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#knowledgerepresentation — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #knowledgerepresentation, aggregated by home.social.

  1. We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

    #KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

  2. We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

    #KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

  3. We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

    #KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

  4. We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

    #KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

  5. We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

    #KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

  6. 🔍 Lecture 01 — The Art of Understanding
    Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
    This opening lecture steps back from the algorithms and starts with first principles.
    It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
    #KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

  7. 🔍 Lecture 01 — The Art of Understanding
    Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
    This opening lecture steps back from the algorithms and starts with first principles.
    It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
    #KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

  8. 🔍 Lecture 01 — The Art of Understanding
    Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
    This opening lecture steps back from the algorithms and starts with first principles.
    It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
    #KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

  9. 🔍 Lecture 01 — The Art of Understanding
    Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
    This opening lecture steps back from the algorithms and starts with first principles.
    It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
    #KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

  10. 🔍 Lecture 01 — The Art of Understanding
    Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
    This opening lecture steps back from the algorithms and starts with first principles.
    It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
    #KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

  11. The recording of my @iswc_conf keynote is available online:

    Wikipedia and the Semantic Web -- 20 years of co-development, and the future

    Drawing on the roots of @wikipedia and the Semantic Web, how they influenced each other during the last two decades, leading to
    @wikidata and peeking forward to @wikifunctions and Abstract Wikipedia.

    #semanticWeb #abstractWikipedia #knowledge #knowledgeGraphs #knowledgerepresentation #wikipedia #wikidata #wikifunctions

    videolectures.net/videos/iswc2

  12. The recording of my @iswc_conf keynote is available online:

    Wikipedia and the Semantic Web -- 20 years of co-development, and the future

    Drawing on the roots of @wikipedia and the Semantic Web, how they influenced each other during the last two decades, leading to
    @wikidata and peeking forward to @wikifunctions and Abstract Wikipedia.

    #semanticWeb #abstractWikipedia #knowledge #knowledgeGraphs #knowledgerepresentation #wikipedia #wikidata #wikifunctions

    videolectures.net/videos/iswc2

  13. The recording of my @iswc_conf keynote is available online:

    Wikipedia and the Semantic Web -- 20 years of co-development, and the future

    Drawing on the roots of @wikipedia and the Semantic Web, how they influenced each other during the last two decades, leading to
    @wikidata and peeking forward to @wikifunctions and Abstract Wikipedia.

    #semanticWeb #abstractWikipedia #knowledge #knowledgeGraphs #knowledgerepresentation #wikipedia #wikidata #wikifunctions

    videolectures.net/videos/iswc2

  14. The recording of my @iswc_conf keynote is available online:

    Wikipedia and the Semantic Web -- 20 years of co-development, and the future

    Drawing on the roots of @wikipedia and the Semantic Web, how they influenced each other during the last two decades, leading to
    @wikidata and peeking forward to @wikifunctions and Abstract Wikipedia.

    videolectures.net/videos/iswc2

  15. The recording of my @iswc_conf keynote is available online:

    Wikipedia and the Semantic Web -- 20 years of co-development, and the future

    Drawing on the roots of @wikipedia and the Semantic Web, how they influenced each other during the last two decades, leading to
    @wikidata and peeking forward to @wikifunctions and Abstract Wikipedia.

    #semanticWeb #abstractWikipedia #knowledge #knowledgeGraphs #knowledgerepresentation #wikipedia #wikidata #wikifunctions

    videolectures.net/videos/iswc2

  16. What stands out in this call is the focus on explicit models, traceability, and responsibility, from provenance and uncertainty to reproducibility. Computational methods here strengthen interpretation, not replace it. #complexityscience #knowledgerepresentation #researchdata

  17. What stands out in this call is the focus on explicit models, traceability, and responsibility, from provenance and uncertainty to reproducibility. Computational methods here strengthen interpretation, not replace it. #complexityscience #knowledgerepresentation #researchdata

  18. What stands out in this call is the focus on explicit models, traceability, and responsibility, from provenance and uncertainty to reproducibility. Computational methods here strengthen interpretation, not replace it. #complexityscience #knowledgerepresentation #researchdata

  19. What stands out is the strong focus on methodological rigor and responsibility: formal models, explicit assumptions, and traceability (e.g. provenance, uncertainty, reproducibility) are treated as central to cultural research—not optional add-ons.
    The call also bridges complexity science, Digital Humanities, and Semantic Web approaches, emphasizing interoperability, evaluation, and governance.
    #complexityscience #knowledgerepresentation #researchdat

  20. What stands out is the strong focus on methodological rigor and responsibility: formal models, explicit assumptions, and traceability (e.g. provenance, uncertainty, reproducibility) are treated as central to cultural research—not optional add-ons.
    The call also bridges complexity science, Digital Humanities, and Semantic Web approaches, emphasizing interoperability, evaluation, and governance.
    #complexityscience #knowledgerepresentation #researchdat

