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glam/schemas/20251121/linkml/modules/classes/VideoAnnotation.yaml
kempersc ca4a54181e Refactor schema files to improve clarity and maintainability 
- Updated WorldCatIdentifier.yaml to remove unnecessary description and ensure consistent formatting.
- Enhanced WorldHeritageSite.yaml by breaking long description into multiple lines for better readability and removed unused attributes.
- Simplified WritingSystem.yaml by removing redundant attributes and ensuring consistent formatting.
- Cleaned up XPathScore.yaml by removing unnecessary attributes and ensuring consistent formatting.
- Improved YoutubeChannel.yaml by breaking long description into multiple lines for better readability.
- Enhanced YoutubeEnrichment.yaml by breaking long description into multiple lines for better readability.
- Updated YoutubeVideo.yaml to break long description into multiple lines and removed legacy field name.
- Refined has_or_had_affiliation.yaml by removing unnecessary comments and ensuring clarity.
- Cleaned up is_or_was_retrieved_at.yaml by removing unnecessary comments and ensuring clarity.
- Added rules for generic slots and avoiding rough edits in schema files to maintain structural integrity.
- Introduced changes_or_changed_through.yaml to define a new slot for linking entities to change events.
2026-01-31 00:46:23 +01:00

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id: https://nde.nl/ontology/hc/class/VideoAnnotation
name: video_annotation_class
title: Video Annotation Class
imports:
- linkml:types
- ../enums/AnnotationTypeEnum
- ../slots/analyzes_or_analyzed
- ../slots/contains_or_contained
- ../slots/filters_or_filtered
- ../slots/has_or_had_quantity
- ../slots/has_or_had_rationale
- ../slots/has_or_had_score
- ../slots/has_or_had_treshold
- ../slots/has_or_had_type
- ../slots/has_or_had_unit
- ../slots/includes_bounding_box
- ../slots/includes_segmentation_mask
- ../slots/keyframe_extraction
- ../slots/model_architecture
- ../slots/model_task
- ../slots/specificity_annotation
- ./AnnotationMotivationType
- ./AnnotationMotivationTypes
- ./DetectedEntity
- ./DetectionThreshold
- ./Quantity
- ./SpecificityAnnotation
- ./TemplateSpecificityScore
- ./TemplateSpecificityType
- ./TemplateSpecificityTypes
- ./Unit
- ./VideoFrame
- ./VideoTextContent
- ./VideoTimeSegment
- ./Segment
- ./AnnotationType
- ./Rationale
prefixes:
linkml: https://w3id.org/linkml/
hc: https://nde.nl/ontology/hc/
schema: http://schema.org/
dcterms: http://purl.org/dc/terms/
prov: http://www.w3.org/ns/prov#
crm: http://www.cidoc-crm.org/cidoc-crm/
oa: http://www.w3.org/ns/oa#
as: https://www.w3.org/ns/activitystreams#
default_prefix: hc
classes:
VideoAnnotation:
is_a: VideoTextContent
class_uri: oa:Annotation
abstract: true
description: "Abstract base class for computer vision and multimodal video annotations.\n\n**DEFINITION**:\n\nVideoAnnotation represents structured information derived from visual\nanalysis of video content. This includes:\n\n| Subclass | Analysis Type | Output |\n|----------|---------------|--------|\n| VideoSceneAnnotation | Shot/scene detection | Scene boundaries, types |\n| VideoObjectAnnotation | Object detection | Objects, faces, logos |\n| VideoOCRAnnotation | Text extraction | On-screen text (OCR) |\n\n**RELATIONSHIP TO W3C WEB ANNOTATION**:\n\nVideoAnnotation aligns with the W3C Web Annotation Data Model:\n\n```turtle\n:annotation a oa:Annotation ;\n oa:hasBody :detection_result ;\n oa:hasTarget [\n oa:hasSource :video ;\n oa:hasSelector [\n a oa:FragmentSelector ;\n dcterms:conformsTo <http://www.w3.org/TR/media-frags/> ;\n rdf:value \"t=30,35\"\n ]\n ] ;\n oa:motivatedBy oa:classifying .\n```\n\n**FRAME-BASED\
