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--- |
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language: |
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- en |
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tags: |
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- climate |
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- policy |
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- legal |
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size_categories: |
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- 1M<n<10M |
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--- |
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# Global Stocktake Open Data |
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This repo contains the data for the first [UNFCCC Global Stocktake](https://unfccc.int/topics/global-stocktake). The data consists of document metadata from sources relevant to the Global Stocktake process, as well as full text parsed from the majority of the documents. |
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The files in this dataset are as follows: |
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- `metadata.csv`: a CSV containing document metadata for each document we have collected. **This metadata may not be the same as what's stored in the source databases** – we have cleaned and added metadata where it's corrupted or missing. |
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- `full_text.parquet`: a parquet file containing the full text of each document we have parsed. Each row is a text block (paragraph) with all the associated text block and document metadata. |
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The last refresh of the data was on **2023-05-17**. |
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A research tool you can use to view this data and the results of some classifiers run on it is at [gst1.org](https://gst1.org). |
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**[View our methodology](https://labs.climatepolicyradar.org/global-stocktake/)**. |
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**Contents** |
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- [Field descriptions](#field-descriptions) |
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- [Known issues](#known-issues) |
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- [Usage in Python](#usage-in-python) |
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- [Loading metadata CSV](#loading-metadata-csv) |
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- [Loading text block data](#loading-text-block-data) |
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--- |
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## Field descriptions |
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- `author`: document author (str) |
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- `author_is_party`: whether the author is a Party (national government) or not (bool) |
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- `block_index`: the index of a text block in a document. Starts from 0 (int) |
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- `coords`: coordinates of the text block on the page |
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- `date`: publication date of the document |
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- `document_content_type`: file type. We have only parsed text from PDFs. |
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- `document_id`: unique identifier for a document |
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- `document_md5_sum`: md5sum of the document's content |
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- `document_name`: document title |
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- `document_source_url`: URL for document |
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- `document_variant`: used to identify translations. In `[nan, 'Translation', 'Original Language']` |
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- `has_valid_text`: our heuristic about whether text is valid or not in the document based on the parser |
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- `language`: language of the text block. Either `en` or `nan` - see known issues |
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- `page_number`: page number of text block (0-indexed) |
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- `text`: text in text block |
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- `text_block_id`: identifier for a text block which is unique per document |
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- `translated`: whether we have machine-translated the document to English. Where we have translated documents, both the original and translated exist. |
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- `type`: type of text block. In `["Text", "Title", "List", "Table", "Figure","Ambiguous"]` |
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- `type_confidence`: confidence from that the text block is of the labelled type |
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- `types`: list of document types e.g. Nationally Determined Contribution, National Adaptation Plan (list[str]) |
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- `version`: in `['MAIN', 'ANNEX', 'SUMMARY', 'AMENDMENT', 'SUPPORTING DOCUMENTATION', 'PREVIOUS VERSION']` |
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## Known issues |
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* Author names are sometimes corrupted |
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* Text blocks in non-English languages are currently missing or marked as `nan` |
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## Usage in Python |
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### Loading metadata CSV |
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``` py |
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metadata = pd.read_csv("metadata.csv") |
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``` |
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### Loading text block data |
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Once loaded into a Huggingface Dataset or Pandas DataFrame object the parquet file can be converted to other formats, e.g. Excel, CSV or JSON. |
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``` py |
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# Using huggingface (easiest) |
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dataset = load_dataset("ClimatePolicyRadar/global-stocktake-documents") |
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# Using pandas |
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text_blocks = pd.read_parquet("full_text.parquet") |
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``` |
