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| dido:01-fdis-ra:02-background-and-motivation:02-4-existing-functional-capabilities-in-reporting-systems:02-4-5-rules-and-validation:start [2026/07/12 12:27] – created nick_dido | dido:01-fdis-ra:02-background-and-motivation:02-4-existing-functional-capabilities-in-reporting-systems:02-4-5-rules-and-validation:start [2026/07/18 12:33] (current) – external edit 127.0.0.1 |
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| [[dido:01-fdis-ra:02-background-and-motivation:02-4-existing-functional-capabilities-in-reporting-systems:start|Return to 2.4 Existing Functional Capabilities in Reporting Systems]] | [[dido:01-fdis-ra:02-background-and-motivation:02-4-existing-functional-capabilities-in-reporting-systems:start|Return to 2.4 Existing Functional Capabilities in Reporting Systems]] |
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| Although the functional capabilities described in [[dido:01-fdis-ra:02-background-and-motivation:02-4-existing-functional-capabilities-in-reporting-systems:02-4-1-source-artifact-persistence:start|Section 2.4.1]] through [[dido:01-fdis-ra:02-background-and-motivation:02-4-existing-functional-capabilities-in-reporting-systems:02-4-5-rules-and-validation:start|Section 2.4.5]] are widely deployed in modern reporting systems, organisations typically assemble them through ad hoc, tool-driven, or implementation-specific arrangements. | Although the functional capabilities described in [[dido:01-fdis-ra:02-background-and-motivation:02-4-existing-functional-capabilities-in-reporting-systems:02-4-1-source-artifact-persistence:start|Section 2.4.1]] through [[dido:01-fdis-ra:02-background-and-motivation:02-4-existing-functional-capabilities-in-reporting-systems:02-4-5-rules-and-validation:start|Section 2.4.5]] are widely deployed in modern reporting systems, organizations typically assemble them through ad hoc, tool-driven, or implementation-specific arrangements. |
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| Architectural decisions concerning how evidence, observations, [[dido:99_annexes:annex-b-terms-and-definitions:s:semantic|semantic]] representations, rule execution, and validation outcomes relate to one another often remain implicit. Software implementations, analytical pipelines, configuration conventions, and organisational practices embed these decisions without making the governing relationships, authorities, versions, or assumptions explicit. | Architectural decisions concerning how evidence, observations, [[dido:99_annexes:annex-b-terms-and-definitions:s:semantic|semantic]] representations, rule execution, and validation outcomes relate to one another often remain implicit. Software implementations, analytical pipelines, configuration conventions, and organizational practices embed these decisions without making the governing relationships, authorities, versions, or assumptions explicit. |
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| As a result, reporting systems exhibit recurring architectural failure modes: | As a result, reporting systems exhibit recurring architectural failure modes: |
| * Semantics remain distributed across tools, systems, analytical logic, configurations, and codebases rather than governed as explicit, versioned assets | * Semantics remain distributed across tools, systems, analytical logic, configurations, and codebases rather than governed as explicit, versioned assets |
| * Systems blur or lose the distinctions among reported, observed, and interpreted facts | * Systems blur or lose the distinctions among reported, observed, and interpreted facts |
| * Organisations cannot assess changes to definitions, rules, or interpretive guidance consistently across implementations | * Organizations cannot assess changes to definitions, rules, or interpretive guidance consistently across implementations |
| * Comparability across agencies, jurisdictions, reporting periods, and independently developed systems degrades over time, even when systems share syntactic standards | * Comparability across agencies, jurisdictions, reporting periods, and independently developed systems degrades over time, even when systems share syntactic standards |
| * Artificial intelligence-assisted extraction and interpretation introduce additional opacity when architectural controls do not constrain their authority, inputs, outputs, provenance, and use | * Artificial intelligence-assisted extraction and interpretation introduce additional opacity when architectural controls do not constrain their authority, inputs, outputs, provenance, and use |
| Such systems may operate effectively in isolation while remaining fragile, opaque, and difficult to govern as an integrated interpretation environment. | Such systems may operate effectively in isolation while remaining fragile, opaque, and difficult to govern as an integrated interpretation environment. |
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| The [[dido:99_annexes:annex-b-terms-and-definitions:f:fdis_ra|Federated Data Interpretation Systems Reference Architecture (FDIS-RA)]] addresses this gap by making architectural responsibilities explicit rather than by replacing existing tools, standards, products, or implementations. | The [[dido:99_annexes:annex-b-terms-and-definitions:f:fdis-ra|Federated Data Interpretation Systems Reference Architecture (FDIS-RA)]] addresses this gap by making architectural responsibilities explicit rather than by replacing existing tools, standards, products, or implementations. |
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| FDIS-RA: | FDIS-RA: |
| * Establishes explicit boundaries and interface obligations | * Establishes explicit boundaries and interface obligations |
| * Treats semantic interpretation as a first-class, governable architectural concern | * Treats semantic interpretation as a first-class, governable architectural concern |
| * Preserves traceability among source artefacts, observations, interpretations, rules, and outcomes | * Preserves traceability among source artifacts, observations, interpretations, rules, and outcomes |
| * Supports controlled evolution of semantic and interpretive assets | * Supports controlled evolution of semantic and interpretive assets |
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| * Controlled semantic evolution | * Controlled semantic evolution |
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| These characteristics determine whether system behaviour remains explainable, comparable, inspectable, and auditable as requirements, standards, technologies, tools, organisational responsibilities, and analytical techniques evolve. | These characteristics determine whether system behavior remains explainable, comparable, inspectable, and auditable as requirements, standards, technologies, tools, organizational responsibilities, and analytical techniques evolve. |
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| Many systems that support agency-specific implementation of the FDTA joint data standards operate in mission-critical or high-consequence contexts. In such environments, failures of semantic interpretation, traceability, reproducibility, or governance are not merely technical deficiencies. They may produce material regulatory, financial, legal, operational, or systemic consequences. | Many systems that support agency-specific implementation of the FDTA joint data standards operate in mission-critical or high-consequence contexts. In such environments, failures of semantic interpretation, traceability, reproducibility, or governance are not merely technical deficiencies. They may produce material regulatory, financial, legal, operational, or systemic consequences. |