Summary
Over the past 10 years, there has been an a ground swell of knowledge systems. Knowledge systems stand on the shoulders of information systems...not only delivering information, but delivering that information in the context of the user's needs. The user experience for these systems has not kept pace with the rapid proliferation of technologies that support knowledge systems (artificial intelligence, machine learning, knowledge graphs). Let's take a survey of these the technology and landscape of knowledge systems, and discover strategies and best practices for implementing knowledge systems. You will: Gain an understanding of the different type and purposes of knowledge systems, and their characteristic advantages and disadvantages Discover the needs of users Methods to implement UX strategies for knowledge systems
Key Insights
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Knowledge systems use graph databases with nodes and relationships modeled after subject-verb-object sentence structures for efficient storage and comprehension.
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Knowledge differs from data and information by being tailored toward human action, not just consumption.
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Graph-based knowledge systems are still immature compared to well-established tabular data systems and lack standardized UX patterns and terminology.
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AI chatbots like ChatGPT provide conversational knowledge access but lack traceability and rich interaction beyond transactional Q&A.
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Knowledge creation interfaces must cater to both creators and consumers, a duality posing UX design challenges uncommon in data or information systems.
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Metadata plays a crucial role in enriching knowledge nodes and managing complex relationships at enterprise scale.
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The abstraction of knowledge makes UX design particularly challenging and necessitates translating conceptual models into concrete, usable experiences.
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Different user groups and industries require context-sensitive language bridging jargon from UX, information architecture, and organizational domains.
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UX professionals have an opportunity to influence vendor product design and internal deployments to improve knowledge system usability from the start.
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A blended approach like the World Economic Forum's transformation maps shows promise for integrating graph-based visualizations with narrative information to enrich knowledge presentation.
Notable Quotes
"Knowledge systems are enterprise level applications that are repositories of a body of knowledge, usually focused on a single topic or related group of topics."
"Knowledge is not only intended for human consumption, it is meant for human action."
"The method of depicting knowledge comes directly from subject verb object sentence diagramming that we learned in school."
"Graph databases use nodes and relationships instead of tables to store information, providing a network of knowledge."
"Many knowledge systems have little ability to create new interfaces, but their experience can be shaped by how they’re used and configured."
"The chatbot method is very transactional: user asks, system responds, and that is pretty much it."
"There needs to be some sort of universal standard for sourcing or mapping how the knowledge was obtained."
"We need to break out of the 30 years of design that has been geared around relational databases."
"Knowledge is very conceptual, very abstract, and you’re trying to make it very concrete to use."
"The best experiences I’ve had are where information architecture and user experience worked hand in hand."
Dig deeper—ask the Rosenbot:
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