Published

Time Series / Observation Collection

vr.wm-dat-010 · wm-dat-010-time-series-observation-collection

Represent one governed, versioned collection of ordered observations so agents can interpret values, dimensions, time, vintages, quality and provenance without confusing a series definition, individual observation, release or forecast.

World Models Information and virtual systems INF.DAT.TS

Bundle → Layer → Finding → Questions Classifiers What it is Why it exists Distinguishing features What robots and AI may and may not do Moral aspects Owners Links to other meta-models Identity and identifiers Direct properties Recognition Capabilities and actions Hazards and failure modes Standards and interfaces Context of use Sources

Bundle → Layer → Finding → Questions Filled

6 bundles · 12 layers · 24 findings · 72 questions

Series identity, semantics and dimensional structure Groups governed collection context for series identity, semantics and dimensional structure.

Collection and series identity, version and authority

Groups source-qualified time-series context for collection and series identity, version and authority.

Collection, series ID, version, head, status, owner and purpose

Records collection, series id, version, head, status, owner and purpose as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish collection, series id, version, head, status, owner and purpose? identity
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use collection, series id, version, head, status, owner and purpose, for which purpose and under what authority? authority
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify collection, series id, version, head, status, owner and purpose? security

Series key, boundary, membership profile and compatibility

Records series key, boundary, membership profile and compatibility as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish series key, boundary, membership profile and compatibility? constraint
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use series key, boundary, membership profile and compatibility, for which purpose and under what authority? requirement
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify series key, boundary, membership profile and compatibility? privacy

Variable, measure, unit, dimensions and classifications

Groups source-qualified time-series context for variable, measure, unit, dimensions and classifications.

Variable, indicator, observed property, measure, unit, scale and datatype

Records variable, indicator, observed property, measure, unit, scale and datatype as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish variable, indicator, observed property, measure, unit, scale and datatype? measurement
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use variable, indicator, observed property, measure, unit, scale and datatype, for which purpose and under what authority? constraint
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify variable, indicator, observed property, measure, unit, scale and datatype? retention

Dimension, key, coordinate, classification, code list and concept

Records dimension, key, coordinate, classification, code list and concept as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish dimension, key, coordinate, classification, code list and concept? classification
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use dimension, key, coordinate, classification, code list and concept, for which purpose and under what authority? process
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify dimension, key, coordinate, classification, code list and concept? access

Observation membership, values and states Groups governed collection context for observation membership, values and states.

Observation identity, membership, order and integrity

Groups source-qualified time-series context for observation identity, membership, order and integrity.

Observation ID, series membership, dimension key and order

Records observation id, series membership, dimension key and order as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish observation id, series membership, dimension key and order? composition
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use observation id, series membership, dimension key and order, for which purpose and under what authority? event
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify observation id, series membership, dimension key and order? exception

Collection cardinality, completeness, duplicate, gap and overlap

Records collection cardinality, completeness, duplicate, gap and overlap as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish collection cardinality, completeness, duplicate, gap and overlap? validation
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use collection cardinality, completeness, duplicate, gap and overlap, for which purpose and under what authority? measurement
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify collection cardinality, completeness, duplicate, gap and overlap? interoperability

Result value, status, flags and missingness

Groups source-qualified time-series context for result value, status, flags and missingness.

Result value, type, unit, precision, resolution, range and component

Records result value, type, unit, precision, resolution, range and component as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish result value, type, unit, precision, resolution, range and component? measurement
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use result value, type, unit, precision, resolution, range and component, for which purpose and under what authority? evidence
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify result value, type, unit, precision, resolution, range and component? decision

Status, flag, missing, not applicable, suppressed, confidential and provisional

Records status, flag, missing, not applicable, suppressed, confidential and provisional as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish status, flag, missing, not applicable, suppressed, confidential and provisional? state
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use status, flag, missing, not applicable, suppressed, confidential and provisional, for which purpose and under what authority? quality
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify status, flag, missing, not applicable, suppressed, confidential and provisional? identity

Temporal semantics, frequency, calendars and vintages Groups governed collection context for temporal semantics, frequency, calendars and vintages.

