Comments (4)
@pietercolpaert pointed out his implementation of JSON-LD Stream which meets similar goals.
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Also by @pietercolpaert, Linked Data Event Streams.
from ndjson-ld.
This issue was discussed in the 2022-10-12 meeting
from ndjson-ld.
Also by @pietercolpaert, Linked Data Event Streams.
Copy from the mailinglist:
LDES (https://w3id.org/ldes/specification) together with TREE (https://w3id.org/tree/specification) are RDF vocabularies to describe collections and members that are part of that collection. An ldes:EventStream is a tree:Collection with immutable members and thus a “log” that always grows.
Simple example of something that is an LDES:
<C1> a ldes:EventStream ;
tree:member <streetname1-v1>, <streetname1-v2> .
<streetname1-v1> rdfs:label "Station Road" ;
dcterms:isVersionOf <streetname1> ;
dcterms:created "2020-01-01T00:10:00Z"^^xsd:dateTime .
<streetname1-v2> rdfs:label "Station Square" ;
dcterms:isVersionOf <streetname1> ;
dcterms:created "2021-01-10T00:10:00Z"^^xsd:dateTime .
Using TREE you can then say that this is the first page of the LDES, and that tree:Relations exist towards other pages. Using these relation objects, you can then describe what you can find on that page: e.g., everything later in time than a certain timestamp, or everything within a geospatial area, or all members with an rdfs:label that contains a certain substring, etc.
This means that, in comparison to streamed JSON-LD, that LDES is:
- independent from serialization
- making containment explicit using RDF: you need to say you’re part of a stream using tree:member and describe the event stream as a kind of dcat:Dataset
- using TREE to also describe how structures of interlinked pages publish that event stream, and one stream can be published using multiple “views” (e.g., a Triple Pattern Fragments, a SPARQL endpoint, a substring fragmentation, etc.)
The goal is thus different, and maybe even complementary. I see value in streamed JSON-LD as a convience mechanism to just append JSON to a file and still being able to automatically translate the full file to RDF quads. You need more than just NLDJSON as you also want to be more efficient and or example not repeat the @context
on each write.
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