| ---
|
| license: unknown
|
| task_categories:
|
| - object-detection
|
| - image-segmentation
|
| tags:
|
| - pdf
|
| - document-layout-analysis
|
| - data-extraction
|
| language:
|
| - en
|
| - fr
|
| - es
|
| size_categories:
|
| - n<1K
|
| configs:
|
| - config_name: annotations
|
| data_files:
|
| - split: unhcr
|
| path: "annotations/unhcr/*.json"
|
| - split: prwp
|
| path: "annotations/prwp/*.json"
|
| - split: refugee
|
| path: "annotations/refugee/*.json"
|
| - config_name: metadata
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| data_files:
|
| - split: unhcr
|
| path: "metadata/unhcr/*.json"
|
| - split: prwp
|
| path: "metadata/prwp/*.json"
|
| - split: refugee
|
| path: "metadata/refugee/*.json"
|
| - config_name: documents
|
| data_files:
|
| - split: unhcr
|
| path: "documents/unhcr/*.pdf"
|
| - split: prwp
|
| path: "documents/prwp/*.pdf"
|
| - split: refugee
|
| path: "documents/refugee/*.pdf"
|
| - config_name: snapshots
|
| data_files:
|
| - split: unhcr
|
| path: "snapshots/unhcr/*.png"
|
| - split: prwp
|
| path: "snapshots/prwp/*.png"
|
| - split: refugee
|
| path: "snapshots/refugee/*.png"
|
| ---
|
|
|
| # Dataset card for data-snapshot
|
|
|
| ## Dataset summary
|
| The `data-snapshot` dataset is an annotated corpus designed for the evaluation and development of models for extracting *data snapshots* from PDF documents. A **data snapshot** is defined as a figure or table that contains quantitative data derived from statistics, indicators, or structured data sources.
|
|
|
| ## Dataset structure
|
|
|
| The repository is organized as follows:
|
|
|
| ```
|
| ai4data/data-snapshot/
|
| ├── annotations/<source>/*.json # Contains annotation files per document
|
| ├── documents/<source>/*.pdf # Actual PDFs
|
| ├── metadata/<source>/*.json # Document-level metadata
|
| ├── schemas/*.json # Provides the schema of the annotation and metadata files
|
| ├── snapshots/<source>/*.png # Image files corresponding to the annotations
|
| └── README.md
|
| ```
|
|
|
| ### Subsets
|
| - `annotations`
|
| - JSON files that indicate the data snapshots: their object class (Figure / Table) and bounding box locations (in normalized `[x1, y1, x2, y2]` format, top-left origin)
|
| - Follows the schema provided in `schemas/data-snapshot-eval-v1.3.schema.json`
|
| - Provided on a per-document basis; documents that do not have data snapshots will still have an annotation file present but list of bounding boxes will be empty.
|
| - `documents`
|
| - Actual PDF files that were annotated
|
| - `metadata`
|
| - Document-level metadata following the [World Bank Metadata Standards (Chapter 5 — Documents)](https://worldbank.github.io/schema-guide/chapter05.html), schema provided in `schemas/metadata_schema.json`.
|
| - Provided on a per-document basis
|
| - All files across all sources share a uniform schema (same keys at every nesting level)
|
| - `snapshots`
|
| - PNG files extracted from the documents and bounding box locations
|
|
|
| ### Sources
|
| - UNHCR
|
| - PRWP
|
| - Refugee
|
|
|
| ## Loading the dataset using HF's `datasets` library
|
|
|
| ### Annotations
|
|
|
| ```python
|
| >>> from datasets import load_dataset
|
| >>> annotations = load_dataset("ai4data/data-snapshot", name="annotations", split="unhcr")
|
| >>> annotations[0] # Inspect the first record
|
| {'label_map': {'1': 'Figure', '2': 'Table'}, 'info': {'schema_version': '1.3', 'type': 'ground_truth', 'created_at': datetime.datetime(2026, 5, 20, 13, 44, 29), 'run_id': 'human-annotation-combined-e3432dce89', 'model': {'name': 'human annotation'}, 'coordinate_system': {'type': 'normalized_xyxy', 'range': [0.0, 1.0], 'origin': 'top_left'}}, 'documents': [{'doc_id': '06072015-baalbek-hermelgovernorateprofile.pdf', 'doc_name': '06072015-baalbek-hermelgovernorateprofile.pdf', 'doc_path': 'pdf_input/06072015-baalbek-hermelgovernorateprofile.pdf'}], 'predictions': [{'page_id': '06072015-baalbek-hermelgovernorateprofile.pdf::p000', 'doc_id': '06072015-baalbek-hermelgovernorateprofile.pdf', 'page_index': 0, 'objects': [{'id': '1d69f693', 'label': 'Figure', 'bbox': [0.029415499554572243, 0.1766403810171256, 0.5954839424856321, 0.7354445202645015], 'score': None}, ...}
