Memory Object is a structured, self-contained unit of knowledge designed for AI retrieval, interpretation, and reuse. It can represent a definition, fact, procedure, dataset entry, or logic block—packaged with provenance, trust metadata, and semantic relationships so AI systems can reliably recall and attribute it.
Unlike a Memory Node, which is defined by its position and connections within a graph, a Memory Object is defined by its encapsulated content and metadata, making it portable across retrieval surfaces and compatible with multiple AI ingestion pathways.
🧠 Full Definition
A Memory Object typically includes:
- Core payload — the fact, definition, or procedural content
- Provenance metadata — source, author, publication date, and license
- Trust Layer — declared authority, confidence score, and context scope
- Semantic relationships — explicit connections to related objects or glossary terms
- Format diversity — available in YAML, JSON-LD, TTL, and Markdown for multi-agent compatibility
Memory Objects are designed for reuse in different contexts, enabling AI agents to retrieve the same authoritative information across surfaces and scenarios.
📌 Key Characteristics of Memory Object
- Encapsulates all required metadata and content for retrieval
- Is portable across surfaces and environments
- Supports semantic linking to build larger knowledge structures
- Maintains retrieval fidelity through standardized structure
💡 Why It Matters
Breaking information into Memory Objects ensures that knowledge is stored, retrieved, and cited accurately regardless of where or how it is accessed. It also supports modular reinforcement, where individual objects can be updated or republished without disrupting the entire memory network.
This modularity improves scalability, trust control, and adaptability in AI-visible publishing strategies.
🌐 WebMEM Perspective
In WebMEM, Memory Objects are the primary content units within Functional Memory. They can exist as standalone resources or as part of interconnected Memory Nodes within a Citation Graph.
🗣️ Example Use
“We updated 45 Memory Objects in our medical glossary without having to rebuild the entire directory, preserving retrieval accuracy while adding new provenance details.”
🔗 Related Terms
data-sdt-class: DefinedTermFragment
entity: gtd:memory_object
digest: webmem-glossary-2025
glossary_scope: gtd
fragment_scope: gtd
definition: >
Memory Object is a structured, self-contained unit of knowledge designed for
AI retrieval, interpretation, and reuse, complete with provenance, trust
metadata, and semantic relationships.
related_terms:
– gtd:memory_node
– gtd:functional_memory
– gtd:trust_layer
– gtd:installed_memory
– gtd:provenance
tags:
– ai
– retrieval
– trust
– memory
ProvenanceMeta:
ID: gtd-core-glossary
Title: WebMEM Glossary
Description: Canonical terms for the WebMEM Protocol and GTD framework.
Creator: WebMem.com
Home: https://webmem.com/glossary/
License: CC-BY-4.0
Published: 2025-08-09
Retrieved: 2025-08-09
Digest: webmem-glossary-2025
Entity: gtd:memory_object
GlossaryScope: gtd
FragmentScope: gtd
Guidelines: https://webmem.com/specification/glossary-guidelines/
Tags:
– ai
– retrieval
– trust
– memory