Reference, phenomenon, validity period and calendar

Groups source-qualified time-series context for reference, phenomenon, validity period and calendar.

Phenomenon, reference, effective, validity, instant, interval and bounds

Records phenomenon, reference, effective, validity, instant, interval and bounds as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish phenomenon, reference, effective, validity, instant, interval and bounds? temporal
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use phenomenon, reference, effective, validity, instant, interval and bounds, for which purpose and under what authority? validation
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify phenomenon, reference, effective, validity, instant, interval and bounds? classification

Frequency, periodicity, cadence, calendar, time zone, offset and precision

Records frequency, periodicity, cadence, calendar, time zone, offset and precision as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish frequency, periodicity, cadence, calendar, time zone, offset and precision? temporal
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use frequency, periodicity, cadence, calendar, time zone, offset and precision, for which purpose and under what authority? security
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify frequency, periodicity, cadence, calendar, time zone, offset and precision? composition

Result, availability, release, revision, vintage and knowledge time

Groups source-qualified time-series context for result, availability, release, revision, vintage and knowledge time.

Result, issued, available, release, embargo and publication time

Records result, issued, available, release, embargo and publication time as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish result, issued, available, release, embargo and publication time? temporal
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use result, issued, available, release, embargo and publication time, for which purpose and under what authority? privacy
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify result, issued, available, release, embargo and publication time? relationship

Revision, vintage, recorded, ingestion, transaction and knowledge time

Records revision, vintage, recorded, ingestion, transaction and knowledge time as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish revision, vintage, recorded, ingestion, transaction and knowledge time? provenance
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use revision, vintage, recorded, ingestion, transaction and knowledge time, for which purpose and under what authority? retention
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify revision, vintage, recorded, ingestion, transaction and knowledge time? state

Coverage, sampling, transformations and forecast qualifiers Groups governed collection context for coverage, sampling, transformations and forecast qualifiers.

Feature, population, space, sample and granularity

Groups source-qualified time-series context for feature, population, space, sample and granularity.

Feature of interest, population, domain, spatial and thematic coverage

Records feature of interest, population, domain, spatial and thematic coverage as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish feature of interest, population, domain, spatial and thematic coverage? relationship
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use feature of interest, population, domain, spatial and thematic coverage, for which purpose and under what authority? access
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify feature of interest, population, domain, spatial and thematic coverage? lifecycle

Sample frame, specimen, sampling method, cadence, granularity and weight

Records sample frame, specimen, sampling method, cadence, granularity and weight as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish sample frame, specimen, sampling method, cadence, granularity and weight? measurement
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use sample frame, specimen, sampling method, cadence, granularity and weight, for which purpose and under what authority? exception
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify sample frame, specimen, sampling method, cadence, granularity and weight? temporal

Aggregation, transformation, adjustment, forecast and scenario

Groups source-qualified time-series context for aggregation, transformation, adjustment, forecast and scenario.

Aggregation, weighting, index base, normalization, seasonal adjustment and chain

Records aggregation, weighting, index base, normalization, seasonal adjustment and chain as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish aggregation, weighting, index base, normalization, seasonal adjustment and chain? process
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use aggregation, weighting, index base, normalization, seasonal adjustment and chain, for which purpose and under what authority? interoperability
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify aggregation, weighting, index base, normalization, seasonal adjustment and chain? provenance

Observed, estimated, nowcast, forecast, scenario, horizon, quantile and confidence

Records observed, estimated, nowcast, forecast, scenario, horizon, quantile and confidence as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish observed, estimated, nowcast, forecast, scenario, horizon, quantile and confidence? classification
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use observed, estimated, nowcast, forecast, scenario, horizon, quantile and confidence, for which purpose and under what authority? decision
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify observed, estimated, nowcast, forecast, scenario, horizon, quantile and confidence? ownership

Source, provenance, quality and revision Groups governed collection context for source, provenance, quality and revision.

Source, procedure, sensor, run and lineage

Groups source-qualified time-series context for source, procedure, sensor, run and lineage.

