epam · iliia-veselov · Jul 1, 2026
@@ -15,6 +15,7 @@ design, services, tools, and integration requirements.
 | **[🔎 Data Query & Hybrid Search](./data-query-hybrid-search.md)** | How NL queries become grounded SDMX data, and how hybrid indicator search works (conceptual) | • Composite indicators<br>• Keyword + semantic + LLM<br>• Two-phase indexing<br>• Availability grounding |
 | **[🔌 Application MCP](./mcp.md)**                   | Agentic access via Model Context Protocol                 | • Channel tools surfaced to AI agents<br>• DIAL Application registration<br>• MCP-spec discovery + IDP OAuth flow      |
 | **[📊 SDMX Compatibility](./sdmx-compatibility.md)** | SDMX standards and requirements guide                     | • Version support (2.1/3.0)<br>• Metadata requirements<br>• Performance standards<br>• Quality checklist               |
+| **[📐 SDMX Data Models](./sdmx-data-models.md)**     | SDMX data-model patterns and which StatGPT supports       | • Conventional (supported)<br>• Shared DSD<br>• Indicator-per-dataflow<br>• Why indicator search fits one model |
 
 ### Design Documentation/res
 

@@ -34,6 +34,18 @@ effectively with statistical data sources.
 - ✅ Available Constraint endpoint
 - ✅ Data endpoint
 
+## 📐 Supported Data Models
+
+StatGPT is an indicator-search-based system and supports only the **conventional
+(multi-indicator dataflow)** data model. Providers whose indicator is encoded by *which
+dataflow (or table)* you pick — the **shared DSD** (e.g. OECD) and **indicator-per-dataflow /
+dedicated-DSD-per-dataset** (e.g. Eurostat, ISTAT, ABS, ILO) models — are **not supported yet**.
+
+The three data models, their example providers, and why StatGPT supports one of them are
+described in a dedicated document:
+
+➡️ **[SDMX Data Models & StatGPT Support](./sdmx-data-models.md)**
+
 ## 🌐 Connectivity Requirements
 
 ### API Availability
@@ -179,6 +191,7 @@ Use this checklist to ensure your SDMX metadata meets StatGPT requirements:
 5. **Missing Concept Definitions**: Reduces context understanding
 6. **Slow API Response Times**: Degrades user experience
 7. **Authentication Complexity**: Currently not supported by StatGPT
+8. **Unsupported Data Model**: Only the conventional multi-indicator dataflow model is supported — see [Supported Data Models](#-supported-data-models) and [SDMX Data Models & StatGPT Support](./sdmx-data-models.md)
 
