Update README.md

README.md

@@ -10,11 +10,13 @@ pretty_name: CoMMA
 size_categories:
 - 1B<n<10B
 ---
-# Dataset Card for Dataset Name
+# Dataset Card for CoMMA JSON-L
 
-<!-- Provide a quick summary of the dataset. -->
-
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
+CoMMA is a large-scale corpus of digitized medieval manuscripts 
+transcribed using Handwritten Text Recognition (HTR). It 
+contains over 2.5 billion tokens from more than 23,000 manuscripts in
+Latin and Old French (801–1600 CE). Unlike most existing resources, the corpus
+provides raw, non-normalized text.
 
 ## Dataset Details
 
@@ -24,49 +26,58 @@ This dataset card aims to be a base template for new datasets. It has been gener
 
 
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
+- **Curated by:** Thibault Clérice
+- **Funded by:** Inria, [COLaF](https://colaf.huma-num.fr/), [ParamHTRs](https://www.bnf.fr/fr/les-projets-de-recherche-bnf-datalab)
+- **Language(s) (NLP):** Latin, Old French, Italian
+- **License:** CC-BY 4.0
 
 ### Dataset Sources [optional]
 
 <!-- Provide the basic links for the dataset. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** ARCA, Gallica, Biblissima + (Metadata)
+- **Paper:** [More Information Needed]
+- **Browser:** [More Information Needed]
 
 ## Uses
 
-<!-- Address questions around how the dataset is intended to be used. -->
-
 ### Direct Use
 
-<!-- This section describes suitable use cases for the dataset. -->
+- Training and evaluation of NLP models on medieval Latin and French.
+- Historical linguistics and corpus linguistics research.
+- Digital humanities applications (script analysis, layout studies, philology).
+- Pretraining embeddings for downstream semantic tasks.
 
-[More Information Needed]
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
+- Modern language processing tasks.
+- Sensitive/identity analysis (texts are historical and not linked to personal data).
 
 ## Dataset Structure
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-
-[More Information Needed]
+The dataset is in JSON-L format, one line = one digitization of a manuscript 
+(manuscript can be represented by more than one digitization). Columns are:
+
+- **biblissima_id**: Unique identifier of the manuscript, with metadata. .e.g https://data.biblissima.fr/entity/Q237292
+- **shelfmark**: Human readable identifier
+- **iiif_manifest**: Source of our data
+- **biblissima_language**: Biblissima provided language metadata
+- **biblissima_simplified_language**: Denoising field for **biblissima_language**
+- **language_fasttext**: Categorization in 5 languages (Latin, French, Bilingual, Other, Ambiguous), with two levels of details for Latin, French and Bilingual (e.g. Massively French, Truely French)
+- **notBefore**: Minimal date of production. Some provider use 800 for stating 9th century instead of 801, be careful with the date.
+- **notAfter**: When provided, maximum date of production. Mostly *null*.
+- **lines**: Number of transcribed lines.
+- **pages**: Number of treated pages.
+- **tokens**: Number of whitespace delimited tokens.
+- **scopecontent**: Free-text field description of the content of the manuscript, provided by Biblissima and the original curating institution.
+- **text**: The main body of text, in its plain text representation.
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
+To provide the first large-scale, open, raw-text corpus of medieval manuscripts enabling both computational linguistics and digital humanities research at scale.
 
 ### Source Data
 
@@ -74,49 +85,36 @@ This dataset card aims to be a base template for new datasets. It has been gener
 
 #### Data Collection and Processing
 
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
+- Harvested via IIIF from Gallica (BnF), ARCA, Bodleian, e-codices, etc.
+- Downloaded in batch respecting institutional constraints.
+- Segmentation: YOLOv11 + SegmOnto vocabulary.
+- Recognition: Kraken with CATMuS models.
+- Post-processed into ALTO and TEI.
 
 #### Who are the source data producers?
 
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+Medieval scribes and copyists (8th–16th c. CE), preserved in institutional digitizations.
 
 #### Annotation process
 
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
+- Automated segmentation and transcription.
+- Manual evaluation of CER on roughly 700 manuscripts single pages.
+- TEI structuring for zones (marginalia, main text, etc.).
 
 #### Personal and Sensitive Information
 
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
+The dataset contains no personal or sensitive modern data.
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+- Recognition quality varies by script type (Caroline/Textualis better, Cursiva and Beneventan worse).
+- Language metadata may be noisy (e.g. mixed Latin/French glosses).
+- Manuscripts are primarily from libraries, underrepresenting archives (e.g. charters).
+- Errors in segmentation (skewed lines, faint text) persist.
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+Users should evaluate CER for their subcorpus and be aware of biases in script and manuscript type coverage.
 
 ## Citation [optional]
 
@@ -130,20 +128,6 @@ Users should be made aware of the risks, biases and limitations of the dataset.
 
 [More Information Needed]
 
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Dataset Card Authors [optional]
-
-[More Information Needed]
-
 ## Dataset Card Contact
 
-[More Information Needed]
+Thibault Clerice