  21. What stands out is the strong focus on methodological rigor and responsibility: formal models, explicit assumptions, and traceability (e.g. provenance, uncertainty, reproducibility) are treated as central to cultural research—not optional add-ons.
    The call also bridges complexity science, Digital Humanities, and Semantic Web approaches, emphasizing interoperability, evaluation, and governance.
    #complexityscience #knowledgerepresentation #researchdat

  22. What stands out is the strong focus on methodological rigor and responsibility: formal models, explicit assumptions, and traceability (e.g. provenance, uncertainty, reproducibility) are treated as central to cultural research—not optional add-ons.
    The call also bridges complexity science, Digital Humanities, and Semantic Web approaches, emphasizing interoperability, evaluation, and governance.
    #complexityscience #knowledgerepresentation #researchdat

  23. What stands out is the strong focus on methodological rigor and responsibility: formal models, explicit assumptions, and traceability (e.g. provenance, uncertainty, reproducibility) are treated as central to cultural research—not optional add-ons.
    The call also bridges complexity science, Digital Humanities, and Semantic Web approaches, emphasizing interoperability, evaluation, and governance.
    #complexityscience #knowledgerepresentation #researchdat

  24. 🚀 PMD core ontology (PMDco) v3.0.0 Release

    This release marks a major milestone for the #PMD working area Semantic Interoperability and reflects several years of joint conceptual work, implementation, discussion, and validation across projects and disciplines.

    GitHub: github.com/materialdigital/cor
    PMDco 3.0.0: materialdigital.github.io/core
    Docs: materialdigital.github.io/core

    #ontologies #materialsscience #materialdigital #AI #symbolicAI #knowledgerepresentation @fiz_karlsruhe @joerg @enorouzi @lysander07

  25. 🚀 PMD core ontology (PMDco) v3.0.0 Release

    This release marks a major milestone for the #PMD working area Semantic Interoperability and reflects several years of joint conceptual work, implementation, discussion, and validation across projects and disciplines.

    GitHub: github.com/materialdigital/cor
    PMDco 3.0.0: materialdigital.github.io/core
    Docs: materialdigital.github.io/core

    #ontologies #materialsscience #materialdigital #AI #symbolicAI #knowledgerepresentation @fiz_karlsruhe @joerg @enorouzi @lysander07

  26. 🚀 PMD core ontology (PMDco) v3.0.0 Release

    This release marks a major milestone for the #PMD working area Semantic Interoperability and reflects several years of joint conceptual work, implementation, discussion, and validation across projects and disciplines.

    GitHub: github.com/materialdigital/cor
    PMDco 3.0.0: materialdigital.github.io/core
    Docs: materialdigital.github.io/core

    #ontologies #materialsscience #materialdigital #AI #symbolicAI #knowledgerepresentation @fiz_karlsruhe @joerg @enorouzi @lysander07

  27. 🚀 PMD core ontology (PMDco) v3.0.0 Release

    This release marks a major milestone for the #PMD working area Semantic Interoperability and reflects several years of joint conceptual work, implementation, discussion, and validation across projects and disciplines.

    GitHub: github.com/materialdigital/cor
    PMDco 3.0.0: materialdigital.github.io/core
    Docs: materialdigital.github.io/core

    #ontologies #materialsscience #materialdigital #AI #symbolicAI #knowledgerepresentation @fiz_karlsruhe @joerg @enorouzi @lysander07

  28. 🚀 PMD core ontology (PMDco) v3.0.0 Release

    This release marks a major milestone for the #PMD working area Semantic Interoperability and reflects several years of joint conceptual work, implementation, discussion, and validation across projects and disciplines.

    GitHub: github.com/materialdigital/cor
    PMDco 3.0.0: materialdigital.github.io/core
    Docs: materialdigital.github.io/core

    #ontologies #materialsscience #materialdigital #AI #symbolicAI #knowledgerepresentation @fiz_karlsruhe @joerg @enorouzi @lysander07

  29. Call for Posters: DiTraRe Symposium 2025 on the Digitalization of research.
    deadline: Oct 17, 2025
    CfP: easychair.org/cfp/DiTraRe2025

    Topics:
    - #KnowledgeRepresentation and #AI
    - Ethical and legal challenges
    - #Research #Infrastructures
    - Impact on #Science and #Society
    - #SmartData acquisition
    - AI-based knowledge realms
    - Publication cultures

    #digitalization #knowledgegraphs #cfp ##ditrare #aiethics #society #digitalhumanities @fiz_karlsruhe @KIT_Karlsruhe @ITAS @AnnaJacyszyn @Feelix @lysander07

  30. Call for Posters: DiTraRe Symposium 2025 on the Digitalization of research.
    deadline: Oct 17, 2025
    CfP: easychair.org/cfp/DiTraRe2025

    Topics:
    - #KnowledgeRepresentation and #AI
    - Ethical and legal challenges
    - #Research #Infrastructures
    - Impact on #Science and #Society
    - #SmartData acquisition
    - AI-based knowledge realms
    - Publication cultures

