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DarjaCore
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asjp-cerist

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Arabic

French

English

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The dataset viewer is not available for this subset.

Cannot get the split names for the config 'default' of the dataset.

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 246, in _split_generators
                  raise ValueError(
                      "`file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files"
                  )
              ValueError: `file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

ASJP / CERIST Academic PDF Corpus

Overview

DarjaCore ASJP/CERIST is a large-scale collection of academic PDF documents collected from the Algerian ASJP (Algerian Scientific Journal Platform) ecosystem associated with CERIST (Centre de Recherche sur l'Information Scientifique et Technique).

The dataset preserves the original PDF documents rather than converting them into extracted text. This allows researchers to perform their own OCR, document parsing, layout analysis, multilingual processing, metadata extraction, and other downstream tasks.

The collection contains tens of thousands of academic PDF files covering Algerian scientific and scholarly publications.

Dataset Statistics

Statistic	Value
PDF files	37,807
Metadata records	21,604
Total PDF size	~50.30 GB
Total pages	579,683
Extracted text characters*	1,094,404,357
Extracted text words*	166,828,860
Estimated tokens*	~216.9 million

* Text statistics were obtained during corpus analysis. They should not be interpreted as the exact amount of machine-readable text available in every PDF.

Document Composition

The corpus contains a mixture of digitally generated PDFs and scanned documents.

PDF type	Files	Percentage
Text PDFs	6,231	16.48%
Image PDFs	494	1.31%
Mixed PDFs	30,981	81.95%
Empty / no detected text	50	0.13%
Processing errors	51	—

The large proportion of mixed PDFs means that many documents may contain both machine-readable text and scanned/image-based pages.

Dataset Structure

The repository is organized into numbered subdirectories to avoid excessive numbers of files in a single directory.

asjp-cerist/
├── README.md
├── metadata.jsonl
└── pdfs/
    ├── 000/
    │   ├── 00001.pdf
    │   ├── 00001_sommaire.pdf
    │   └── ...
    ├── 001/
    ├── 002/
    ├── 003/
    ├── 004/
    ├── 005/
    ├── 006/
    └── 007/

Each PDF is identified by a normalized numeric identifier.

Metadata

The metadata.jsonl file contains one JSON object per line.

Available fields include:

title
journal_title
volume
issue
first_page
last_page
publication_date
abstract
keywords
pdf_url
sommaire_pdf_url
article_url
authors
authors_emails
institutions
local_pdf_path
local_sommaire_pdf_path

Example:

{
  "title": "...",
  "journal_title": "...",
  "volume": "...",
  "issue": "...",
  "publication_date": "...",
  "abstract": "...",
  "keywords": ["...", "..."],
  "pdf_url": "...",
  "article_url": "...",
  "authors": ["..."],
  "institutions": ["..."],
  "local_pdf_path": "pdfs/000/00001.pdf"
}

Why Raw PDFs?

This dataset intentionally keeps the original documents in PDF format.

This makes the corpus useful for:

OCR research
Arabic OCR
French OCR
Multilingual document understanding
PDF parsing
Document layout analysis
Academic information extraction
Metadata extraction
Citation extraction
Table and figure extraction
Retrieval-Augmented Generation (RAG)
Building academic search engines
Training document-processing models
Creating downstream text datasets

Keeping the original PDFs allows researchers to select their own extraction and preprocessing pipeline.

Languages

The corpus contains multilingual academic material, including:

Arabic
French
English

Individual documents may contain more than one language.

Data Processing

The preparation pipeline included:

Collecting PDF documents.
Collecting associated bibliographic metadata.
Normalizing PDF identifiers.
Organizing PDFs into subdirectories.
Updating metadata paths.
Validating the relationship between metadata and PDF files.
Converting metadata into JSON Lines format.
Validating the final dataset structure.

Final validation confirmed:

Metadata records         : 21,604
Actual PDFs              : 37,807

Main PDFs referenced     : 19,053
Sommaire PDFs referenced : 18,754

Unique referenced PDFs   : 37,807

Missing main PDFs        : 0
Missing sommaire PDFs    : 0
Unreferenced PDFs        : 0

JSONL validation         : OK

Intended Uses

This corpus can be useful for research and development involving:

Algerian academic literature
Arabic NLP
French NLP
Multilingual NLP
Information retrieval
Semantic search
Retrieval-Augmented Generation
Academic question answering
OCR
Document AI
Digital libraries
Knowledge extraction
Academic language-model datasets

Scanned Documents

A significant portion of the corpus contains scanned or partially scanned pages.

Consequently, standard PDF text extraction may not recover all of the document content. OCR may be required for image-based pages.

A typical processing pipeline could be:

PDF
 │
 ├── PDF text extraction
 │
 ├── OCR for image-based pages
 │
 ├── Language identification
 │
 ├── Text normalization
 │
 ├── Deduplication
 │
 ├── Metadata alignment
 │
 └── Training / Retrieval Dataset

For Arabic documents, researchers should pay particular attention to Unicode normalization, Arabic character variants, OCR errors, diacritics, and document layout.

Main PDF vs. Sommaire PDF

The dataset contains both main article PDFs and documents identified with the _sommaire.pdf suffix.

Researchers building text datasets may wish to treat these as separate document types during preprocessing.

Data Quality

The dataset was validated to ensure that:

Metadata is valid JSONL.
Referenced PDF files exist.
Main PDF paths are valid.
Sommaire PDF paths are valid.
No local PDFs were left unreferenced.
PDF identifiers follow the normalized naming convention.

Citation

If you use this dataset in research, please cite the original ASJP/CERIST sources and this dataset repository.

@dataset{darjacore_asjp_cerist,
  title     = {ASJP / CERIST Academic PDF Corpus},
  author    = {DarjaCore},
  publisher = {Hugging Face},
  year      = {2026},
  url       = {https://huggingface.co/datasets/DarjaCore/asjp-cerist}
}

Acknowledgements

This dataset was assembled by DarjaCore as part of efforts to build large-scale Arabic and Algerian-language resources for research in natural language processing, information retrieval, document understanding, and language model development.

The underlying documents originate from the ASJP/CERIST academic publication ecosystem. Credit belongs to the original authors, journals, publishers, and source platforms.

License and Rights

The PDFs in this repository originate from third-party academic publications.

Users are responsible for determining whether their intended use of individual documents complies with the copyright, licensing, and access conditions applicable to those documents and their respective publishers.

This repository does not grant redistribution rights for the underlying publications.

Before making the dataset publicly accessible or using it for commercial purposes, verify the applicable rights and licenses of the source documents.

Disclaimer

This dataset is provided for research and educational purposes.

DarjaCore does not claim ownership of the underlying academic publications. The original authors, journals, publishers, and rights holders retain their respective rights.

The dataset may contain documents subject to different copyright and licensing conditions.

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