Great explanation of #LinkedData and #SPARQL with Buckets and Ballsby @kvistgaard https://t.co/wBPZWgNmUG pic.twitter.com/QOEA5BG7di— Elena Makurochkina (@elenamdata) October 26, 2020
FYI: #semanticweb #ontologies and #linkedopendata can be hosted on #github pages with proper #mime types - just wrote a small test-case. See here for code: https://t.co/7iSh8g4atw - inspiration from @iswc_conf #slack— martin hepp (@mfhepp) November 3, 2020
#KnowledgeGraphs articles per year on Google Scholar, slide from #iswc2020 keynote presentation of Kavitha Srinivas pic.twitter.com/MP98uGLv31— Harald Sack (@lysander07) November 3, 2020
🚨⚠️ We have just released pyRDF2Vec 0.1.0 ⚠️🚨In this release, we make the three main building blocks of the RDF2Vec algorithm fully configurable (discussed further).To illustrate how pyRDF2Vec could be used, we wrote a blog: https://t.co/sYqQuJF6Z3 (1/5)— Gilles Vandewiele (@Gillesvdwiele) November 2, 2020
Just published by @WikimediaIL :https://t.co/JadkTTL6cJCould this be the best #SPARQL / @wikidata query tutorial ever? pic.twitter.com/yeyRum76ix— WikiCite (@Wikicite) October 21, 2020
Link Prediction in #KnowledgeGraphs with an Explainable AI approach that supports newly emerging entitiesPresented this week at #ISWC2020 Joint work w/ @kingsaintrb Code: https://t.co/OzjaefFFoLPaper:https://t.co/4saczQ0slx pic.twitter.com/BnY03YtYTc— Gerard de Melo (@gdm3000) November 4, 2020
Today we presented at @iswc_conf our paper In-Database Graph Analytics with Recursive SPARQL 😊 you can check the video here: https://t.co/MBnWXPqQJQThis work was done by @JuanLReutter, @aidhog and me 🎊— Adrián Soto Suárez (@alanezz) November 3, 2020
gist is Semantic Arts' "minimalist upper ontology. It is designed to have the maximum coverage of typical business ontology concepts with the fewest number of primitives and the least amount of ambiguity." https://t.co/5pwf1LVR67— Aaron Bradley (@aaranged) November 4, 2020
"Language Models Are Open Knowledge Graphs" comparing #Wikidata with knowledge graphs automatically constructed from pre-trained language models.(Wang et al, 2020)#NLProc@dawnsongtweetshttps://t.co/re8TTPK5y3 pic.twitter.com/CC90phUnSC— WikiResearch (@WikiResearch) November 4, 2020
Yes!! One of the cool things about the semantic web community is the gender balance! https://t.co/Ch5ed6sAoU— Juan Sequeda (@juansequeda) November 3, 2020
"As we’ve grown ... developing the API aggregation layer has become increasingly harder. In order to address this rising problem, we’ve developed a federated GraphQL platform to power the API layer." @tejas26 https://t.co/vgBdzNJa0v— Aaron Bradley (@aaranged) November 9, 2020
Computer scientists develop a better way to find approximate solutions to the 44-year-old "traveling salesperson" problem.Paper: https://t.co/75WRpTKCmN (v/@UW) More: https://t.co/489nTfxm9J (v/@EricaKlarreich @QuantaMagazine)#MondayMotivation pic.twitter.com/4Xh61lzEmK— MIT CSAIL (@MIT_CSAIL) November 9, 2020
RDF vs. Property Graphs! hear @joshsh and @jansaasman of @Franzinc on @TheGraphShow episode #1https://t.co/yOaqdmNqWR#Ontology #GraphDatabases #Semantic #RDF #KnowledgeGraphs pic.twitter.com/NDBKxmrvJR— TheGraphShow (@TheGraphShow) November 2, 2020
This is a very detailed post about Uber’s data catalog. I’ve truly enjoyed and learned so much fron my conversations with @joshsh which has framed a lot of my thinking about how enterprises should manage their metadata and data. https://t.co/UWpOkStl5G— Juan Sequeda (@juansequeda) November 11, 2020
"Inrupt ... has launched its first enterprise-ready Solid servers for use by more than a dozen partners, including the NHS, the BBC and NatWest Bank." https://t.co/HcW0uWJjUZ— Aaron Bradley (@aaranged) November 10, 2020
Enrich your content and take advantage of the #LOD Cloud! #DBpediaSpotlight returned with fantastic #updates and is now aligned with the #DBpediaDatabus. Check all details here: https://t.co/dpK7bhCZfZ #DBpedia #datamatters #Docker #API #demo pic.twitter.com/HguYOJ8mXu— DBpedia (@dbpedia) November 10, 2020
Wonderful presentation by @lesliemyint on how knowledge graphs can be used to understand complexity https://t.co/tS1n9HB6wn— Dan McCreary (@dmccreary) November 13, 2020
Did some SPARQL tests with @binteractions Quadstore (powered by @comunicajs and @rdfjs) and the client-side browser instance provided by @txreto.Conclusion: 100% client side RDF & SPARQL is ready, at least for lightweight use-cases!Great validation for our RDF JS Efforts! pic.twitter.com/R7QFXtKWr1— Adrian Gschwend (@linkedktk) November 13, 2020
On one hand we have a really great technology, that may solve numerous issues in the #data industry, but how does it become attractive for the #enterprise? #KnowledgeGraphs #GraphDatabase https://t.co/GadQV0IJUj pic.twitter.com/r5D3MrY1Lf— Carbon LDP (@CarbonLDP) November 12, 2020
I wrote about how we're using knowledge graphs and machine learning to connect together heritage collections @sciencemuseum @nat_collection : https://t.co/HfHFeBP8sg pic.twitter.com/WfdOyAPCWl— kalyan (@KDutia) November 11, 2020