[[edit source](/w/index.php?title=Semantic_Web&action=edit&section=8 "Edit section's source code: Beyond Web 3.0")] The next generation of the Web is often termed Web 4.0, but its definition is not clear. According to some sources, it is a Web that involves [artificial intelligence](https://en.wikipedia.org/wiki/Artificial_intelligence "Artificial intelligence"),[[30]](#cite_note-30) the [internet of things](https://en.wikipedia.org/wiki/Internet_of_things "Internet of things"), [pervasive computing](https://en.wikipedia.org/wiki/Pervasive_computing "Pervasive computing"), [ubiquitous computing](https://en.wikipedia.org/wiki/Ubiquitous_computing "Ubiquitous computing") and the [Web of Things](https://en.wikipedia.org/wiki/Web_of_Things "Web of Things") among other concepts.[[31]](#cite_note-31) According to the European Union, Web 4.0 is "the expected fourth generation of the World Wide Web. Using advanced artificial and ambient intelligence, the internet of things, trusted blockchain transactions, virtual worlds and XR capabilities, digital and real objects and environments are fully integrated and communicate with each other, enabling truly intuitive, immersive experiences, seamlessly blending the physical and digital worlds".[[32]](#cite_note-32) Challenges ---------- [[edit source](/w/index.php?title=Semantic_Web&action=edit&section=9 "Edit section's source code: Challenges")] Some of the challenges for the Semantic Web include vastness, vagueness, uncertainty, inconsistency, and deceit. [Automated reasoning systems](https://en.wikipedia.org/wiki/Automated_reasoning_system "Automated reasoning system") will have to deal with all of these issues in order to deliver on the promise of the Semantic Web. * Vastness: The World Wide Web contains many billions of pages. The [SNOMED CT](https://en.wikipedia.org/wiki/SNOMED_CT "SNOMED CT") [medical terminology](https://en.wikipedia.org/wiki/Medical_terminology "Medical terminology") [ontology](https://en.wikipedia.org/wiki/Ontology_(information_science) "Ontology (information science)") alone contains 370,000 [class](https://en.wikipedia.org/wiki/Class_(programming) "Class (programming)") names, and existing technology has not yet been able to eliminate all semantically duplicated terms. Any automated reasoning system will have to deal with truly huge inputs. * Vagueness: These are imprecise concepts like "young" or "tall". This arises from the vagueness of user queries, of concepts represented by content providers, of matching query terms to provider terms and of trying to combine different [knowledge bases](https://en.wikipedia.org/wiki/Knowledge_base "Knowledge base") with overlapping but subtly different concepts. [Fuzzy logic](https://en.wikipedia.org/wiki/Fuzzy_logic "Fuzzy logic") is the most common technique for dealing with vagueness. * Uncertainty: These are precise concepts with uncertain values. For example, a patient might present a set of symptoms that correspond to a number of different distinct diagnoses each with a different probability. [Probabilistic](https://en.wikipedia.org/wiki/Probabilistic_logic "Probabilistic logic") reasoning techniques are generally employed to address uncertainty. * Inconsistency: These are logical contradictions that will inevitably arise during the development of large ontologies, and when ontologies from separate sources are combined. Deductive reasoning fails catastrophically when faced with inconsistency, because ["anything follows from a contradiction"](https://en.wikipedia.org/wiki/Principle_of_explosion "Principle of explosion"). [Defeasible reasoning](https://en.wikipedia.org/wiki/Defeasible_reasoning "Defeasible reasoning") and [paraconsistent reasoning](https://en.wikipedia.org/wiki/Paraconsistent_logic "Paraconsistent logic") are two techniques that can be employed to deal with inconsistency. * Deceit: This is when the producer of the information is intentionally misleading the consumer of the information. [Cryptography](https://en.wikipedia.org/wiki/Cryptography "Cryptography") techniques are currently utilized to alleviate this threat. By providing a means to determine the information's integrity, including that which relates to the identity of the entity that produced or published the information, however [credibility](https://en.wikipedia.org/wiki/Credibility "Credibility") issues still have to be addressed in cases of potential deceit. This list of challenges is illustrative rather than exhaustive, and it focuses on the challenges to the "unifying logic" and "proof" layers of the Semantic Web. The World Wide Web Consortium (W3C) Incubator Group for Uncertainty Reasoning for the World Wide Web[[33]](#cite_note-33) (URW3-XG) final report lumps these problems together under the single heading of "uncertainty".[[34]](#cite_note-34) Many of the techniques mentioned here will require extensions to the Web Ontology Language (OWL) for example to annotate conditional probabilities. This is an area of active research.[[35]](#cite_note-35) Standards --------- [[edit source](/w/index.php?title=Semantic_Web&action=edit&section=10 "Edit section's source code: Standards")] Standardization for Semantic Web in the context of Web 3.0 is under the care of W3C.[[36]](#cite_note-36)