|
| ```
|
|
|
| ### Metadata
|
|
|
| ```python
|
| >>> metadata = load_dataset("ai4data/data-snapshot", name="metadata", split="unhcr")
|
| >>> metadata[0] # Inspect the first record
|
| {'type': 'document', 'metadata_information': {'title': 'Lebanon: Baalbek-Hermel Governorate Profile (June 2015)', 'idno': '06072015-baalbek-hermelgovernorateprofile', 'producers': [{'name': 'UNHCR', 'abbr': 'UNHCR', 'affiliation': 'UNHCR', 'role': 'Source'}], 'production_date': datetime.datetime(2026, 5, 21, 0, 0), ...}
|
| ```
|
|
|
| ### Documents
|
|
|
| ```python
|
| >>> docs = load_dataset("ai4data/data-snapshot", data_dir="documents/unhcr") # Or simply data_dir="documents/" for all files
|
| >>> docs.save_to_disk("path/to/docs_directory") # Files are saved as an Arrow file
|
| ```
|
|
|
| ### Snapshots
|
|
|
| ```python
|
| >>> snapshots = load_dataset("ai4data/data-snapshot", data_dir="snapshots/unhcr") # Or simply data_dir="snapshots/" for all snapshots
|
| >>> snapshots.save_to_disk("path/to/snapshots_directory") # Files are saved as an Arrow file
|
| ```
|
|
|
| ## Schema
|
|
|
| ### Annotations
|
|
|
| The annotation files follow the **Data Snapshot Evaluation Format (v1.3)**. Below is a simplified, human-readable example of the JSON schema with explanatory comments for each field.
|
|
|
| > **Note**: You will notice a top-level field called `predictions`. In the context of this dataset, this is a misnomer because these are actually human-labeled **annotations** (ground truth). We use the key `predictions` because we borrow this schema from the project's evaluation codebase, which uses a unified structure for both ground truth and model predictions.
|
|
|
| ```json
|
| {
|
| // Canonical mapping of integer IDs to class names
|
| "label_map": {
|
| "1": "Figure",
|
| "2": "Table"
|
| },
|
|
|
| // High-level metadata about the file
|
| "info": {
|
| "schema_version": "1.3",
|
| "type": "ground_truth", // Indicates these are human annotations
|
| "created_at": "2026-05-20T13:44:29",
|
| "run_id": "human-annotation-combined-e3432dce89",
|
| "model": {
|
| "name": "human annotation"
|
| },
|
| "coordinate_system": {
|
| "type": "normalized_xyxy",
|
| "range": [0.0, 1.0], // Bounding boxes are normalized between 0 and 1
|
| "origin": "top_left"
|
| }
|
| },
|
|
|
| // List of documents referenced in this file
|
| "documents": [
|
| {
|
| "doc_id": "1_advocacy_note_mineaction_-_niger_eng.pdf",
|
| "doc_name": "1_advocacy_note_mineaction_-_niger_eng.pdf",
|
| "doc_path": "pdf_input/1_advocacy_note_mineaction_-_niger_eng.pdf"
|
| }
|
| ],
|
|
|
| // Per-page container of objects; these contain the ground truth annotations
|
| "predictions": [
|
| {
|
| "page_id": "1_advocacy_note_mineaction_-_niger_eng.pdf::p001",
|
| "doc_id": "1_advocacy_note_mineaction_-_niger_eng.pdf",
|
| "page_index": 0, // 0-indexed page number
|
| "objects": [
|
| {
|
| "id": "obj_001",
|
| "label": "Figure", // Matches a label_map entry
|
| "bbox": [0.029, 0.177, 0.595, 0.735], // Normalized [x_min, y_min, x_max, y_max]
|
| "score": null // Always null for ground truth
|
| }
|
| ]
|
| }
|
| ]
|
| }
|
| ```
|
|
|
| ### Metadata
|
|
|
| The metadata files follow the [**World Bank Document Metadata Schema**](https://worldbank.github.io/schema-guide/chapter05.html). See `schemas/metadata_schema.json` for the formal JSON schema definition.
|
|
|
| All metadata files across all sources share a uniform schema (same keys at every nesting level, same types) to ensure compatibility with Apache Arrow and HuggingFace streaming.
|
|
|
| Top-level fields:
|
| - `type`
|
| - `metadata_information`
|
| - `document_description`
|
| - `provenance`
|
| - `tags`
|
| - `schematype`
|
| - `additional` - contains source-specific fields (e.g. `additional.unhcr_*` for UNHCR, `additional.wds_*` for WDS API-sourced datasets).
|
|
|
| ## Dataset creation
|
| The annotations were produced through human labeling using Label Studio.
|
|
|
| ## Licensing information
|
| [TBD]
|
|
|
| ## Citation information
|
| [TBD]
|
|
|
