DIGITAL HUMANITIES
Conceptual model construction for the A Comprehensive Collection of Ancient Chinese Paintings based on metadata and ontology
Chinese paintings, as treasures of traditional culture, embody the historical depth and artistic heritage of Chinese civilization. To support digital management of A Comprehensive Collection of Ancient Chinese Paintings (CCACP), this study constructs an ontological conceptual model integrating metadata and ontology. CCACP metadata were modeled to refine its structure and align with standards such as CIDOC CRM, CDWA, and China's Metadata Standard for Painting Cultural Relics. Using Protégé and the Seven-Step Method, an ontology of 60 classes and properties was developed. A knowledge graph based on Wang Ximeng's A Thousand Li of Rivers and Mountains tested its consistency and revealed embedded knowledge associations. The model demonstrates value for collection management, knowledge sharing, and academic research, providing a practical foundation for CCACP's digital management and advancing digital humanities and cultural heritage research.
Executive Impact: Key Findings at a Glance
This paper addresses the challenges in managing A Comprehensive Collection of Ancient Chinese Paintings (CCACP) by proposing a digital humanities approach. It leverages metadata and ontology to create a structured knowledge system, enhancing resource sharing and semantic discovery. The aim is to transform traditional art historical research into a data-driven methodology.
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Ontology Classes & Properties
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Paintings Cataloged
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Institutions Covered
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CIDOC CRM Version
Deep Analysis & Enterprise Applications
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Methodology
Standards Integration
Ontology Engineering
Application Example
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Key Steps in Stanford's Method
Ontology Development Steps
The Stanford Seven-Step Method was employed for ontology construction, ensuring a structured and comprehensive approach to model development.
| Standard | Key Benefits | Application to CCACP |
|---|---|---|
| CIDOC CRM |
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| CDWA |
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| Dublin Core |
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| China's National Standards |
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Ontology Construction Process
Determine domain & scope
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Consider reuse of existing ontologies
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Enumerate important terms
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Define classes & hierarchy
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Define properties of classes
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Define facets for properties
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Create individuals
The new ontology model for CCACP was constructed using a systematic, iterative process, starting from domain definition to individual instance creation.
Case Study: A Thousand Li of Rivers and Mountains
Wang Ximeng's 'A Thousand Li of Rivers and Mountains' served as a pivotal case study to test and validate the ontological model.
Artwork Significance: A representative work of blue-green landscape painting from the Northern Song period, created by Wang Ximeng. It's his only extant work, depicting magnificent natural scenery.
Model Validation: Used to demonstrate knowledge graph construction, revealing embedded knowledge associations (e.g., linking to digital animation videos, research projects, and digital publishing initiatives).
Digital Humanities Impact: Showcases how the CCACP ontological model facilitates deeper understanding, enhances resource dissemination, and supports interdisciplinary research in cultural heritage.
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Your AI Implementation Roadmap
We've outlined a strategic, phase-by-phase approach to integrate AI into your enterprise, ensuring minimal disruption and maximum impact. This roadmap is derived from the successful methodology demonstrated in the research.
Phase 1: Metadata Foundation
Structured collection of existing painting metadata, aligning with international standards (CIDOC CRM, CDWA) and specific Chinese cultural relic standards.
Phase 2: Ontology Development
Construction of a domain ontology for CCACP using the Stanford Seven-Step Method, defining classes, properties, and relationships in Protégé.
Phase 3: Knowledge Graph Creation
Populating the ontology with instance data from CCACP, exemplified by 'A Thousand Li of Rivers and Mountains', to create a knowledge graph.
Phase 4: Semantic Enrichment & Application
Developing intelligent retrieval, semantic search, and knowledge discovery tools based on the knowledge graph for research and dissemination.
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