#knowledgemanagement — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #knowledgemanagement, aggregated by home.social.
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Here is the paradox I keep running into.
A well exercised reading habit makes you better at using AI, because you can frame the input and judge the output. And AI is the easiest way to stop exercising it. Read the summary, skip the book.
Where do you draw your own line between using it and leaning on it?
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Here is the paradox I keep running into.
A well exercised reading habit makes you better at using AI, because you can frame the input and judge the output. And AI is the easiest way to stop exercising it. Read the summary, skip the book.
Where do you draw your own line between using it and leaning on it?
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Here is the paradox I keep running into.
A well exercised reading habit makes you better at using AI, because you can frame the input and judge the output. And AI is the easiest way to stop exercising it. Read the summary, skip the book.
Where do you draw your own line between using it and leaning on it?
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Here is the paradox I keep running into.
A well exercised reading habit makes you better at using AI, because you can frame the input and judge the output. And AI is the easiest way to stop exercising it. Read the summary, skip the book.
Where do you draw your own line between using it and leaning on it?
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Here is the paradox I keep running into.
A well exercised reading habit makes you better at using AI, because you can frame the input and judge the output. And AI is the easiest way to stop exercising it. Read the summary, skip the book.
Where do you draw your own line between using it and leaning on it?
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From my slip-box, written after a conversation with Claude: my thinking shapes the AI's response, and its response alters my thinking. A cognitive feedback loop.
The upside is a perspective other than my own. The catch is that it is roughly the human average, and research suggests work made by human and AI together is less diverse than work made by humans alone.
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From my slip-box, written after a conversation with Claude: my thinking shapes the AI's response, and its response alters my thinking. A cognitive feedback loop.
The upside is a perspective other than my own. The catch is that it is roughly the human average, and research suggests work made by human and AI together is less diverse than work made by humans alone.
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From my slip-box, written after a conversation with Claude: my thinking shapes the AI's response, and its response alters my thinking. A cognitive feedback loop.
The upside is a perspective other than my own. The catch is that it is roughly the human average, and research suggests work made by human and AI together is less diverse than work made by humans alone.
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From my slip-box, written after a conversation with Claude: my thinking shapes the AI's response, and its response alters my thinking. A cognitive feedback loop.
The upside is a perspective other than my own. The catch is that it is roughly the human average, and research suggests work made by human and AI together is less diverse than work made by humans alone.
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From my slip-box, written after a conversation with Claude: my thinking shapes the AI's response, and its response alters my thinking. A cognitive feedback loop.
The upside is a perspective other than my own. The catch is that it is roughly the human average, and research suggests work made by human and AI together is less diverse than work made by humans alone.
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Organisations rarely lack knowledge. They lack a reliable way to find and use it.
Could one secure corporate AI assistant connect documents, systems, processes and expertise across the enterprise?
https://medium.com/@chribonn/the-organisation-that-knows-what-it-knows-9ef1636c94fa
#EnterpriseAI #AIGovernance #TTMO #Medium #KnowledgeManagement #RAG
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📊 There’s plenty of data – what matters is what we learn from it.
Join our Galaxy Deep Dive to see how BlueSpice Galaxy turns wiki data into clear insights with spreadsheets, charts, and dashboards.
📅 Sept. 17, 2026
🕑 2–2:30 p.m. CEST
💻 Free & online👉 Register: https://bluespice.com/visualizing-data-in-the-wiki-with-spreadsheets-charts-and-dashboards/
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📊 There’s plenty of data – what matters is what we learn from it.
Join our Galaxy Deep Dive to see how BlueSpice Galaxy turns wiki data into clear insights with spreadsheets, charts, and dashboards.
📅 Sept. 17, 2026
🕑 2–2:30 p.m. CEST
💻 Free & online👉 Register: https://bluespice.com/visualizing-data-in-the-wiki-with-spreadsheets-charts-and-dashboards/
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Offloading to a technology is not, on its own, the problem.
