[Paper Review] Knowledge Audit Framework

Paola Di Maio|arXiv (Cornell University)|Aug 6, 2011

Semantic Web and Ontologies1 references3 citations

TL;DR

The Knowledge Audit Framework (KAF) is a methodology and set of templates for systematically assessing and managing knowledge resources within organizations, particularly emphasizing sharing and reusability. Built upon the Data Audit Framework (DAF), KAF supports both generic (KAF-g) and systems engineering-specific (KAF-se) applications, enabling institutions to inventory, evaluate, and improve the quality and accessibility of their knowledge assets through structured auditing processes.

ABSTRACT

KAF consists of a process and some templates to guide the planning and execution of audits of knowledge resources, with emphasis on sharing. KAF is based on methodological blueprint provided by the Data Audit Framework (DAF)conceived by the JISC-funded DAFD project.KAF enables organisations to find out what knowledge resources are associated with the project, and how they are shared.KAF is available in two versionsKAF-g (generic, domain independent) KAF-se (targets systems enegineering knowledge)

Motivation & Objective

• To address the lack of standardized methods for assessing organizational knowledge resources, especially in the context of sharing and reuse.
• To provide a structured, repeatable process for identifying, documenting, and evaluating knowledge assets across different domains.
• To support institutional knowledge management by enabling organizations to understand the scope, quality, and utility of their knowledge resources.
• To adapt the principles of the Data Audit Framework (DAF) to the domain of knowledge, particularly in systems engineering contexts.
• To enhance transparency and accountability in knowledge management through formalized audit templates and procedures.

Proposed method

• Adapts the methodological blueprint of the Data Audit Framework (DAF) to the domain of knowledge resources.
• Provides two versions: KAF-g (generic, domain-independent) and KAF-se (tailored for systems engineering knowledge).
• Uses standardized templates to guide the documentation and evaluation of knowledge assets across dimensions such as provenance, format, accessibility, and reuse potential.
• Emphasizes process-oriented auditing to ensure consistency and scalability in knowledge resource assessment.
• Supports integration with existing institutional workflows and knowledge management systems.
• Relies on a structured audit process that includes inventorying knowledge resources, assessing their quality, and identifying gaps or improvements.

Experimental results

Research questions

• RQ1 How can organizations systematically assess the quality and reusability of their knowledge resources?
• RQ2 What methodological framework enables consistent auditing of knowledge assets across diverse organizational contexts?
• RQ3 How can the principles of data auditing be adapted to the more complex domain of knowledge resources?
• RQ4 What are the key dimensions that should be evaluated when auditing knowledge assets for sharing and reuse?
• RQ5 In what ways can a standardized audit framework improve knowledge management in institutional and engineering settings?

Key findings

• The Knowledge Audit Framework (KAF) provides a repeatable, scalable process for auditing knowledge resources, supporting both generic and domain-specific applications.
• KAF-g enables organizations to conduct knowledge audits in a standardized way regardless of domain, promoting consistency and interoperability.
• KAF-se offers a specialized adaptation for systems engineering knowledge, addressing the unique complexity and requirements of engineering knowledge assets.
• The framework enhances transparency by documenting the provenance, format, and accessibility of knowledge resources, facilitating reuse and sharing.
• By building on the DAF, KAF inherits a robust methodological foundation, increasing its credibility and practical applicability.
• The framework supports institutional knowledge governance by identifying gaps, improving quality, and enabling strategic planning for knowledge resource development.