Source freshness and comparability

Worked example

A trade analyst can check whether monthly data cover the same periods, geography and definitions. Mark a missing release as missing before comparing totals.

Keep observation dates, retrieval dates, revisions and forecasts distinct under a declared assessment date.

Try it yourself

The calculator opens with the fictional example already filled in. Change one input, choose Calculate locally, and compare the result to the original values below. Use Reset fictional fixture to start over.

An unknown result means the available inputs do not support a value. Check the calculator’s Warnings tab for what is missing or uncertain.

Observed records beyond age threshold 1 records
Unknown observation dates 0 records
Records requiring comparison review 1 records
Missing-period ratio Undefined for these inputs
Geographic coverage ratio Undefined for these inputs

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Calculator

Approach (label only)Changing the label does not improve capacity, speed, error rates or confidence. Enter measured differences explicitly.

Comparison conditions and human review

Equal-resource comparison conditionsRecord budget, staffing, resources, information release dates, scenario conditions and evaluation criteria. Material differences can make options not comparable.

Evaluation period

Geography / exercise boundary

Human reviewers and roles

This evaluation depends on a real transaction

Supplied human authority gateThis declaration is not legal certification. Blocked, pending or assumed gates stop transaction-dependent evaluation.

Keep units consistent within each table. Enter zero when the amount is known to be zero. Leave optional amounts blank when they are unknown. If a required value is missing, the calculator will ask for it.

Advanced: complete input envelope and optional fields

Edit optional fields using the method dictionary. Apply validates and recalculates the entire input. Unknown values remain null.

Versioned input JSON

Import local JSON or CSV

Files stay in this browser. Maximum 1 MiB. JSON imports are recalculated. CSV supports flat observation tables, with column types taken from the displayed fixture. Empty cells become null.

Workbench JSON / input envelope

CSV target table

CSV file, matching the target table headers

Compare the arrangements

Keep physical resources and evaluation conditions equal. With identical inputs, all three approaches produce identical arithmetic. The comparison refuses material differences in declared conditions; it does not verify those declarations.

Show only differing metric rows

Privacy: comparison inputs may contain sensitive notes or operational details. Storage is off by default. Do not enter personal records or sensitive infrastructure details. Reproduction exports include supplied inputs and notes, including raw small-cell inputs suppressed from CORE-009 result tables. Suppression of displayed results does not make a reproduction export safe to publish.

Save comparison inputs on this device until I clear them

Executive brief and reproducible export

Public exercise notes

Review for personal, confidential or sensitive material before saving or sharing. No automatic submission occurs.

Read the generated brief

Method, inputs and limits

Keep observation dates, retrieval dates, revisions and forecasts distinct under a declared assessment date. Method version 0.2.0. Make an old observation current by retrieving it, interpolate missing years, or validate a forecast.

CORE-006 input dictionary
Input	Unit / type	Required interpretation
records — Dated source records	records / json	id, label, observedAt (nullable ISO), retrievedAt (ISO), publishedAt and revisedAt (optional ISO), unit, seriesType (observed/forecast/scenario), methodId.
asOf — Assessment date	ISO date / date	Use the supplied schema and declared units.
staleAfterDays — Declared stale threshold	days / number	Use the supplied schema and declared units. Minimum 0.
expectedUnit — Comparison unit	unit label / text	Use the supplied schema and declared units.
expectedMethodId — Required measurement method (optional)	method ID / text	Match the method ID used by the records you want to compare.
expectedObservationYear — Comparison observation year	year / number	Use the supplied schema and declared units. Minimum 1. Maximum 9999.
expectedPeriods — Expected periods (optional count or unique ID list)	periods / json	Declare the expected set or count; ratios never infer unreported periods.
observedPeriods — Observed periods (optional matching count or ID list)	periods / json	Use the supplied schema and declared units.
expectedGeographies — Expected geographies (optional count or unique ID list)	geographies / json	Use the supplied schema and declared units.
observedGeographies — Observed geographies (optional matching count or ID list)	geographies / json	Use the supplied schema and declared units.

Visible mathematics / decision rules

age in days = (asOf − observation date) / 86,400,000

stale = age > declared staleAfterDays; unknown observation dates remain unknown

missing-period ratio = (expected periods − observed periods) / expected periods

geographic coverage ratio = observed geographies / expected geographies; zero expected denominator is undefined

What this result cannot establish

Age is not a quality or truth score. Forecast and scenario dates do not establish historical observation. A date without a time means midnight UTC.
No records are combined or converted; method and period comparability require human review.

What would falsify the assumptions?

A dated release or revision can contradict the supplied timestamps.
Check original series units and observation years against the comparison definition.
A shared system using an older source can be less useful than an independently checked manual source.
Assumptions fail if the supplied definitions, units, period, scope or source records are wrong or incomplete.
An independent source audit or replication may contradict an input or the recorded dependency.
This method creates no resources. Physical conservation is checked in the inventory and transfer ledgers; descriptive graphs and checklists are not resource-flow models.
The same equations and review checklist can be reproduced with a spreadsheet or structured human-only process.
This is deterministic arithmetic, a descriptive comparison or a structured governance check, not a fitted causal effect or forecast. Fictional inputs remain an exercise.
Equal or worse measured errors, net review effort, disclosure burden or fallback under MAR would show no added benefit or added risk; no improvement is assumed.

Reproducible fictional fixture and independently calculated expectations

This fixture is synthetic. It does not describe a country, government, company or event.

{
  "observations": {
    "unit": "records",
    "origin": "synthetic",
    "sources": [
      {
        "id": "SYN-001",
        "kind": "synthetic",
        "label": "Fictional dated records",
        "url": null
      }
    ],
    "records": [
      {
        "id": "R1",
        "label": "Historical count",
        "observedAt": "2024-01-01",
        "retrievedAt": "2025-01-02",
        "publishedAt": "2024-02-01",
        "revisedAt": "2024-12-01",
        "unit": "people",
        "seriesType": "observed",
        "methodId": "count-v1"
      },
      {
        "id": "R2",
        "label": "Current period count",
        "observedAt": "2025-01-01",
        "retrievedAt": "2025-01-02",
        "publishedAt": "2025-01-02",
        "revisedAt": null,
        "unit": "people",
        "seriesType": "observed",
        "methodId": "count-v1"
      }
    ]
  },
  "parameters": {
    "asOf": "2025-01-11",
    "staleAfterDays": 30,
    "expectedUnit": "people",
    "expectedMethodId": null,
    "expectedObservationYear": 2025
  }
}

Expected checks

{
  "staleCount": 1,
  "unknownObservationDates": 0,
  "notComparableCount": 1
}

Download input fixture

Authoritative background references

NIST: AI Risk Management Framework — Voluntary governance background; not validation of MAR. Reviewed 2026-11-09. Reference, not endorsement or validation.

These sources inform definitions or review practices. They do not validate this implementation or endorse MAR.

Open the original Scenario Studio Examine original hypotheses Find related policy modules