Source dataset, API, sensor, device, procedure, method and feature binding

Records source dataset, api, sensor, device, procedure, method and feature binding as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish source dataset, api, sensor, device, procedure, method and feature binding? provenance
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use source dataset, api, sensor, device, procedure, method and feature binding, for which purpose and under what authority? identity
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify source dataset, api, sensor, device, procedure, method and feature binding? authority

Collection, processing run, software, operator, input, output and lineage

Records collection, processing run, software, operator, input, output and lineage as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish collection, processing run, software, operator, input, output and lineage? provenance
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use collection, processing run, software, operator, input, output and lineage, for which purpose and under what authority? classification
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify collection, processing run, software, operator, input, output and lineage? requirement

Validation, quality, uncertainty, anomaly and correction

Groups source-qualified time-series context for validation, quality, uncertainty, anomaly and correction.

Validation rule, quality dimension, metric, uncertainty, confidence, anomaly and outlier

Records validation rule, quality dimension, metric, uncertainty, confidence, anomaly and outlier as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish validation rule, quality dimension, metric, uncertainty, confidence, anomaly and outlier? quality
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use validation rule, quality dimension, metric, uncertainty, confidence, anomaly and outlier, for which purpose and under what authority? composition
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify validation rule, quality dimension, metric, uncertainty, confidence, anomaly and outlier? constraint

Revision, correction, benchmark, restatement, backcast, retraction and supersession

Records revision, correction, benchmark, restatement, backcast, retraction and supersession as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish revision, correction, benchmark, restatement, backcast, retraction and supersession? lifecycle
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use revision, correction, benchmark, restatement, backcast, retraction and supersession, for which purpose and under what authority? relationship
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify revision, correction, benchmark, restatement, backcast, retraction and supersession? process

Lifecycle, access, distribution and interoperability Groups governed collection context for lifecycle, access, distribution and interoperability.

Lifecycle, release, access, rights and records

Groups source-qualified time-series context for lifecycle, release, access, rights and records.

Draft, validated, released, superseded, withdrawn and data availability

Records draft, validated, released, superseded, withdrawn and data availability as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish draft, validated, released, superseded, withdrawn and data availability? lifecycle
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use draft, validated, released, superseded, withdrawn and data availability, for which purpose and under what authority? state
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify draft, validated, released, superseded, withdrawn and data availability? event

Access, privacy, license, embargo, retention, legal hold, tombstone and audit

Records access, privacy, license, embargo, retention, legal hold, tombstone and audit as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish access, privacy, license, embargo, retention, legal hold, tombstone and audit? access
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use access, privacy, license, embargo, retention, legal hold, tombstone and audit, for which purpose and under what authority? lifecycle
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify access, privacy, license, embargo, retention, legal hold, tombstone and audit? measurement

Distribution, API, packaging, integrity and projections

Groups source-qualified time-series context for distribution, api, packaging, integrity and projections.

Distribution, format, media type, API, query, pagination, chunk, compression and checksum

Records distribution, format, media type, api, query, pagination, chunk, compression and checksum as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish distribution, format, media type, api, query, pagination, chunk, compression and checksum? interoperability
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use distribution, format, media type, api, query, pagination, chunk, compression and checksum, for which purpose and under what authority? temporal
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify distribution, format, media type, api, query, pagination, chunk, compression and checksum? evidence

SDMX, OMS, SSN, Data Cube, Time, PROV, DQV, DCAT, CSVW, GSIM, RFC, ISO, DataCite, CF and FHIR projection

Records sdmx, oms, ssn, data cube, time, prov, dqv, dcat, csvw, gsim, rfc, iso, datacite, cf and fhir projection as source-qualified collection context while observation, sensor, procedure, feature, statistical unit, source dataset, processing run, release and records masters remain independently identifiable.