Writing offloaded our memory and we spent the freed capacity on thinking. Turning speech into flat, concrete, written words forces you to think, so the trade paid for itself.
Generative AI offloads the thinking. So what do you spend the freed capacity on?
From this week's post: https://www.ctnet.co.uk/downsides-of-writing-ai/
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Offloading to a technology is not, on its own, the problem.
Writing offloaded our memory and we spent the freed capacity on thinking. Turning speech into flat, concrete, written words forces you to think, so the trade paid for itself.
Generative AI offloads the thinking. So what do you spend the freed capacity on?
From this week's post: https://www.ctnet.co.uk/downsides-of-writing-ai/
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Offloading to a technology is not, on its own, the problem.
Writing offloaded our memory and we spent the freed capacity on thinking. Turning speech into flat, concrete, written words forces you to think, so the trade paid for itself.
Generative AI offloads the thinking. So what do you spend the freed capacity on?
From this week's post: https://www.ctnet.co.uk/downsides-of-writing-ai/
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Offloading to a technology is not, on its own, the problem.
Writing offloaded our memory and we spent the freed capacity on thinking. Turning speech into flat, concrete, written words forces you to think, so the trade paid for itself.
Generative AI offloads the thinking. So what do you spend the freed capacity on?
From this week's post: https://www.ctnet.co.uk/downsides-of-writing-ai/
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Offloading to a technology is not, on its own, the problem.
Writing offloaded our memory and we spent the freed capacity on thinking. Turning speech into flat, concrete, written words forces you to think, so the trade paid for itself.
Generative AI offloads the thinking. So what do you spend the freed capacity on?
From this week's post: https://www.ctnet.co.uk/downsides-of-writing-ai/
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🔐 Don’t just protect your systems. Protect your knowledge. 🔐
From October 27–29, 2026, we’ll be at it-sa in Nuremberg. Meet us in hall 7 at booth 352!
At the event, we’ll be discussing topics such as:
➡️ Migration to BlueSpice
➡️ BlueSpice Galaxy👉 Find all the information here: https://bluespice.com/bluespice-at-it-sa/
#itsa2026 #Cybersecurity #ITSecurity #KnowledgeManagement #BlueSpice #BlueSpiceGalaxy #Migration #OpenSource
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Same question, different user, different answer, by design!
An admin asks about executive pay and gets a cited answer. A regular employee asks the same and honestly gets none: your #MediaWiki chatbot only ever draws on pages the asking user may read.
No separate permission system: your wiki's existing permissions decide what it may use to answer. Confidential pages stay confidential.
Learn more at https://professional.wiki/en/mediawiki-ai-assistant
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BlueSpice at Smart Country Convention 2026
📅 Oct 13–15, 2026
📍 Messe Berlin | Hall 25 | Booth 224Discover how BlueSpice Galaxy, AI and modern migration solutions are shaping the future of knowledge management for the public sector.
We look forward to seeing you in Berlin! 🤝
https://bluespice.com/bluespice-at-the-smart-country-convention-2026/#SCCon26 #KnowledgeManagement #DigitalGovernment #AI #BlueSpice
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Anne-Laure Le Cunff offers five tips for avoiding cognitive debt with AI. Keep thinking, let it challenge you, write the first draft yourself, watch for over-reliance, keep reflecting.
All reasonable. I am not convinced they are enough on their own, because none of them stop you offloading the very tasks you need to do in order to learn.
My addition is metacognition, and a Zettelkasten to practise it in: https://www.ctnet.co.uk/cognitive-debt-ai-offloading/
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💡 Knowledge is only valuable if it can be found quickly. 💡
In our next Galaxy Deep Dive webinar, we’ll show you exactly how BlueSpice Galaxy helps you organize knowledge clearly and make it accessible faster.
📅 September 2, 2026
🕚 2:00 p.m. – 2:30 p.m.