 ## 💡 Recommendations for Data Providers
 

@@ -0,0 +1,111 @@
+# SDMX Data Models & StatGPT Support
+
+This document describes the SDMX data-model patterns StatGPT encounters across providers and
+which of them StatGPT supports. It complements the [SDMX Compatibility](./sdmx-compatibility.md)
+requirements.
+
+## Overview
+
+Across SDMX providers there are three data models. StatGPT supports only the **conventional
+(multi-indicator dataflow)** model — where the indicator is a dimension inside one broad
+dataflow, which is what StatGPT's indicator search resolves and filters within (see
+[Data Query & Hybrid Search](./data-query-hybrid-search.md)). The **shared DSD** and
+**indicator-per-dataflow** models — where the indicator is instead encoded by *which dataflow
+(or table)* you pick — are **not supported yet**.
+
+| # | Data model | Indicator is selected by… | Example providers | Supported |
+|---|------------|---------------------------|-------------------|:---------:|
+| 1 | **Conventional (multi-indicator dataflow)** | a dimension *inside* one broad dataflow | IMF, BIS | ✅ Yes |
+| 2 | **Shared DSD** | *which dataflow* (one DSD split across many per-country / per-table dataflows) | OECD | ❌ Not yet |
+| 3 | **Indicator-per-dataflow (dedicated DSD per dataset)** | *which dataflow* (one narrow table = one DSD) | Eurostat, ISTAT, ABS, ILO | ❌ Not yet |
+
+---
+
+## 1. Conventional (multi-indicator dataflow) — ✅ Supported
+
+A dataset is a **single broad dataflow that holds many indicators**.
+
+**Shape:**
+
+- A relatively small number of dataflows.
+- Each dataflow exposes a broad indicator/measure dimension whose code list holds the
+  individual indicators.
+- One DSD may back one or several such broad dataflows.
+
+**Examples:** IMF, BIS.
+
+**Why it works:** the indicator index is populated from the codes on the broad indicator
+dimension, and query resolution is a filter *within* a dataflow — exactly the flow StatGPT
+implements.
+
+---
+
+## 2. Shared DSD — ❌ Not supported yet
+
+One rich DSD is **deliberately partitioned into many semantically-distinct dataflows** —
+typically one dataflow per country or per sub-table. The DSD is shared; the dataflows are
+narrow slices of it.
+
+**Shape:**
+
+- One DSD backs many dataflows (mean dataflows-per-DSD well above 1); a large share of
+  dataflows ride a shared DSD.
+- Each dataflow is a narrow slice of the shared structure — typically one country or one
+  sub-table — not a broad indicator dataflow.
+
+**Example: OECD**
+
+- ~1,536 dataflows over ~413 distinct DSDs (mean ≈ 3.65 dataflows per DSD); ~82% of dataflows
+  ride a shared DSD.
+- Naming encodes the DSD in every dataflow id: `DSD_<name>@DF_<name>` (~96% of dataflows).
+- The sharing is almost always one structure split by country or sub-table:
+
+| DSD | # dataflows | Example dataflows |
+|-----|-------------|-------------------|
+| `OECD.TAD.ADM:DSD_FFS` (fossil-fuel support) | 53 | `DSD_FFS@DF_FFS_ARG`, `…_ARM`, `…_AUS` (per country) |
+| `OECD.CTP.TPS:DSD_REV_OECD` (tax revenue) | 39 | `DSD_REV_OECD@DF_REVAUS`, `…_AUT`, … (per country) |
+| `OECD.SDD.NAD:DSD_NAMAIN10` (national accounts) | 35 | `DSD_NAMAIN10@DF_TABLE1`, `…_EXPENDITURE`, … (per table) |
+
+---
+
+## 3. Indicator-per-dataflow (dedicated DSD per dataset) — ❌ Not supported yet
+
+Each dataset is **one narrow table — effectively one indicator — published as its own
+dataflow with its own dedicated DSD**, producing thousands of dataflows. The indicator is
+determined by *which* dataflow is chosen, not by a dimension within one.
+
+**Shape:**
+
+- Thousands of dataflows, each with its own dedicated DSD — a near-1:1 dataflow-to-DSD ratio,
+  often with `dataflow-id == DSD-id`.
+- Each dataflow is a narrow table; there is no broad indicator dataflow to select and filter.
+- The dataset-specific axis is usually a domain indicator dimension that is not consistent
+  across datasets.
+
+**Example: Eurostat**
+
+- ~8,245 dataflows over ~7,698 distinct DSDs, in near-perfect 1:1 — ~100% of base datasets
+  have `dataflow-id == DSD-id` (e.g. dataflow `NAMA_10_GDP` → DSD `NAMA_10_GDP`).
+- The one genuinely dataset-specific axis is a domain indicator dimension (`na_item`,
+  `indic_is`, `indic_bt`, …), which is not consistent across datasets.
+- Plus ~547 `$DV_` "data-view" dataflows (pre-saved filtered views) that reference their
+  parent dataset's DSD (e.g. `ISOC_CI_AC_I$DV_1043`).
+
+**Other providers with this model:**
+
+| Provider | Shape |
+|----------|-------|
+| **Eurostat** | ~8,245 dataflows, one dedicated DSD per dataset (`dataflow-id == DSD-id`), + `$DV_` views |
+| **ISTAT** | ~810 real datasets, one DSD each, but ~78% of its ~4,876 dataflows are `_DF_..._N` saved-view variants of a parent dataset |
+| **ABS** | ~1,223 dataflows, dedicated DSD ~1:1 (`dataflow-id == DSD-id`) |
+| **ILO** | ~1,208 dataflows ↔ 1,208 DSDs, strict 1:1 (`DF_<X>` → DSD `<X>`) |
+
+---
+
+## Summary
+
+| Data model | Example providers | Supported |
+|------------|-------------------|:---------:|
+| Conventional (multi-indicator dataflow) | IMF, BIS | ✅ |
+| Shared DSD | OECD | ❌ |
+| Indicator-per-dataflow (dedicated DSD per dataset) | Eurostat, ISTAT, ABS, ILO | ❌ |