Data · dataset · 2026
SCMAD1.0: An Image Dataset of Shuishu Text Character Library
Listed in ScienceDB
To advance the exploration of OCR technology for Shuishu characters found in folk manuscripts of the Shui ethnic group, we construct and release SCMAD1.0 (Shuishu Character Multimodal Dataset v1.0), a machine-learning-oriented multimodal dataset for Shuishu characters.
Description
The dataset comprises two complementary subsets. Subset 1, shui_rawchars_set (Raw Shuishu Character Image Collection), contains 2,203 single-character images selected from over 90,000 images cropped character-by-character from pages of Shuishu scriptures.
Each image is named according to the convention "source document_page number_intra-page index", preserving the morphological distribution characteristics of the original documents, making it suitable for pre-training and unsupervised analysis. Subset 2, shui_normalchars_set (Collated Shuishu Character Image Collection), integrates multimodal information in JSON format, encompassing 2,073 single-character images and complete digital representations of 1,117 Shuishu characters.
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Drawing upon linguistic research resources such as the Shuishu Character Library, each character entry includes 13 content fields: a unique identifier, Shuishu character image, Chinese meaning, pronunciation (annotated in the International Phonetic Alphabet), annotations, classification (semantic domain), character formation method, etc. This subset is directly applicable to model training and evaluation for supervised learning tasks.Data sources were selected from published works including the Shuishu Character Library, Shuishu (Wedding Volume), Common Character List of Shuishu, and Chinese Shuishu (160-volume facsimile edition).
The dataset was constructed by combining automated pipelines — including PDF scanning, image crawling, OCR-to-Word conversion, and textual information extraction — with manual proofreading, ensuring data accuracy and consistency. Subset 2 was specifically designed with machine-learning-friendly features: (1) a variant-relationship network among characters, linking standard glyphs to their variant forms via the variants field; (2) a hierarchical classification system comprising 11 top-level categories, including celestial bodies and astronomical phenomena, heaven-earth and the Eight Trigrams, birds, beasts, fish, insects, and plants, among others; and (3) a unified image naming convention following the format SC_xxxxx.
The dataset supports a wide range of machine learning tasks, including character recognition, classification, cross-modal retrieval, and variant character analysis. The dataset is released under the CC BY-NC 4.0 license on the Science Data Bank platform, providing a standardized benchmark data resource for the intelligent study of Shuishu characters.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.37647 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Heritage, archive and museum studies 75% · Image 75% · Optical character recognition 65% · Text 75%
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.37647 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4302 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (75%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[method].local:method:ocr | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[modality].local:modality:image | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:text | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |