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Privacy Aggregation & Cohort Floor

This meta-model describes how the state of a population is sensed without exposing any person in it: statistics are computed over cohorts, never below a minimum cohort size, with suppression and noise where counts run thin. It is its own model because aggregation is a distinct trade with its own artifacts: cohort definitions, k-floors, noise budgets and disclosure review are reusable machinery that many consumers rely on, and the guarantees only hold if that machinery is modelled and checked in one place.

IDworld.s5-privacy-aggregation-and-cohort-floor
Version history0.2.0-legacy
CategoryReference example
IndustryCross-industry
Domainsecurity-ownership-access
Tagsprivacy, aggregation, cohort, floor
Data structure

Bundles and layers

Bundle

cohort

Which population slices may be looked at

Layers

definition`: dimensions, membership rules and validity windows of cohorts · `floors`: minimum cohort sizes per sensitivity of the underlying data

Bundle

computation

Turning members into numbers safely

Layers

measures`: statistics computed over cohorts and their methods · `protection`: cell suppression, noise addition and privacy budget accounting

Bundle

release

What actually leaves

Layers

review`: pre-release disclosure checks against floors and budgets · `publication`: released series with method and provenance attached

Findings

Catalogue-native findings must describe the information grouped by each layer. This legacy version does not declare them separately.

Questions & artifacts

Questions, artifact requirements and serial naming rules are required by Vercy vNext; they remain unassigned in this reference version.

Service layers

How this specification operates

Dimension & namespace

  • REFERENCE `world.ownership` (S1): aggregation never transfers control; source objects remain their holders' throughout.
  • REFERENCE `world.accessContract` (S2): sensing requests and series subscriptions are themselves access contracts.
  • REFERENCE `world.disclosureScope` (S3): the aggregation grains that S3 policies point to are defined and enforced here.
  • REFERENCE `world.accessAudit` (S4): every sensing run, review and release is logged.
  • REFERENCE `world.person` (H1): population registers of the person model are the typical cohort source.
  • imports: differential-privacy-practice (ALIGN): noise addition and budget accounting semantics.
  • imports: sdmx (ALIGN): the exchange shape of published statistical series.

Canon, patches & standards

  • REFERENCE `world.ownership` (S1): aggregation never transfers control; source objects remain their holders' throughout.
  • REFERENCE `world.accessContract` (S2): sensing requests and series subscriptions are themselves access contracts.
  • REFERENCE `world.disclosureScope` (S3): the aggregation grains that S3 policies point to are defined and enforced here.
  • REFERENCE `world.accessAudit` (S4): every sensing run, review and release is logged.
  • REFERENCE `world.person` (H1): population registers of the person model are the typical cohort source.
  • imports: differential-privacy-practice (ALIGN): noise addition and budget accounting semantics.
  • imports: sdmx (ALIGN): the exchange shape of published statistical series.

Artifact formats & serial data

Format-independent core. Concrete artifact formats and naming prefixes are not declared in this legacy version.

Policies & accepted processes

  • `seriesSubscription`: a consumer receives published series and their revisions; never anything below the published grain.
  • `sensingRequest`: a party commissions a new aggregate over defined cohorts; honored only above floors and within budgets.
  • `methodAudit`: an auditor examines cohort definitions, floors, budgets and methods; microdata is never in scope.

Read / add / edit / delete

CRUD procedures and interface bindings are not declared in this legacy version.

Ownership, roles & access

A statistics office steward archetype operates the model within its statutory mandate: it computes and releases, but the underlying data stays with its owners, and the steward's own reads run under S2 contracts and land in the S4 log like anyone else's.

Existing assembly

Objects, relationships, events and projections

Objects

  • `cohort`: a population subset defined by dimensions; key attributes: dimensions, membership rule, member count, validity window.
  • `kFloor`: a minimum cohort size rule; key attributes: threshold, applicable sensitivity tier, rationale, review cadence.
  • `aggregateMeasure`: one statistic computed over a cohort; key attributes: measure kind, value, period, method reference.
  • `suppressionRule`: the condition under which cells are withheld or merged; key attributes: trigger, action (suppress, merge, coarsen), scope.
  • `noiseBudget`: privacy loss accounting for a source over a period; key attributes: budget, spent, period, accounting method.
  • `releaseCandidate`: an assembled set of measures awaiting disclosure review; key attributes: contents, requested by, review state.
  • `publishedSeries`: a released statistical series; key attributes: series identity, periods, method summary, provenance.

Relationships

  • `aggregateMeasure` -> computedOver -> `cohort` (*..1): every number names the cohort it summarizes.
  • `cohort` -> constrainedBy -> `kFloor` (*..1): a cohort below its floor yields no measure at all.
  • `releaseCandidate` -> assembles -> `aggregateMeasure` (1..*): releases bundle measures, and review judges the bundle, not each cell alone.
  • `releaseCandidate` -> shapedBy -> `suppressionRule` (0..*): thin cells are suppressed, merged or coarsened before review.
  • `releaseCandidate` -> spends -> `noiseBudget` (0..1): noisy releases draw down the budget of their source.
  • `publishedSeries` -> releasedFrom -> `releaseCandidate` (1..*): a series is the accumulation of passed reviews over time.

Events

  • `cohortDefined`: a new population slice was defined and its membership counted.
  • `floorAdjusted`: a minimum cohort size was raised or lowered with recorded rationale.
  • `measureComputed`: a statistic was computed over a cohort inside the protected environment.
  • `cellSuppressed`: a thin cell was withheld or merged before release.
  • `budgetSpent`: a release drew down a noise budget, or a budget ran out and blocked further sensing for the period.
  • `reviewPassed`: a release candidate cleared disclosure review against floors and budgets.
  • `seriesPublished`: reviewed aggregates were released with method and provenance.

Projections

  • `publicStatistics`: published series only; omits cohorts under floor, suppressed cells and all member-level data.
  • `methodologySheet`: definitions, floors, suppression and noise methods per series; omits the values' underlying sources.
  • `budgetLedger`: budget allocation and spend per source and period; omits what the queries were about.