\ ANALYSIS**:\n\nUnlike audio transcription (continuous stream), video annotation is\ntypically frame-based:\n\n- `frame_sample_rate`: Frames analyzed per second (e.g., 1 fps, 5 fps)\n- `analyzes_or_analyzed`: Total frames processed\n- Higher sample rates = more detections but higher compute cost\n\n**DETECTION THRESHOLDS**:\n\nCV models output confidence scores. Thresholds filter noise:\n\n| Threshold | Use Case |\n|-----------|----------|\n| 0.9+ | High precision, production display |\n| 0.7-0.9 | Balanced, general use |\n| 0.5-0.7 | High recall, research/review |\n| < 0.5 | Raw output, needs filtering |\n\n**MODEL ARCHITECTURE TRACKING**:\n\nDifferent model architectures have different characteristics:\n\n| Architecture | Examples | Strengths |\n|--------------|----------|-----------|\n| CNN | ResNet, VGG | Fast inference, good for objects |\n| Transformer | ViT, CLIP | Better context, multimodal |\n| Hybrid | DETR, Swin | Balance of speed and accuracy |\n\n**HERITAGE INSTITUTION\
\ CONTEXT**:\n\nVideo annotations enable:\n- **Discovery**: Find videos containing specific objects/artworks\n- **Accessibility**: Scene descriptions for visually impaired\n- **Research**: Analyze visual content at scale\n- **Preservation**: Document visual content as text\n- **Linking**: Connect detected artworks to collection records\n\n**CIDOC-CRM E13_Attribute_Assignment**:\n\nAnnotations are attribute assignments - asserting properties about\nvideo segments. The CV model or human annotator is the assigning agent.\n"
exact_mappings:
- oa:Annotation
close_mappings:
- crm:E13_Attribute_Assignment
related_mappings:
- as:Activity
- schema:ClaimReview
slots:
- has_or_had_rationale
- contains_or_contained
- has_or_had_type
- filters_or_filtered
- includes_bounding_box
- includes_segmentation_mask
- keyframe_extraction
- model_architecture
- model_task
- specificity_annotation
- has_or_had_score
- analyzes_or_analyzed
slot_usage:
has_or_had_type:
range: uriorcurie
required: true
examples:
- value:
has_or_had_code: OBJECT_DETECTION
has_or_had_label: Object Detection
contains_or_contained:
range: string
multivalued: true
required: false
inlined_as_list: true
examples:
- value:
has_or_had_label: Night Watch painting visible
has_or_had_description: 30.0 - 35.0 seconds
has_or_had_rationale:
range: string
required: false
examples:
- value:
has_or_had_label: ClassifyingMotivation
filters_or_filtered:
description: "MIGRATED 2026-01-25: Replaces detection_count and detection_threshold slots.\n\nLinks to DetectedEntity which contains:\n- has_or_had_quantity \u2192 Quantity (for detection_count)\n- has_or_had_treshold \u2192 DetectionThreshold (for detection_threshold)\n\n**Migration Pattern**:\n- Old: detection_count: 342, detection_threshold: 0.5\n- New: filters_or_filtered \u2192 DetectedEntity with structured data\n"
range: DetectedEntity
inlined: true
required: false
examples:
- value:
has_or_had_quantity:
has_or_had_unit:
has_or_had_treshold:
- value:
has_or_had_quantity:
has_or_had_unit:
has_or_had_treshold:
has_or_had_label: High Precision
analyzes_or_analyzed:
description: "MIGRATED 2026-01-22: Now supports VideoFrame class for frame_sample_rate migration.\n\nFrame analysis information including:\n- Total frames analyzed (integer, legacy pattern)\n- Frame sample rate and analysis parameters (VideoFrame class)\n\nMIGRATED SLOTS:\n- frame_sample_rate \u2192 VideoFrame.has_or_had_quantity with unit \"samples per second\"\n"
range: VideoFrame
inlined: true
required: false
examples:
- value:
has_or_had_quantity:
has_or_had_unit:
- value:
has_or_had_quantity:
has_or_had_unit:
keyframe_extraction:
range: boolean
required: false
examples:
- value: true
model_architecture:
range: string
required: false
examples:
- value: Transformer
- value: CNN
model_task:
range: string
required: false
examples:
- value: detection
- value: captioning
includes_bounding_box:
range: boolean
required: false
examples:
- value: true
includes_segmentation_mask:
range: boolean
required: false
examples:
- value: false
comments:
- Abstract base for all CV/multimodal video annotations
- Extends VideoTextContent with frame-based analysis parameters
- W3C Web Annotation compatible structure
- Supports both temporal and spatial annotation
- Tracks detection thresholds and model architecture
see_also:
- https://www.w3.org/TR/annotation-model/
- http://www.cidoc-crm.org/cidoc-crm/E13_Attribute_Assignment
- https://iiif.io/api/presentation/3.0/
annotations:
specificity_score: 0.1
specificity_rationale: Generic utility class/slot created during migration
custodian_types: "['*']"
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