💻 Free and online👉 Register now: https://bluespice.com/find-information-faster-with-a-structure-that-works/
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Choose the AI behind your wiki's answers!
Configure your #MediaWiki chatbot via the admin panel: pick the provider, from Anthropic and OpenAI to the French Mistral and Swiss Apertus, or your own self-hosted model. Tune the chat features and apply your branding.
Learn more at https://professional.wiki/en/mediawiki-ai-assistant
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I ran the second quarterly analysis of my Obsidian vault this month, three months on from the first one.
2,064 permanent notes, 595 literature notes, and a processing backlog that shrank for the first time since I started measuring. Claude also flagged the concepts I keep linking to but have never written up.
Full review here: https://www.ctnet.co.uk/quarterly-vault-review-q3/
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Part 3 of my 'How I use Obsidian with Claude' series is live.
This one covers: trying the new Fable model for my quarterly vault review, letting Buffer draft my social posts automatically, and how an 'intent' property finally stopped my notes backlog growing.
If you missed Part 2, it's here too: https://www.ctnet.co.uk/claude-obsidian-workflow-pkm-pt2/
#PKM #Zettelkasten #Obsidian #AI #KnowledgeManagement #SecondBrain
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Do you run periodic reviews of your notes system?
I used Claude's new Fable model for my second quarterly vault review this time, instead of Opus. It felt noticeably quicker, and it picked up on a different way I'd started working with my notes since the last review, comparing the two.
Made me realise how much giving AI proper context on your vault actually matters.
More here: https://www.ctnet.co.uk/claude-obsidian-workflow-pkm-pt3/
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New post: Part 3 of how I use Claude alongside my Obsidian PKM.
This time: trying the new Fable model for my quarterly vault review, letting Claude draft my social media posts automatically, and how an 'intent' property finally stopped my notes backlog growing.
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📣 The new versions of BlueSpice 5.2.6 and 5.1.10 are now available for download.
https://bluespice.com/download/Full details on the included improvements and bug fixes can be found in our Helpdesk:
➡️ https://en.wiki.bluespice.com/wiki/Setup:Release_Notes#MediaWiki #BlueSpice #Wiki #Release #Patch #EnterpriseWiki #KnowledgeManagement #KnowledgeBase #Documentation #Changelog
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If Cognitive Mirror Syndrome has you worried (and it should, a bit), this new post connects to two things I've written before:
My AI Knowledge Framework series, which sets out how I use AI deliberately rather than reactively.
And my post on whether a PKM practice like a Zettelkasten can protect your cognitive abilities.
New post: https://www.ctnet.co.uk/cognitive-mirror-syndrome/
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🔎 What's Next for BlueSpice? 🔍
Our technical roadmap provides an overview of current and planned development steps – from new features and improvements to large-scale setups, connectors, and integrations.
The roadmap shows what we’re currently working on and how we’re technically advancing BlueSpice with Galaxy.
👉 An overview of all planned development steps:
https://bluespice.com/roadmap/#BlueSpice #BlueSpiceGalaxy #Roadmap #KnowledgeManagement #EnterpriseWiki #OpenSource
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🌌 Our new webinar series, Galaxy Deep Dives, is kicking off! 🌌
In concise 30-minute webinars, we’ll showcase new and improved features of BlueSpice Galaxy.
We’ll kick things off on August 12, 2026, with the webinar 🪐BlueSpice Galaxy – The Future of Enterprise Knowledge Management🪐.
👉 Register now: https://bluespice.com/bluespice-galaxy-the-future-of-enterprise-knowledge-management/
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📣 Patch Day 📣 BlueSpice 5.2.5 and 5.1.9 are now available for download: https://bluespice.com/download/
Details on included improvements and bug fixes in our Helpdesk:
➡️ https://en.wiki.bluespice.com/wiki/Setup:Release_Notes#MediaWiki #BlueSpice #Wiki #EnterpriseWiki #KnowledgeManagement #KnowledgeBase #Documentation
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🚨BlueSpice is bringing Galaxy to Berlin🚨
AI needs more than just data. AI needs structured knowledge.
That’s exactly what our booth is all about: BlueSpice Galaxy. See firsthand how companies connect, structure, and make knowledge usable for AI.📍 June 30 & July 1 | Messe Berlin, Hall 1.2, Booth 26
🎤 Live presentations daily at 10:00 a.m. & 2:00 p.m.
🎟️ Tickets & more information: https://bluespice.com/bluespice-at-gitex-2026/ -
⏳ Only two weeks left until GITEX AI Europe 2026⏳
Meet us on June 30 and July 1, 2026 in Hall 1.2, Booth 26.
The focus will be on modern knowledge management, AI-powered knowledge databases, and the public debut of BlueSpice Galaxy.
🎤 There will also be daily short presentations on-site with Richard Heigl, CEO of Hallo Welt! GmbH, at 10:00 AM and 2:00 PM each day.
➡️https://bluespice.com/bluespice-at-gitex-2026/
#BlueSpice #GITEXAIEurope #GITEX2026 #KnowledgeManagement #AI #HalloWelt
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📣 Today is Patch Day 📣
BlueSpice 5.2.4 and 5.1.8 are now available for download.
https://bluespice.com/download/Find more information about included improvements and bug fixes in our helpdesk:
➡️ https://en.wiki.bluespice.com/wiki/Setup:Release_Notes#MediaWiki #BlueSpice #Wiki #Release #Patch #EnterpriseWiki #KnowledgeManagement #KnowledgeBase #Documentation #Changelog
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🎫Don’t have a ticket for #GITEXAIEurope 2026 yet?🎫
Now is the perfect time to get one: GITEX AI Europe will bring together companies, technology providers, and decision-makers in the fields of AI, digitalization, and innovation in Berlin on June 30 and July 1, 2026.
➡️ Get your ticket with our Code I35Z1L and meet us at #GITEXEurope in Berlin (Hall 1.2, Booth 26): https://visit.gitexeurope.com/
#BlueSpice #BlueSpiceGalaxy #KnowledgeManagement #EnterpriseWiki #AI #DigitalTransformation
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✨ AI needs more than just good prompts. It needs good knowledge. ✨
At GITEX AI Europe 2026 in Berlin (June 30 & July 1, hall 1.2, booth 26) we’ll show how companies can lay the groundwork for successful AI applications: with structured and discoverable knowledge.💡BlueSpice helps organizations centrally document, connect, and make knowledge usable.
More: https://bluespice.com/bluespice-at-gitex-2026/
#BlueSpice #GITEXAIEurope #KnowledgeManagement #EnterpriseWiki #AI #DigitalTransformation
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🏝️Companies don’t think in terms of island solutions. Why should wikis?🏝️
At GITEX AI Europe 2026, we’ll be unveiling BlueSpice Galaxy for the first time: our new concept for connected knowledge management.🪐
Meet us in Berlin and experience BlueSpice Galaxy live for the first time!
🔍 You’ll find us in Hall 1.2 at Booth 26.Find more information here: https://bluespice.com/bluespice-at-gitex-2026/
#BlueSpice #BlueSpiceGalaxy #GITEXAIEurope #KnowledgeManagement #EnterpriseWiki #AI
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🙌Accessibility is a team effort🙌
In an interview with Golem, our CEO Richard Heigl talks about how we at BlueSpice “failed miserably” in our first accessibility audits – and what we learned from it.
➡️ Click here for Golem’s “Chefs von Devs” newsletter (German): https://www.golem.de/news/richard-heigl-ueber-barrierefreiheit-wir-sind-bei-den-ersten-audits-glatt-durchgefallen-2605-208298.html
#BlueSpice #Accessibility #DigitalInclusion #AccessibleSoftware #UX #BITV #WCAG #OpenSource #KnowledgeManagement
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⚡A bolder digital Europe is open – BlueSpice at GITEX AI Europe 2026⚡
On June 30 and July 1, 2026, we will be presenting 🪐BlueSpice Galaxy🪐 for the first time at GITEX EUROPE in Berlin!In our presentations, we’ll offer initial insights into the concept behind our new knowledge universe.💪
We look forward to connecting with you in Hall 1.2, Booth 26!
#BlueSpice #BlueSpiceGalaxy #GITEXAIEurope #GITEXEurope #KnowledgeManagement #EnterpriseWiki #AI #DigitalTransformation
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👩🚀The Next-Generation Knowledge Universe: BlueSpice Galaxy 👩🚀
BlueSpice Galaxy isn’t just another update – it’s a completely new approach to how corporate knowledge is connected, discovered, and utilized.
What’s new?
🪐 Intuitive knowledge structuring
🌠 Highly scalable, interconnected knowledge spaces
🤖 AI support that really helpsFind out more👉 https://bluespice.com/bluespice-galaxy/
#BlueSpice #KnowledgeManagement #AI #DigitalWorkplace #EnterpriseWiki #FutureOfWork #Galaxy
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🤝We are excited about our partnership with Linux Systems Consulting AG🤝
Together, we help companies in Germany and Austria successfully implement modern knowledge management with BlueSpice – from licensing consulting📄 to technical implementation⚙️ and ongoing operations💡.
Together, we create powerful and future-proof solutions for documentation, collaboration, and knowledge management.🎉
#BlueSpice #LinuxSystemsConsulting #OpenSource #KnowledgeManagement #Documentation #Collaboration
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Knowledge lost when experts leave? 🤯
Our partner Intrafind shows how #DigitalClones & #AI assistants preserve #knowledge, provide answers & speed up onboarding.
🎤 Franz Kögl
📍Hall 16, D10
🕒 April 21 & 22 | 2:00 PM -
🔄 Rethinking Knowledge Platforms: Migrating from Confluence 🔄
Many companies are considering migrating their knowledge platforms.
In our presentation at the Hannover Messe, we’ll show you how to approach a secure and structured migration. You’ll also learn why BlueSpice, as an open-source platform, is the ideal, scalable alternative for your company.
📍 Hall 16, Booth D10
🕒 Dates:
April 20 | 3:00 PM
April 21–23 | 11:00 AM#Migration #KnowledgeManagement #BlueSpice #OpenSource #HannoverMesse
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We are excited about our partnership with Linova Software GmbH.
Your benefits 🎯
✅ Centralized platform for processes, knowledge and so much more
✅ Integrated end-to-end system for audits, documentation, and knowledge management
✅ Lean, audit-ready IMS and ISMS
✅ Structured software and requirements documentationLearn more here: https://bluespice.com/hallo-welt-and-linova-are-strengthening-digital-knowledge-management/
#BlueSpice #Linova #KnowledgeManagement #IMS #ISMS #Audit #Digitalization
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If you are going to the DDD conference in Melbourne tomorrow, head over to the Write The Docs booth and say hi. See if you can solve our 3 minute BrickDocs Challenge or join in some Docs Bingo.
#dddmelb #WriteTheDocs #TechWriting #TechnicalWriting #KnowledgeManagementDDD Melbourne | 21st February 2026
https://www.dddmelbourne.com/ -
Domain Ontologies: Indispensable for Knowledge Graph Construction
AI slop is all around and increasingly extraction of useful information will face difficulties as we start to feed more noise into the already noisy world of knowledge. We are in an era of unprecedented data abundance, yet this deluge of information often lacks the structure necessary to derive meaningful insights. Knowledge graphs (KGs), with their ability to represent entities and their relationships as interconnected nodes and edges, have emerged as a powerful tool for managing and leveraging complex data. However, the efficacy of a KG is critically dependent on the underlying structure provided by domain ontologies. These ontologies, which are formal, machine-readable conceptualizations of a specific field of knowledge, are not merely useful, but essential for the creation of robust and insightful KGs. Let’s explore the role that domain ontologies play in scaffolding KG construction, drawing on various fields such as AI, healthcare, and cultural heritage, to illuminate their importance.
