IEEE Std 2807.1-2024 PDF

Full title and description

IEEE Std 2807.1-2024 — IEEE Standard for Technical Requirements and Evaluating Knowledge Graphs. This standard specifies technical requirements, performance metrics, evaluation criteria and mandatory test cases for knowledge graphs, including data input and metadata handling, data extraction, data fusion, storage and retrieval, inference and analysis, and knowledge-graph display and visualization. Its purpose is to promote the stability, availability and usability of knowledge graphs and to lower the barrier for model selection by users and producers of knowledge-graph technologies.

Abstract

This active IEEE standard defines a common set of measurable requirements and evaluation procedures for knowledge-graph systems. It provides mandatory test cases and recommended evaluation metrics covering ingestion, metadata, extraction, fusion, storage/retrieval, inferencing, analysis, and presentation of knowledge graphs so organizations can assess functional quality, performance and conformance. The standard targets both producers (tool and platform developers) and consumers (system integrators, application teams) of knowledge-graph solutions.

General information

• Status: Active standard.
• Publication date: 17 September 2024.
• Publisher: Institute of Electrical and Electronics Engineers (IEEE), published through IEEE Standards channels.
• ICS / categories: 35.240.01 — Applications of information technology (general / IT applications).
• Edition / version: 2024 edition (IEEE Std 2807.1-2024).
• Number of pages: 57 pages.

Key administrative notes: the project was developed under the IEEE Computer Society / Knowledge Engineering Standards Committee and was approved by the IEEE SA Standards Board in 2024.

Scope

The scope covers technical requirements, performance metrics, evaluation criteria and concrete test cases for knowledge graphs used across industries and research. It applies to systems and components that create, manage, serve or visualize knowledge graphs and to suppliers of supporting tools and services; it is intended for use in planning, design, development, implementation and validation of knowledge-graph solutions. Mandatory test categories are defined for data input and metadata, extraction, fusion, storage and retrieval, inference and analysis, and display.

Key topics and requirements

• Definition of technical requirements for knowledge-graph components (ingest, model, store, query, inferencing, visualization).
• Performance metrics and measurable evaluation criteria (latency, throughput, accuracy/coverage, consistency, completeness, metadata quality).
• Mandatory evaluation test cases covering: data input and metadata; data extraction and transformation; data fusion and linking; storage and retrieval (queries); inference and analytic processing; and display/visualization.
• Conformance testing procedures and reporting structure for evaluation results.
• Recommendations for test-data selection, measurement methodology and interoperability considerations for knowledge-graph tooling.

Typical use and users

Typical users include knowledge engineers, data engineers, ML/AI teams, platform and data‑infrastructure architects, QA/validation teams, vendors of knowledge-graph platforms and tools, systems integrators, and research groups assessing KG technologies. Organizations use the standard to specify procurement requirements, perform comparative evaluations, validate system conformance, and guide design and implementation choices for production knowledge-graph deployments.

Related standards

Related work includes other IEEE 2807-series projects (extensions and application-level standards in the 2807 family) and industry specifications for graph data and semantic technologies (for example, W3C recommendations such as RDF, OWL and SPARQL) which are commonly used alongside evaluation standards to define representation and query interoperability. The IEEE working group has active related projects in the same family (for example the P2807.12 project on general knowledge services).

Keywords

knowledge graph; knowledge-graph evaluation; performance metrics; test cases; data fusion; metadata; inferencing; graph storage; knowledge engineering; conformance testing.

FAQ

Q: What is this standard?

A: IEEE Std 2807.1-2024 is an IEEE standard that specifies technical requirements, performance metrics, evaluation criteria and mandatory test cases for knowledge graphs to enable consistent assessment and comparison of knowledge-graph systems.

Q: What does it cover?

A: It covers functional and performance aspects of knowledge graphs, including data input and metadata, extraction, fusion, storage and retrieval, inferencing and analysis, and presentation/visualization, together with test procedures and reporting.

Q: Who typically uses it?

A: Knowledge engineers, data/platform architects, tool vendors, QA teams, systems integrators and researchers use the standard to specify requirements, run evaluations, validate conformance and guide procurement or development of KG solutions.

Q: Is it current or superseded?

A: As published on 17 September 2024, IEEE Std 2807.1-2024 is an active (current) standard. Users should check IEEE Standards listings for any amendments or corrigenda published after that date.

Q: Is it part of a series?

A: Yes — it is part of the broader IEEE 2807 family of work on knowledge graphs and knowledge services; related projects and extensions are tracked by the Knowledge Engineering Standards Committee (KESC).

Q: What are the key keywords?

A: Knowledge graph, evaluation, performance metrics, test cases, data fusion, metadata, inferencing, graph storage, conformance testing.