Icon Ontology (ICON)

The ICON ontology provides a formal framework for high-granularity art interpretation and analysis. It was developed by conceptualizing Panofsky’s theory of levels of interpretation, enabling artworks to be systematically described according to three complementary analytical perspectives: Pre-iconographical (visual recognition and formal elements), Iconographical (subject matter and represented themes), and Iconological (deeper symbolic, cultural, and philosophical meanings) [1]. This three-level approach enables comprehensive semantic annotation of artworks, capturing both surface-level visual descriptions and deeper interpretive insights [1] [2]. The ontology supports structured knowledge representation of artistic elements, iconographic themes, cultural references, and symbolic meanings [1]. It facilitates semantic interoperability in linked cultural heritage data by aligning with other ontologies and knowledge bases, including CIDOC-CRM and VIR [1] [3]. The ICON ontology enables detailed modelling of artistic interpretation for art history research, corpus annotation, and linked data applications, supporting researchers and curators in analyzing and comparing artworks across interpretation levels [1] [2].

Example Usage: Annotate an artwork or museum object with ICON ontology terms describing pre-iconographical elements, iconographical subjects, and iconological meanings for example, identifying depicted figures, their symbolic attributes, and the broader cultural or philosophical interpretation of the scene to support semantic search, comparative art historical analysis, and linked data integration across cultural heritage datasets [1] [2].

Metrics & Statistics

Graph Statistics

Total Nodes

408

Total Edges

1091

Root Nodes

11

Leaf Nodes

131
Knowledge Coverage Statistics

Classes

76

Individuals

0

Properties

68
Hierarchical Metrics

Maximum Depth

12

Minimum Depth

0

Average Depth

5.92

Depth Variance

13.34
Breadth Metrics

Maximum Breadth

13

Minimum Breadth

5

Average Breadth

8.62

Breadth Variance

4.24
LLMs4OL Dataset Statistics

Term Types

0

Taxonomic Relations

65

Non-taxonomic Relations

4

Average Terms per Type

0.00

Usage Example

Use the following code to import this ontology programmatically:

from ontolearner.ontology import ICON

ontology = ICON()
ontology.load("path/to/ICON-ontology.owl")

# Extract datasets
data = ontology.extract()

# Access specific relations
term_types = data.term_typings
taxonomic_relations = data.type_taxonomies
non_taxonomic_relations = data.type_non_taxonomic_relations

References