Vassily Kandinsky, 1913 – Composition VII (1913)
According to Kandinsky, this is the most complex piece he ever painted.At its core, an ontology is a formal representation of knowledge within a specific domain, providing a structured vocabulary and defining the semantic relationships between concepts. In the context of KGs, ontologies serve as the blueprint that defines the types of nodes (entities) and edges (relationships) that can exist within the graph. Without this foundational structure, a KG would be a mere collection of isolated data points with limited utility. The ontology ensures that the KG’s data is not only interconnected but also semantically interoperable. For example, in the biomedical domain, an ontology like the Chemical Entities of Biological Interest (ChEBI) provides a standardized way of representing molecules and their relationships, which is essential for building biomedical KGs. Similarly, in the cultural domain, an ontology provides a controlled vocabulary to define the entities, such as artworks, artists, and historical events, and their relationships, thus creating a consistent representation of cultural heritage information.
One of the primary reasons domain ontologies are crucial for KGs is their role in ensuring data consistency and interoperability. Ontologies provide unique identifiers and clear definitions for each concept, which helps in aligning data from different sources and avoiding ambiguities. Consider, for example, a healthcare KG that integrates data from various clinical trials, patient records, and research publications. Without a shared ontology, terms like “cancer” or “hypertension” may be interpreted differently across these data sets. The use of ontologies standardizes the representation of these concepts, thus allowing for effective integration and analysis. This not only enhances the accuracy of the KG but also makes the information more accessible and reusable. Furthermore, using ontologies that follow the FAIR (Findable, Accessible, Interoperable, Reusable) principles facilitates data integration, unification, and information sharing, essential for building robust KGs.
Moreover, ontologies facilitate the application of advanced AI methods to unlock new knowledge. They support both deductive reasoning to infer new knowledge and provide structured background knowledge for machine learning. In the context of drug discovery, for instance, a KG built on a biomedical ontology can help identify potential drug targets by connecting genes, proteins, and diseases through clearly defined relationships. This structured approach to data also enables the development of explainable AI models, which are critical in fields like medicine where the decision-making process must be transparent and interpretable. The ontology-grounded KGs can then be used to generate hypotheses that can be validated through manual review, in vitro experiments, or clinical studies, highlighting the utility of ontologies in translating complex data into actionable knowledge.
Despite their many advantages, domain ontologies are not without their challenges. One major hurdle is the lack of direct integration between data and ontologies, meaning that most ontologies are abstract knowledge models not designed to contain or integrate data. This necessitates the use of (semi-)automated approaches to integrate data with the ontological knowledge model, which can be complex and resource-intensive. Additionally, the existence of multiple ontologies within a domain can lead to semantic inconsistencies that impede the construction of holistic KGs. Integrating different ontologies with overlapping information may result in semantic irreconcilability, making it difficult to reuse the ontologies for the purpose of KG construction. Careful planning is therefore required when choosing or building an ontology.
As we move forward, the development of integrated, holistic solutions will be crucial to unlocking the full potential of domain ontologies in KG construction. This means creating methods for integrating multiple ontologies, ensuring data quality and credibility, and focusing on semantic expansion techniques to leverage existing resources. Furthermore, there needs to be a greater emphasis on creating ontologies with the explicit purpose of instantiating them, and storing data directly in graph databases. The integration of expert knowledge into KG learning systems, by using ontological rules, is crucial to ensure that KGs not only capture data, but also the logical patterns, inferences, and analytic approaches of a specific domain.
