-01-01T00:00:00.000Z" } ], "asset_count": 12 }, "expected_output": { "county_fips": "12086", "flood_declaration_count": 2, "mean_declaration_interval_years": 5, "grant_priority_level": "MODERATE_FREQUENCY" } }, { "input": { "_record_type": "simplified synthetic app record", "county_fips": "12001", "state": "FL", "declarations": [], "asset_count": 3 }, "expected_output": { "county_fips": "12001", "flood_declaration_count": 0, "mean_declaration_interval_years": null, "grant_priority_level": "LOW_FREQUENCY" } } ] ```

Does not calculate physical flood risk or provide engineering guarantees; outputs strictly reflect administrative grant declaration history for funding evaluation. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Does not calculate physical flood risk or provide engineering guarantees; outputs strictly reflect administrative grant declaration history for funding evaluation. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Correctly formats OData query parameters including ISO-8601 timestamps. Aggregates flood declarations per county over specified multi-decade windows. Ranks public assets by county administrative disaster declaration counts for grant planning.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Filter OpenFEMA DisasterDeclarationsSummaries by state, county, and incidentType 'Flood'. Ingest municipal facility locations and match to county FIPS codes. Calculate historical administrative declaration frequencies and mean intervals between declarations. Produce a capital improvement grant prioritization list based on administrative declaration frequency.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Correctly formats OData query parameters including ISO-8601 timestamps. Aggregates flood declarations per county over specified multi-decade windows. Ranks public assets by county administrative disaster declaration counts for grant planning.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Streamlit application displaying county administrative disaster timelines, declaration metrics, and facility grant priority tables.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Does not calculate physical flood risk or provide engineering guarantees; outputs strictly reflect administrative grant declaration history for funding evaluation.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Filter OpenFEMA DisasterDeclarationsSummaries by state, county, and incidentType 'Flood'.

  • Ingest municipal facility locations and match to county FIPS codes.

  • Calculate historical administrative declaration frequencies and mean intervals between declarations.

  • Produce a capital improvement grant prioritization list based on administrative declaration frequency.

Resources and assets

Reference links and supporting material

Dataset notes

Query OpenFEMA API endpoint /v2/DisasterDeclarationsSummaries with $filter or download historical CSV extract using $allrecords=true. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

Mastra AI

TypeScript agent framework.

Evaluated output

No output checks are configured.

Evaluation checks
  • Filter OpenFEMA DisasterDeclarationsSummaries by state, county, and incidentType 'Flood'. Ingest municipal...
  • Correctly formats OData query parameters including ISO-8601 timestamps. Aggregates flood declarations per c...
  • Streamlit application displaying county administrative disaster timelines, declaration metrics, and facilit...
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 2 configured tools

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • Mastra AI · Optional
Orchestration
  • Mastra AI · Optional

Evaluation contract

  • Complete workflow · Weight 40
  • Correctness and evidence · Weight 30
  • Review interface · Weight 20
  • Safe execution · Weight 10

Reference cases

  • 2 public reference cases

Workflow tasks

No workflow tasks are configured.

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Build a Disaster Declaration Administrative Frequency Auditor