A small tool to view real-world ActivityPub objects as JSON! Enter a URL
or username from Mastodon or a similar service below, and we'll send a
request with
the right
Accept
header
to the server to view the underlying object.
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"inReplyToAtomUri": "ostatus:inReplyToAtomUri",
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"toot": "http://joinmastodon.org/ns#",
"votersCount": "toot:votersCount",
"litepub": "http://litepub.social/ns#",
"directMessage": "litepub:directMessage",
"blurhash": "toot:blurhash",
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"Hashtag": "as:Hashtag"
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"type": "Note",
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"published": "2023-05-10T22:25:53Z",
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"content": "<p>As a technology, Knowledge Graphs are a particular configuration and deployment of the technologies of the semantic web. Though the technologies are heterogeneous and vary widely, the common architectural feature is treating data as a graph rather than as tables as in relational databases. These graphs are typically composed of triplet links or \"triples\" - subject-predicate-object tuples (again, this is heterogeneous) - that make use of controlled vocabularies or schemas.</p><p>These seemingly-ordinary data structures have a much longer and richer history in the semantic web. Initially, the idea was to supplement the ordinary \"duplet\" links of the web with triplets to make the then-radically new web of human-readable documents into something that could also be read by computers. The dream was a fluid, multiscale means of structuring information to bypass the need for platforms altogether - from personal to public information, we could directly exchange and publish information ourselves. </p><p>Needless to say, that didn't happen, and the capture of the web by platforms (with search prominent among them) blunted the idealism of the semantic web. </p><p>/2</p><p><a href=\"https://neuromatch.social/tags/SurveillanceGraphs\" class=\"mention hashtag\" rel=\"tag\">#<span>SurveillanceGraphs</span></a></p>",
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"en": "<p>As a technology, Knowledge Graphs are a particular configuration and deployment of the technologies of the semantic web. Though the technologies are heterogeneous and vary widely, the common architectural feature is treating data as a graph rather than as tables as in relational databases. These graphs are typically composed of triplet links or \"triples\" - subject-predicate-object tuples (again, this is heterogeneous) - that make use of controlled vocabularies or schemas.</p><p>These seemingly-ordinary data structures have a much longer and richer history in the semantic web. Initially, the idea was to supplement the ordinary \"duplet\" links of the web with triplets to make the then-radically new web of human-readable documents into something that could also be read by computers. The dream was a fluid, multiscale means of structuring information to bypass the need for platforms altogether - from personal to public information, we could directly exchange and publish information ourselves. </p><p>Needless to say, that didn't happen, and the capture of the web by platforms (with search prominent among them) blunted the idealism of the semantic web. </p><p>/2</p><p><a href=\"https://neuromatch.social/tags/SurveillanceGraphs\" class=\"mention hashtag\" rel=\"tag\">#<span>SurveillanceGraphs</span></a></p>"
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"url": "https://media.neuromatch.social/media_attachments/files/110/346/703/618/964/509/original/41a470fc0ac96e7a.png",
"name": "Knowledge graphs as a technology are relatively straightforward to define [5, 6, 7, 8] (though see [9]): directed, labeled graphs consisting of nodes corresponding to entities like a person, dataset, location, etc. and edges that describe their relationship [Footnote 1]. Knowledge graphs typically make use of some controlled ontology that provides a specific set of terms for nodes and edges and how they are to be used, and “types” that give a given entity an expected set of properties represented by edges. This makes for an extremely general data structure, where heterogeneous data can form a continuous graph in a way that is both structured and can accommodate ad-hoc modification not anticipated by a schema. For example, in Wikidata, Peter Kropotkin (Q5752) is an instance of the “human” type, which has properties like sex or gender (male) and place of birth (Moscow), but also has additional properties not in the human type like signature. Each of the “edges” like place of birth link to other nodes like Moscow, which in turn have their own sets of links, and so on.\n\nKnowledge graphs are in themselves a fairly ordinary class of data structures and technologies, but their history is the story of the enclosure of the wild and open web into a series of surveillance-backed platforms.\n\n[1]: 1.\n\nEquivalently, one could emphasize that they are graphs composed of triplet links (or just triplets) that describe some subject, predicate, and object. ",
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"name": "The significance of the relationship between search, the semantic web, and what became knowledge graphs is less widely appreciated. The semantic web was initially an alternative to monolithic search engine platforms - or, more generally, to platforms in general [15]. It imagined the use of triplet links and shared ontologies at a protocol level as a way of organizing the information on the web into a richly explorable space: rather than needing to rely on a search bar, one could traverse a structured graph of information [16, 17] to find what one needed without mediation by a third party.\n\nThe Semantic Web project was an attempt to supplement the arbitrary power to express human-readable information in linked documents with computer-readable information. It imagined a linked and overlapping set of schemas ranging from locally expressive vocabularies used among small groups of friends through globally shared, logically consistent ontologies. The semantic web was intended to evolve fluidly, like language, with cultures of meaning meshing and separating at multiple scales [18, 19, 20]:",
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"name": " Locally defined languages are easy to create, needing local consensus about meaning: only a limited number of people have to share a mental pattern of relationships which define the meaning. However, global languages are so much more effective at communication, reaching the parts that local languages cannot. […]\n\n So the idea is that in any one message, some of the terms will be from a global ontology, some from subdomains. The amount of data which can be reused by another agent will depend on how many communities they have in common, how many ontologies they share.\n\n In other words, one global ontology is not a solution to the problem, and a local subdomain is not a solution either. But if each agent has uses a mix of a few ontologies of different scale, that is forms a global solution to the problem. [18]\n\n The Semantic Web, in naming every concept simply by a URI, lets anyone express new concepts that they invent with minimal effort. Its unifying logical language will enable these concepts to be progressively linked into a universal Web. [19]\n",
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"name": "The form of of the semantic web that emerged as “Knowledge Graphs” flipped the vision of a free and evolving internet on its head. The mutation from “Linked Open Data” [16] to “Knowledge Graphs” is a shift in meaning from a public and densely linked web of information from many sources to a proprietary information store used to power derivative platforms and services. The shift isn’t quite so simple as a “closure” of a formerly open resource — we’ll return to the complex role of openness in a moment. It is closer to an enclosure, a domestication of the dream of the Semantic Web. A dream of a mutating, pluralistic space of communication, where we were able to own and change and create the information that structures our digital lives was reduced to a ring of platforms that give us precisely as much agency as is needed to keep us content in our captivity. Links that had all the expressive power of utterances, questions, hints, slander, and lies were reduced to mere facts. We were recast from our role as people creating a digital world to consumers of subscriptions and services. The artifacts that we create for and with and between each other as the substance of our lives online were yoked to the acquisitive gaze of the knowledge graph as content to be mined. We vulgar commoners, we data subjects, are not allowed to touch the graph — even if it is built from our disembodied bits.",
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