What stable identity, version, typed value, dimensions, unit, scope and explicit unknown establish sdmx, oms, ssn, data cube, time, prov, dqv, dcat, csvw, gsim, rfc, iso, datacite, cf and fhir projection? interoperability
Who owns, observes, supplies, transforms, asserts, reviews, approves or may use sdmx, oms, ssn, data cube, time, prov, dqv, dcat, csvw, gsim, rfc, iso, datacite, cf and fhir projection, for which purpose and under what authority? provenance
Which phenomenon, reference, result, availability, release, revision, recorded, ingestion and knowledge times, evidence and uncertainty qualify sdmx, oms, ssn, data cube, time, prov, dqv, dcat, csvw, gsim, rfc, iso, datacite, cf and fhir projection? quality

Classifiers Filled

Family: World Models
Category: Information and virtual systems
Entry kind: aggregate
Navigation path: NAV.INF.DAT.TS
Domain: INF.DAT.TS
Industry: Cross-industry
Tags: timeseriesobservationcollectioninf.dat.ts

What it is Filled

Owns collection and series identity, versions, keys and lifecycle; variable, indicator, measure, unit, dimension and classification bindings; observation membership and order; qualified values, components, status, flags and missingness; phenomenon, reference, validity, result, availability, release, revision, recorded, ingestion and knowledge times; frequency, calendars and time zones; coverage, sampling and granularity; transformations, adjustments, forecasts and uncertainty; source, procedure, sensor, processing and lineage bindings; validation, quality, anomaly, correction and restatement evidence; access, retention, distribution and interoperability projections. External variable, sensor, procedure, feature, statistical unit, source dataset, processing run, release, audit and records masters remain independently authoritative.

In scope

Collection and series identity, structure, dimensions, variables, measures, units, observations, order, values, flags, missingness and multi-time semantics
Vintages, coverage, sampling, transformations, forecasts, provenance, quality, corrections, lifecycle, access, distributions and interoperability projections

Out of scope

Owning Variable, Classification, Unit, Sensor, Procedure, Feature of Interest, Statistical Unit, Population, Source Dataset, Processing Run, Release, Audit or Records masters
Treating an observation assertion as timeless ground truth or collapsing observed, estimated, imputed, adjusted, forecast and scenario values
Autonomous ingestion, imputation, recalculation, revision, suppression, publication, certification, unit change, access widening or physical records disposition

Why it exists Filled

Distinguishing features Filled

An ordered, versioned collection of observations with series keys, not a single observation.
Keeps observed, estimated, imputed, adjusted, forecast and scenario values distinguishable.
Tracks vintages and revisions so past releases can be reproduced.
Differs from the sensor or procedure that produced the values.

What robots and AI may and may not do Filled

Must not

Impute, revise, suppress or publish values without delegation.
Change units or time semantics silently.
Mix forecast or modelled values with observations without flags.
Overwrite a released vintage.
Certify a series.

Only with a human decision

Releasing or revising official series.
Suppressing values for confidentiality.
Changing methods or base periods.

May

Append observations with unit, time and status qualifiers.
Validate order, gaps and duplicates.
Compute derived series under declared methods.
Answer queries for a series as of a given vintage.

Moral aspects Filled

Small-area or individual-level series can reveal people and need disclosure control.
Official statistics drive public policy, so revisions must be transparent.
Health and environmental series affect public safety decisions.

Who is affected

People and units described by the data
Public and policy users
Data providers and statistical agencies

Owners Filled

Steward

Dimension owner, namespace authority, data governance mandate and accountable series owner

Roles

Series owner: Own purpose, scope, series definitions, lifecycle, compatibility and accountable use.
Data steward: Own identifiers, dimensions, variables, units, classifications, missing states and metadata quality.
Method and measurement owner: Own sampling, sensor, procedure, transformation, adjustment, forecast and uncertainty semantics.
Source and pipeline custodian: Own source bindings, processing runs, lineage, ingestion evidence, checksums and operational controls.
Quality reviewer: Own validation rules, quality metrics, anomaly review, limitations, corrections and certification decisions.
Access, privacy and records authority: Own purpose, confidentiality, access, license, embargo, retention, legal hold and disposition policy.
Publication and interoperability steward: Own releases, withdrawals, distributions, APIs, projection versions, declared loss and auditability.

