new life sciences SPARQL endpoint. License unclear, and contains (with permisison) some proprietary data (MeSH): https://t.co/HuvlSNhRo3 https://t.co/gSFH7o7Oxo— Egon Willighⓐgen (@egonwillighagen) February 25, 2021

New @orkg_org release today featuring a new contribution editor, where you can directly add a comparison table to capture the state-of-the-art for a particular research problem: https://t.co/nhZ7Gjzilh pic.twitter.com/MJmLp9bvIi— Sören Auer (@SoerenAuer) March 8, 2021

"Birds of a feather flock together"

Although artificial intelligence capabilities are improving daily, it is not always easy to put the AI rubber on the road – especially when it comes to understanding AI’s contextual data and problem-solving approaches. How about bringing in some “real” intelligence? Graphs are a typically human way

A Google patent describes how Google may read pages on the Web to build a large data graph that can be used to answer queries.

New #openaccess research from @jjkoehorst and colleagues: A protocol for adding knowledge to #Wikidata: aligning resources on human coronaviruses. #Covid19 Read it here: https://t.co/TWkHhRPlA1 pic.twitter.com/ayoSFs0ztd— BMC Biology (@BMCBiology) January 25, 2021

Today’s most pressing data challenges center around connections, not just tabulating discrete data. The ability for graph data science…

“Wikipedia Knowledge Graph for Explainable AI” conference paper https://t.co/4SXkKKgDMK— Learning SPARQL (@LearningSPARQL) December 19, 2020

We kicked off our #NeurIPS2020 series joined by @TacoCohen, ML Researcher at @Qualcomm @Qualcomm_Tech, to discuss his current research in equivariant networks and video compression using generative models, as well as his paper “Natural Graph Networks.”— The TWIML AI Podcast (@twimlai) December 22, 2020

"We present ten simple rules that support converting a legacy vocabulary - a list of terms available in a print-based glossary or table not accessible using web standards - into a FAIR vocabulary." https://t.co/5Jby0iXAXU pic.twitter.com/c2ovJjiAd5— Aaron Bradley (@aaranged) December 10, 2020

Here's my first blog post for Amazon Neptune which discusses the new features it supports with its recent inclusion of @apachetinkerpop 3.4.8. #graphdb https://t.co/ImzR2rFIfX pic.twitter.com/EeHOR5k2xF— stephen mallette (@spmallette) November 18, 2020

I say for some years that graph scaling is solved by throwing enough hardware at it and I'm VERY excited to hear we might even get dedicated "graph" hardware for it in the future! Great explanation! https://t.co/6XoAI3VOD2— Adrian Gschwend (@linkedktk) November 23, 2020

For the last few years, I have been promoting the idea of the Hardware Graph. My assertion was that graph hardware needs a focus on simple…

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

"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

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

"Knowledge-enriched, Type-constrained and Grammar-guided Question Generation over Knowledge Bases"(Sheng Bi et al, 2020)https://t.co/grrc8NTQFD pic.twitter.com/PcAlK4xXdF— WikiResearch (@WikiResearch) October 14, 2020

"Covid-on-the-Web: Knowledge Graph and Services toAdvance COVID-19 Research" a dataset comprising twomain knowledge graphs, including named entities linked to @DBpedia, @Wikidata and other @BioPortal vocabularies.(Michel et al, 2020)https://t.co/iZJH9Y2PpV pic.twitter.com/7hY0QpUQfv— WikiResearch (@WikiResearch) September 21, 2020

“How do you select a graph database? Learn how in @itworldca. Read here: https://t.co/Z529PWdeW6 | #GraphDatabase #GraphDB #GraphAnalytics #DataScience #Developer #Analytics #BigData”

Finding buried treasure: article on the role of graph databases in HR & HCM (Human Capital Management) #KnowledgeGraphs#Datahttps://t.co/pZB7PuDco9 pic.twitter.com/mQqH2Drhqy— Synaptica LLC (@Synaptica) September 25, 2020

TopQuadrant CEO, Irene Polikoff, provides an overview of the two main graph models along with illustrations of their similarities and differences in graph diagrams in Part I of II in this article series from @TDAN_com https://t.co/CxOrTb3ELL#knowledgegraphs #datagovernance— TopQuadrant (@TopQuadrant) September 25, 2020

I'll be discussing "Graph Queries with Gremlin Language Variants" at the Category Theory and Applications group meetup on October 6: https://t.co/MG1HpNEiGd Be prepared to see Gremlin in many different forms! #graphdb pic.twitter.com/OIOsfLvWze— stephen mallette (@spmallette) September 28, 2020

Our #Yahoo! Knowledge Graph version of #Wikipedia entity embedding is now publicly available. This will be the version we use to trigger the related entity search for knowledge panels in Yahoo! Search, try it if you need general entity embedding in any task. @wikiworkshop https://t.co/eB9H6ai2zI— Chien-Chun Ni (@saibalmars) September 2, 2020