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IEEE 2807-2022

IEEE Standard for Framework of Knowledge Graphs

Standard by IEEE, 2023

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  • Availability: Immediate Download
  • Language: English
  • License Type: Single User
  • Updates: Not Included
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  • Language: English
  • License Type: Enterprise / Multi User
  • Updates: Included

About This Item

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IEEE 2807-2022 defines a framework of knowledge graphs for computing and processing applications, helping clarify how graph-based knowledge can be structured, represented, and used. This standard is relevant where information must be linked in a consistent way for analysis, retrieval, or integration across systems. By setting a common technical reference, IEEE 2807-2022 can support more reliable design choices, clearer implementation expectations, and better alignment between teams working with knowledge graph methods.

About IEEE 2807-2022

IEEE 2807-2022 focuses on the framework side of knowledge graphs rather than a single software product or platform. In practice, that means it can guide how entities, relationships, and associated information are organized for computing and processing tasks. The standard is useful when organizations need a shared understanding of structure and terminology before building, comparing, or evaluating knowledge graph-based solutions. It provides a technical basis that may help reduce ambiguity during design, integration, and specification work.

Where is IEEE 2807-2022 used?

This standard is most relevant in environments that build or manage knowledge graph systems for data linking, semantic organization, and structured information access. It may be used in analytics pipelines, enterprise data platforms, digital libraries, decision-support tools, and other computing workflows where relationships between concepts matter. IEEE 2807-2022 can also be useful when defining internal data models or when multiple systems need to exchange graph-oriented knowledge in a consistent way.

Importance in practice

In practice, IEEE 2807-2022 matters because knowledge graph projects can become difficult to compare or maintain without a common framework. A well-defined standard helps support consistency in design, clearer procurement and specification language, and more disciplined testing of graph structures and behavior. It can also reduce integration risk when different teams or tools handle the same knowledge model, making it easier to align performance expectations and long-term maintenance plans.

  • Knowledge graph framework
  • Computing and processing context
  • Structured entity and relationship modeling
  • Consistency for integration and evaluation
  • Active English-language standard
SKU: 01471a0d466b

  • Publication Date: 2023
  • Standard Status: Active
  • Publisher: IEEE
  • Subject: Computing and Processing
  • Official IEEE: Doi link
  • This Version: 2807 (2023)

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