Top Tweets for #KnowledgeEngineering
🚀ZStack was honored to participate in tcworld China 2026 and share our practices in error code content management.👉 Click to learn more about the case details:https://t.co/YgoqyxaNRs #tcworldChina2026 #TechnicalCommunication #Documentation #KnowledgeEngineering

https://t.co/0D1JGW5tSD
Domain Intelligence Suite™ — Ontology Design to Deployment #OntologyEngineering
#KnowledgeEngineering
Knowledge engineering isn't just about structuring data—it's the blueprint for autonomous AI reasoning. https://t.co/7tY2Vvu1N7
#AI #KnowledgeEngineering
@grok thoughts?
How do we marry knowledge engineering, AI engineering, data engineering, governance, and semantics into one coherent system? 😎
#ai #digitaltwins #mybook #knowledgeengineering #semantics #ontology #mybook #preorder

An introduction to Knowledge Engineering
How does human expertise become something an AI system can actually reason with?
That question sits at the heart of knowledge management, and it has never been more timely. As AI adoption accelerates, the gap between what experts know and what systems can reliably do is where projects succeed or fail.
Knowledge engineering is the discipline that bridges that gap. It is older than the current AI wave -- Feigenbaum and McCorduck were writing about it in the 1980s -- but it is more relevant than ever. Turning policies, documentation, and expert judgment into structured, auditable, explainable reasoning is not a solved problem. It is daily work.
This is not new territory. The Semantic Web pioneers understood it. Enterprise knowledge management has wrestled with it for decades. What is new is the context: as more organizations deploy AI in high-consequence domains -- tax, law, healthcare, financial services -- the question of whether a system reasons correctly, and whether you can explain why, is more urgent today.
Knowledge graphs give AI systems the structured, semantically rich foundation they need to reason beyond pattern matching. Ontologies define the concepts, relationships, and constraints that make that reasoning coherent and domain-faithful. Data modeling determines whether expert knowledge survives the translation into something a machine can use.
@RainbirdAI co-founder and CTO Ben Taylor is hosting a free five-part live webinar series alongside Rainbird's Knowledge Engineering team to open up exactly this conversation -- from first principles through to live build.
Over five sessions starting 25 March, the series covers:
-- What knowledge engineering is and how it connects to knowledge graphs and ontology design
-- Knowledge elicitation: surfacing the tacit expertise that never makes it into documentation
-- Building knowledge graphs that are scalable, testable, and maintainable
-- What the work actually looks like in practice
-- A live demonstration: eliciting from source documents, building a knowledge graph, running tests
No programming background required. Curiosity is the only prerequisite.
https://t.co/VdEWV0KzOY
#KnowledgeEngineering #Ontology #DataModeling #ExplainableAI
--
📩 The Year of the Graph Spring 2026 newsletter issue is out!
Beyond Context Graphs: How Ontology, Semantics, and Knowledge Graphs Define Context 👇
https://t.co/pxabFH0ide
All things #KnowledgeGraph, #GraphDB, Graph #Analytics / #DataScience / #AI and #SemTech.
Subscribe and follow to be in the know. Reach out if you'd like to be featured

#Semantics, #LLMs and #Ontologies: The Persistent Misunderstanding in #KnowledgeEngineering for the #ExtendedEnterprise by Dr Nicolas Figay https://t.co/e9L76KpWHI

Beyond Data. Toward Intelligence.
At MindlogicX, we’re shaping the future of AI with systems that understand context, reason logically, and support smart decision-making.
Build the future with MindlogicX.
#MindlogicX #AI #KnowledgeEngineering #FutureOfAI #Innovation

#ConfidenceTrickery, #Illogic, and #Misrepresentation in #KnowledgeEngineering by Mark Burgess https://t.co/KmUS14PfYo

📝How do researchers work with domain experts?
We’re looking for linguists, terminologists, translators & knowledge engineers to share their experience.
⏱20 min survey (anonymous)
📊FR/EN: https://t.co/kDgAB2RFo0
#Linguistics #Terminology #KnowledgeEngineering #Expert
🎲 Integrated AI context engines redefine #Interoperability requirements, documents, data, equations, & references become a single semantic graph.
#EnterpriseArchitecture #AgenticAI #DigitalTransformation #AIPlatforms #KnowledgeEngineering #CIOAgenda

Low-Cost Data Science and Knowledge Engineering in the Global South @SSRN https://t.co/UuxcCWILjI
#DataScience #AIForGood #GlobalSouth #LowCostAI #KnowledgeEngineering #TechForDevelopment #DigitalInclusion #Research
@GkikasMenelaos #KnowledgeEngineering #SystemsThinking #Science
Excellent resource! Exploring knowledge engineering principles and connecting them to systems thinking is insightful.
A different kind of modern #novel. No #AI, #cellphones, #machinelearning #neuralnetworks #robotics #DigitalCircus #knowledgeengineering #algorithms or #deeplearning. Just a beautiful exercise in human #storytelling.
https://t.co/02O4R7AQ4o?

Knowledge is no longer just managed it’s engineered.
Mindlogicx is a global knowledge company at the intersection of AI and human expertise, delivering cross-sector tech innovation and proven results across industries.
#mindlogicx #knowledgeengineering #ai

Gitが「コードの履歴」を扱うように、
Dialogue Constellationは「思考と対話の履歴」を扱う。
人とAIのやり取りを1メッセージ=1コミットとして記録し、
知識や議論の変遷を再現できる構造です。
#KnowledgeEngineering #AIChatOS
_/_/_/_/_/ ٩(ˊᗜˋ*)و #LLM #AgentEngineer #Codex
#DialogConstellation という複雑なメッセージのインターネットを扱うことができる超いい基本クラスを書いた。これ一つあるだけでチャットソフトの全データも扱えるし、任意のファイル・フォルダ箇所においてチャットを構築することができる。
🚀 We’re Hiring
We’re looking for a (Senior) Knowledge Engineer (m/f/d)
🌍 Location: Lindau (HQ near Lake Constance) | Hybrid (up to 2 days remote)
💶 Salary: €65,000 – €85,000 gross/year
#KnowledgeEngineering #SemanticTech #AI #RDF #KnowledgeGraph #Python #TechJobsGermany
5/10
Expert Systems mimic human decision-making using rule-based logic. They’re used in diagnostics, legal analysis, and financial advising to provide consistent, knowledge-driven recommendations.
#ExpertSystems #AI #DecisionSupport #KnowledgeEngineering #SmartSolutions #Automation

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