Domain ontologies will prove to be the key to building robust and useful KGs. They provide the necessary structure, consistency, and interpretability that enables AI systems to extract valuable insights from complex data. By understanding and addressing the challenges associated with ontology design and implementation, we can harness the power of KGs to solve complex problems across diverse domains, from healthcare and science to culture and beyond. The future of knowledge management lies not just in the accumulation of data but in the development of intelligent, ontologically-grounded systems that can bridge the gap between information and meaningful understanding.
References
- Al-Moslmi, T., El Alaoui, I., Tsokos, C.P., & Janjua, N. (2021). Knowledge graph construction approaches: A survey of recent research works. arXiv preprint. https://arxiv.org/abs/2011.00235
- Chandak, P., Huang, K., & Zitnik, M. (2023). PrimeKG: A multimodal knowledge graph for precision medicine. Scientific Data. https://www.nature.com/articles/s41597-023-01960-3
- Gilbert, S., & others. (2024). Augmented non-hallucinating large language models using ontologies and knowledge graphs in biomedicine. npj Digital Medicine. https://www.nature.com/articles/s41746-024-01081-0
- Guzmán, A.L., et al. (2022). Applications of Ontologies and Knowledge Graphs in Cancer Research: A Systematic Review. Cancers, 14(8), 1906. https://www.mdpi.com/2072-6694/14/8/1906
- Hura, A., & Janjua, N. (2024). Constructing domain-specific knowledge graphs from text: A case study on subprime mortgage crisis. Semantic Web Journal. https://www.semantic-web-journal.net/content/constructing-domain-specific-knowledge-graphs-text-case-study-subprime-mortgage-crisis
- Kilicoglu, H., et al. (2024). Towards better understanding of biomedical knowledge graphs: A survey. arXiv preprint. https://arxiv.org/abs/2402.06098
- Noy, N.F., & McGuinness, D.L. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. Semantic Scholar. https://www.semanticscholar.org/paper/Ontology-Development-101%3A-A-Guide-to-Creating-Your-Noy/c15cf32df98969af5eaf85ae3098df6d2180b637
- Taneja, S.B., et al. (2023). NP-KG: A knowledge graph for pharmacokinetic natural product-drug interaction discovery. Journal of Biomedical Informatics. https://www.sciencedirect.com/science/article/pii/S153204642300062X
- Zhao, X., & Han, Y. (2023). Architecture of Knowledge Graph Construction. Semantic Scholar. https://www.semanticscholar.org/paper/Architecture-of-Knowledge-Graph-Construction-Zhao-Han/dcd600619962d5c1f1cfa08a85d0be43a626b301
#AIInHealthcare #ArtificialIntelligence #BiomedicalOntologies #CulturalHeritageData #DataIntegration #DataInteroperability #DomainOntologies #DrugDiscovery #ExplainableAI #FAIRPrinciples #GraphDatabases #KnowledgeGraphs #KnowledgeManagement #LLMs #Ontology #OntologyDesign #OntologyDevelopment #OntologyDrivenAI #SemanticRelationships #SemanticWeb
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Essentials - die Wissenssammlung von Dr. Ulrich Kampffmeyer zu Information Management & Information Governance. 30 Jahre Beiträge von PROJECT CONSULT.
https://bit.ly/Kff-Wissen
#ECM #EIM #IIM #DMS #ERM #RMS #BPM #RPA #AI #KI #KM #KnowledgeManagement #InformationManagement #InformationGovernance #DocumentManagement #Collaboration #Preservation #Digital #Digitalisierung #WCM #CMS #ChangeManagement #ProjectManagement #GRC #Compliance -
Shelf.io closes huge $52.5M Series B after posting 4x ARR growth in the last year - Covering public companies can be a bit of a drag. They grow some modest amount eac... - http://feedproxy.google.com/~r/Techcrunch/~3/0qOxFK2BDlw/ #artificialintelligence #knowledgemanagement #insightpartners #machinelearning #fundings&exits #tigerglobal #startups #shelf #tc