    #digitalization #knowledgegraphs #cfp ##ditrare #aiethics #society #digitalhumanities @fiz_karlsruhe @KIT_Karlsruhe @ITAS @AnnaJacyszyn @Feelix @lysander07

  31. Call for Posters: DiTraRe Symposium 2025 on the Digitalization of research.
    deadline: Oct 17, 2025
    CfP: easychair.org/cfp/DiTraRe2025

    Topics:
    - #KnowledgeRepresentation and #AI
    - Ethical and legal challenges
    - #Research #Infrastructures
    - Impact on #Science and #Society
    - #SmartData acquisition
    - AI-based knowledge realms
    - Publication cultures

    #digitalization #knowledgegraphs #cfp ##ditrare #aiethics #society #digitalhumanities @fiz_karlsruhe @KIT_Karlsruhe @ITAS @AnnaJacyszyn @Feelix @lysander07

  32. Call for Posters: DiTraRe Symposium 2025 on the Digitalization of research.
    deadline: Oct 17, 2025
    CfP: easychair.org/cfp/DiTraRe2025

    Topics:
    - #KnowledgeRepresentation and #AI
    - Ethical and legal challenges
    - #Research #Infrastructures
    - Impact on #Science and #Society
    - #SmartData acquisition
    - AI-based knowledge realms
    - Publication cultures

    #digitalization #knowledgegraphs #cfp ##ditrare #aiethics #society #digitalhumanities @fiz_karlsruhe @KIT_Karlsruhe @ITAS @AnnaJacyszyn @Feelix @lysander07

  33. Call for Posters: DiTraRe Symposium 2025 on the Digitalization of research.
    deadline: Oct 17, 2025
    CfP: easychair.org/cfp/DiTraRe2025

    Topics:
    - #KnowledgeRepresentation and #AI
    - Ethical and legal challenges
    - #Research #Infrastructures
    - Impact on #Science and #Society
    - #SmartData acquisition
    - AI-based knowledge realms
    - Publication cultures

    #digitalization #knowledgegraphs #cfp ##ditrare #aiethics #society #digitalhumanities @fiz_karlsruhe @KIT_Karlsruhe @ITAS @AnnaJacyszyn @Feelix @lysander07

  34. Since the #semanticWeb was introduced almost 25 years ago, many have dismissed it as a failure.

    Charles Ivie shows that the #RDF standard and the #knowledgeRepresentation technology built on it have actually been quite successful.

    More than half of the world's web pages now share semantic annotations, and the widespread adoption of knowledge graphs in enterprises and media companies is only growing as #enterpriseAI architectures mature.

    knowledgegraphinsights.com/cha

  35. Since the #semanticWeb was introduced almost 25 years ago, many have dismissed it as a failure.

    Charles Ivie shows that the #RDF standard and the #knowledgeRepresentation technology built on it have actually been quite successful.

    More than half of the world's web pages now share semantic annotations, and the widespread adoption of knowledge graphs in enterprises and media companies is only growing as #enterpriseAI architectures mature.

    knowledgegraphinsights.com/cha

  36. Since the #semanticWeb was introduced almost 25 years ago, many have dismissed it as a failure.

    Charles Ivie shows that the #RDF standard and the #knowledgeRepresentation technology built on it have actually been quite successful.

    More than half of the world's web pages now share semantic annotations, and the widespread adoption of knowledge graphs in enterprises and media companies is only growing as #enterpriseAI architectures mature.

    knowledgegraphinsights.com/cha

  37. Since the #semanticWeb was introduced almost 25 years ago, many have dismissed it as a failure.

    Charles Ivie shows that the #RDF standard and the #knowledgeRepresentation technology built on it have actually been quite successful.

    More than half of the world's web pages now share semantic annotations, and the widespread adoption of knowledge graphs in enterprises and media companies is only growing as #enterpriseAI architectures mature.

    knowledgegraphinsights.com/cha

  38. Since the #semanticWeb was introduced almost 25 years ago, many have dismissed it as a failure.

    Charles Ivie shows that the #RDF standard and the #knowledgeRepresentation technology built on it have actually been quite successful.

    More than half of the world's web pages now share semantic annotations, and the widespread adoption of knowledge graphs in enterprises and media companies is only growing as #enterpriseAI architectures mature.

    knowledgegraphinsights.com/cha

  39. #til⁩ an overlooked ⁨#zettlelkasten⁩ educator.
    youtu.be/gQqrIxdDWWk⁩
    She clearly has years of experience ⁨#teaching⁩ and is the most concrete and methodical of the content creators on ⁨#knowledgerepresentation

    Reposting for folks in #HomeSchooling , #specialneeds and #adhd followers.

  40. #til⁩ an overlooked ⁨#zettlelkasten⁩ educator.
    youtu.be/gQqrIxdDWWk⁩
    She clearly has years of experience ⁨#teaching⁩ and is the most concrete and methodical of the content creators on ⁨#knowledgerepresentation

    Reposting for folks in #HomeSchooling , #specialneeds and #adhd followers.