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  "text": "[[edit source](/w/index.php?title=Semantic_Web&action=edit&section=8 \"Edit section's source code: Beyond Web 3.0\")]\n\nThe next generation of the Web is often termed Web 4.0, but its definition is not clear. According to some sources, it is a Web that involves [artificial intelligence](https://en.wikipedia.org/wiki/Artificial_intelligence \"Artificial intelligence\"),[[30]](#cite_note-30) the [internet of things](https://en.wikipedia.org/wiki/Internet_of_things \"Internet of things\"), [pervasive computing](https://en.wikipedia.org/wiki/Pervasive_computing \"Pervasive computing\"), [ubiquitous computing](https://en.wikipedia.org/wiki/Ubiquitous_computing \"Ubiquitous computing\") and the [Web of Things](https://en.wikipedia.org/wiki/Web_of_Things \"Web of Things\") among other concepts.[[31]](#cite_note-31) According to the European Union, Web 4.0 is \"the expected fourth generation of the World Wide Web. Using advanced artificial and ambient intelligence, the internet of things, trusted blockchain transactions, virtual worlds and XR capabilities, digital and real objects and environments are fully integrated and communicate with each other, enabling truly intuitive, immersive experiences, seamlessly blending the physical and digital worlds\".[[32]](#cite_note-32)\n\nChallenges\n----------\n\n[[edit source](/w/index.php?title=Semantic_Web&action=edit&section=9 \"Edit section's source code: Challenges\")]\n\nSome of the challenges for the Semantic Web include vastness, vagueness, uncertainty, inconsistency, and deceit. [Automated reasoning systems](https://en.wikipedia.org/wiki/Automated_reasoning_system \"Automated reasoning system\") will have to deal with all of these issues in order to deliver on the promise of the Semantic Web.\n\n* Vastness: The World Wide Web contains many billions of pages. The [SNOMED CT](https://en.wikipedia.org/wiki/SNOMED_CT \"SNOMED CT\") [medical terminology](https://en.wikipedia.org/wiki/Medical_terminology \"Medical terminology\") [ontology](https://en.wikipedia.org/wiki/Ontology_(information_science) \"Ontology (information science)\") alone contains 370,000 [class](https://en.wikipedia.org/wiki/Class_(programming) \"Class (programming)\") names, and existing technology has not yet been able to eliminate all semantically duplicated terms. Any automated reasoning system will have to deal with truly huge inputs.\n* Vagueness: These are imprecise concepts like \"young\" or \"tall\". This arises from the vagueness of user queries, of concepts represented by content providers, of matching query terms to provider terms and of trying to combine different [knowledge bases](https://en.wikipedia.org/wiki/Knowledge_base \"Knowledge base\") with overlapping but subtly different concepts. [Fuzzy logic](https://en.wikipedia.org/wiki/Fuzzy_logic \"Fuzzy logic\") is the most common technique for dealing with vagueness.\n* Uncertainty: These are precise concepts with uncertain values. For example, a patient might present a set of symptoms that correspond to a number of different distinct diagnoses each with a different probability. [Probabilistic](https://en.wikipedia.org/wiki/Probabilistic_logic \"Probabilistic logic\") reasoning techniques are generally employed to address uncertainty.\n* Inconsistency: These are logical contradictions that will inevitably arise during the development of large ontologies, and when ontologies from separate sources are combined. Deductive reasoning fails catastrophically when faced with inconsistency, because [\"anything follows from a contradiction\"](https://en.wikipedia.org/wiki/Principle_of_explosion \"Principle of explosion\"). [Defeasible reasoning](https://en.wikipedia.org/wiki/Defeasible_reasoning \"Defeasible reasoning\") and [paraconsistent reasoning](https://en.wikipedia.org/wiki/Paraconsistent_logic \"Paraconsistent logic\") are two techniques that can be employed to deal with inconsistency.\n* Deceit: This is when the producer of the information is intentionally misleading the consumer of the information. [Cryptography](https://en.wikipedia.org/wiki/Cryptography \"Cryptography\") techniques are currently utilized to alleviate this threat. By providing a means to determine the information's integrity, including that which relates to the identity of the entity that produced or published the information, however [credibility](https://en.wikipedia.org/wiki/Credibility \"Credibility\") issues still have to be addressed in cases of potential deceit.\n\nThis list of challenges is illustrative rather than exhaustive, and it focuses on the challenges to the \"unifying logic\" and \"proof\" layers of the Semantic Web. The World Wide Web Consortium (W3C) Incubator Group for Uncertainty Reasoning for the World Wide Web[[33]](#cite_note-33) (URW3-XG) final report lumps these problems together under the single heading of \"uncertainty\".[[34]](#cite_note-34) Many of the techniques mentioned here will require extensions to the Web Ontology Language (OWL) for example to annotate conditional probabilities. This is an area of active research.[[35]](#cite_note-35)\n\nStandards\n---------\n\n[[edit source](/w/index.php?title=Semantic_Web&action=edit&section=10 \"Edit section's source code: Standards\")]\n\nStandardization for Semantic Web in the context of Web 3.0 is under the care of W3C.[[36]](#cite_note-36)",
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  "heading": "Beyond Web 3.0",
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}