Discover and read the best of Twitter Threads about #SPARQL
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I’ve been testing out #ChatGPT regarding its capabilities with #RDF, #SPARQL, #SHACL and #KnowledgeGraphs in general.
Here’s a short thread about how you can use it to generate RDF graphs, SHACL restrictions and SPARQL queries.
Here’s a short thread about how you can use it to generate RDF graphs, SHACL restrictions and SPARQL queries.
Step 1: Asking it to generate a SHACL shapes restriction for a random domain: tinyurl.com/5en9uc7k 
Step 2: Asking it to extend the SHACL example with restrictions about the actor(s) of the movie: tinyurl.com/4hk588nf
You can't keep a good thing down.
#LinkedData is a classic example, despite confusion that has swirled around it for years.
I was watching @timberners_lee's @TEDTalks presentation on the subject earlier today, and it has aged very well.
#Web30
🧵
#LinkedData is a classic example, despite confusion that has swirled around it for years.
I was watching @timberners_lee's @TEDTalks presentation on the subject earlier today, and it has aged very well.
#Web30
🧵
#LinkedData principles add a powerful dimension to #StructuredData creation, courtesy of a #Hyperlink functioning as an unambiguous Entity Name.
Here's a @YouTube video titled "How the hyperlink changed everything" about this "deceptively simple" tool.
Here's a @YouTube video titled "How the hyperlink changed everything" about this "deceptively simple" tool.
Once you the power of #LinkedData settles in, its importance to #KnowledgeGraph creation becomes clearer.
Here's a nice explainer video.
#SemanticWeb #Web30
Here's a nice explainer video.
#SemanticWeb #Web30
i wonder how many people who know something about "usual" complexity stuff, eg big-O, common time/space compl. classes like P/NP or PSPACE, have heard about enumeration complexity, eg delays. Because it's extremely useful when it comes to query languages, esp. on graphs. 1/
massively simplifying, the "usual" complexity stuff is going to tell you how much time or memory your query engine may use (in worst case) for query/data of some size. Great, but not the whole story. 2/
It's not going to tell you i) how long you may need to wait till 1st result, ii) how long you may need to wait *between* results. That, however, makes huge difference to clients in practice. 3/
Alors, cette carte est tirée des batailles enregistrées dans #Wikidata qui ont une date et une géolocalisation. C'est plus dense sur l'Europe parce que c'est moi qui ait commencé à ajouter ces deux infos systématiquement et que j'ai commencé par l'Europe.
Pourquoi j'ai fait ça ? Parce que j'avais besoin d'une liste de batailles du Moyen-Âge occidental pour debunker une autre discussion du même tonneau, et qu'après j'ai eu la flemme de finir les 10000+ batailles qui ont une entrée mais pas ces deux infos.
Ensuite, les batailles qui ont une entrée (même vide) sur Wikidata sont celles qui ont un article sur Wikipédia (toutes versions confondues). Dont le biais occidentalo-centré est connu (huit des dix plus grosses sont dans des langues européennes.)
Here's what happens when the combined prowess of #CSV #RDF intersect i.e., generation of a #SemanticWeb of #LinkedData visualized using our #HTML5 #PivotViewer: linkeddata.uriburner.com/HtmlPivotViewe…
This is an utlra flexible visual drill-down :)
#DataVisualization #GraphDatabases #RDBMS
This is an utlra flexible visual drill-down :)
#DataVisualization #GraphDatabases #RDBMS
Here's the #PivotViewer report definition that exposes the #SPARQL query behind the #DataVisualization : tinyurl.com/y9o5r5lg .
#LinkedData #SemanticWeb #CIO #CDO #CMO #KnowledgeGraph #CSV #HTML5 #RDF
#LinkedData #SemanticWeb #CIO #CDO #CMO #KnowledgeGraph #CSV #HTML5 #RDF
Here's a post that explains how our #HTML5 #PivotViewer functions in conjunction with #SPARQL re. powerful #DataVisualization that leverages a #SemanticWeb of #LinkedData.
Link: medium.com/virtuoso-blog/…
#GraphDatabases #DocumentDatabase #NoSQL #RDBMS
Link: medium.com/virtuoso-blog/…
#GraphDatabases #DocumentDatabase #NoSQL #RDBMS