Links to other meta-models Filled

references

WM-MAT-008 - Represent the unfrozen matrix or tabular context without approved ownership, mutation or cascade authority.
Variable, Classification, Code List and Unit models - Resolve independently governed observation meaning, dimensions and units.
Observation, Sensor, Procedure, Feature, Statistical Unit, Population and Source Dataset models - Resolve authoritative observations, producers, subjects, populations and sources without absorbing their lifecycles.
Processing Run, Release, Audit and Records models - Resolve derivation, operational publication, audit and disposition authorities.

aligned

SDMX 3.1, OMS 3.0, SSN 2023, RDF Data Cube, OWL-Time, PROV-O, DQV, DCAT 3, CSVW, GSIM 2.0, RFC 3339, ISO 8601-1:2019, DataCite 4.7, CF 1.13 and FHIR R5 - Project version-pinned statistical, observation, sensor, linked-data, temporal, provenance, quality, catalog, tabular, citation, scientific and health views with declared loss.

neighbor

WM-MAT-008 parent signal - The unfrozen parent signal may identify a matrix or tabular context, but no approved relation row exists and it grants no ownership, mutation or cascade authority.
Series definition, observation collection and observation - The definition fixes meaning and key space, the collection governs membership and versions, and each observation is a separately qualified assertion.
Sensor, procedure, feature, statistical unit, source dataset and processing run - These external masters explain what produced or is described by values; the collection stores non-owning references and lineage only.
Release, vintage, revision and distribution - Release and availability decisions, knowledge vintages, correction lineage and transport packages are distinct from the semantic collection head.
SDMX, OMS, SSN, RDF Data Cube, OWL-Time, PROV, DQV, DCAT, CSVW, GSIM, RFC 3339, ISO 8601, DataCite, CF and FHIR profiles - Each source has a distinct scope and normative force. Every mapping is version-pinned, profile-qualified and loss-declaring.

parent

WM-MAT-008

What else AI and robots need to interact with it Filled

Sources Filled

SDMX Technical Specifications - SDMX
Observations, measurements and samples - Open Geospatial Consortium
Semantic Sensor Network Ontology 2023 Edition - World Wide Web Consortium
The RDF Data Cube Vocabulary - World Wide Web Consortium
Time Ontology in OWL - World Wide Web Consortium and Open Geospatial Consortium
PROV-O: The PROV Ontology - World Wide Web Consortium
Data on the Web Best Practices: Data Quality Vocabulary - World Wide Web Consortium
Data Catalog Vocabulary DCAT Version 3 - World Wide Web Consortium
Model for Tabular Data and Metadata on the Web - World Wide Web Consortium
Generic Statistical Information Model version 2.0 User Guide - United Nations Economic Commission for Europe
Date and Time on the Internet: Timestamps - Internet Engineering Task Force
Date and time - Representations for information interchange - Part 1 - International Organization for Standardization
DataCite Metadata Schema - DataCite
NetCDF Climate and Forecast Metadata Conventions - CF Conventions Committee
Observation - FHIR R5 - Health Level Seven International

Open questions

Approve or reject the WM-MAT-008 relation and register Variable, Unit, Observation, Sensor, Procedure, Feature, Statistical Unit, Population, Source Dataset, Processing Run, Release, Audit and Records edges.
Create financial ticks, industrial telemetry, climate-grid, clinical observation, event-sourcing, stream-processing and jurisdiction-specific statistical profiles.
Conformance-test series keys, calendars, time axes, missing states, vintages, transformations, forecasts, quality flags and distributions against concrete engines and datasets.
Validate organization-specific ingestion, disclosure control, publication, certification, legal hold, retention and disposition policies.
Inspect licensed ISO requirements under authorized access before making clause-level conformance claims.
Obtain independent external review before promoting beyond reviewable-draft assurance.
Claude and Grok each timed out on one bounded attempt; no independent external result was admitted.
No relation row is frozen; the WM-MAT-008 parent signal grants no approved ownership or cascade behavior.
Financial market ticks, industrial telemetry, climate grids, clinical observations, event sourcing, streaming systems and jurisdiction-specific statistics require separate profiles.
ISO 8601-1:2019 is used only from public scope and lifecycle metadata; access-restricted requirements were not inferred.
SSN ObservationCollection is identified by its 2023 Edition text as non-normative pending implementation experience and is treated as an alignment profile, not sole canon.

Machine files

Card as JSON Specification AGENTS.md Source Card backlog vercy.card/1

Provenance

world-models research · reviewable-draft

Built from: models/wm-dat-010-time-series-observation-collection/spec.yaml, ver-cy/world-models/card-supplements/wm-dat-010-time-series-observation-collection.json