Knowledge Management & Representation

  • Overview
  • Course Content
Overview

Knowledge Management & Representation

Course Description

This course explores how effective knowledge management supports digital transformation and leadership in the age of artificial intelligence (AI). You will learn how to build a business case for knowledge management, address data silos and heterogeneity, and understand how Findable, Accessible, Interoperable, and Reusable (FAIR) principles and digital threads create measurable value. This course examines knowledge discovery and reuse, including core concepts, reuse patterns, and the role of taxonomies, metadata, knowledge graphs, and AI in improving access to information. You will also explore how ontologies and standards enable interoperability and traceability, and how leaders can strategically apply AI while understanding the responsibilities of decision-making in the age of AI.

Course Content

KNOWLEDGE MANAGEMENT BUSINESS CASE

  • Knowledge management value in aerospace and defense digital transformation
  • Data silos, workforce knowledge loss, and findability challenges
  • Knowledge management metrics and organizational benefits

KNOWLEDGE REUSE AND DISCOVERY

  • Explicit and tacit knowledge lifecycle
  • Reuse patterns, barriers, and context preservation
  • Taxonomies, metadata, and knowledge graphs
  • AI-assisted search and recommendations

ONTOLOGIES AND STANDARDS

  • Knowledge representation concepts and methods
  • Semantic standards and interoperability frameworks
  • Governance, semantic search, and adoption challenges

AI LEADERSHIP AND RESPONSIBLE KNOWLEDGE MANAGEMENT

  • AI-enabled engineering and decision support
  • Data literacy, AI fluency, and ethical reasoning
  • AI governance, accountability, and decision rights

Who Should Attend

This course is designed for engineering and business leaders, knowledge managers, data architects, systems engineers, AI and digital transformation professionals, and government or industry employees responsible for improving knowledge reuse, interoperability, AI readiness, and responsible decision-making in complex organizations.

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What You Will Learn

  • Develop knowledge management business cases and quantify value.
  • Apply FAIR principles to improve knowledge findability and reuse.
  • Explore knowledge creation, discovery, and reuse practices.
  • Use taxonomies, metadata, and knowledge graphs to organize information.
  • Apply ontologies and semantic structures to improve interoperability.
  • Evaluate AI-enabled approaches for knowledge management and decision support.
  • Identify responsible AI governance practices and leadership considerations.

How You Will Benefit

  • Build a stronger business case for knowledge management by connecting reuse, traceability, time savings, and reduced rework to measurable organizational value.
  • Improve knowledge discovery by applying FAIR principles, metadata, taxonomies, and knowledge graphs to make information easier to find, trust, and reuse.
  • Reduce the impact of data silos and heterogeneous systems by using ontologies and standards to improve interoperability across teams and tools.
  • Apply AI-enhanced knowledge management approaches to support faster search, smarter recommendations, and better decision-making.
  • Lead responsible AI and knowledge management initiatives through effective governance and accountability practices
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  • Taught by Experts in the Field icon
    Taught by Experts in the Field

TRAIN AT YOUR LOCATION

We enable employers to provide specialized, on-location training on their own timetables. Our world-renowned experts can create unique content that meets your employees' specific needs. We also have the ability to deliver courses via web conferencing or on-demand online videos. For 15 or more students, it is more cost-effective for us to come to you.

  • Save Money
  • Flexible Schedule
  • Group Training
  • Customize Content
  • On-Site Training
  • Earn a Certificate
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