A knowledge scientist is a person who builds bridges between #business requirements, questions, and #data. The goal is to document knowledge @juansequeda #AI #machinelearning #businessintelligence #analytics https://www.infoworld.com/article/3448577/who-should-be-responsible-for-your-data-the-knowledge-scientist.html

#CaLiGraph, a #knowledgegraph which comes with 5.6M instances and a rich ontology with 750k classes and 200k class restrictions compiled from the @DBpedia ontology and @Wikipedia Categories & Listpages announced by @heikopaulheim @nheist @dwsunima http://caligraph.org

The first public presentation of mm-ADT at ApacheCon 2019 in Las Vegas, Nevada.

#Knowledgegraphs are important resources for many #artificialintelligence tasks but often suffer from incompleteness. #research proposes to use pre-trained language models for knowledge graph completion. Novel framework named KG-BERT

.@opencitations & its datasets, tools, services, activities: #DataModel; @sparontologies (Semantic Publishing & Referencing) #ontologies; open software for searching, browsing and providing REST APIs over RDF #graphDBs; and more #OpenScience #OA https://arxiv.org/abs/1906.11964

.@Gartner Magic Quadrant for Metadata Management Solutions is out, and includes 2 vendors whose solutions rely on #knowledgegraphs #semantics #ontology #graphdatabase Congrats @datadotworld @semwebcompany https://www.gartner.com/en/documents/3970385

Graph databases are shaped the way we think, so why can't people get their heads around them?

Watch Martha's video on Connected Schema Markup and Knowledge Graphs to understand why they are important, how they are built using triples, how adding schema.org properties creates triples and how you can create relationships between entities to improve your SEO success

GPU->Rapids->Cugraph->Scalable Graph Analytics

After more than a decade, the supply-driven approach to publishing public (open) data has resulted in an ever-growing number of data silos. Hundreds of thousands of datasets have been catalogued and can be accessed at data portals at different administrative levels. However, usually, users do not think in terms of datasets when they search for information. Instead, they are interested in information that is most likely scattered across several datasets. In the world of proprietary in-company data, organizations invest heavily in connecting data in knowledge graphs and/or store data in data ...

The Ontologies Community of Practice is engaged in the development of ontologies for agricultural research. In a series of blog posts, we’ll take a look at ongoing ontologies projects and developments.

Solid developer and inrupt advisor on progress with Berners-Lee's vision of re-decentralising the web.

Neo4j's Educator Program offers Graph Data Modeling course slides, tutorials, and community support.

A knowledge base can be thought of as a data encyclopedia that’s specific to an organization, subject domain or location.

Google has moved from Search to Knowledge, and Focusing on Answering questions with knowledge graph entity information provides has led to answering queries w…

Discover tips and strategies for implementing graph embedding into a Neo4j graph database, with plenty of Cypher examples.

When used for KR, we can treat the terms 'knowledge graph' and 'ontology' as interchangeable. But ontologies also have a broader use as specifications for dynamic, ontology-driven applications, a distinction this article emphasizes.

All knowledge panels may be contextual knowledge panels based upon the words in a query that triggers those panels to appear in search results

Google introduced to the general public the term Knowledge Graph (“Things not Strings”) when they added the information boxes that you see to the right-hand side of many searches. However, the benefits of storing information indexed around the entity and its properties and relationships are well-kno

Any JSON at all.

This is the first in a short series introducing Knowledge Graphs. It covers just the basics, showing how to write, store, query and work with graph data using RDF (short for Resource Description Fo…

I would like to point to a crowd-funding of 📊 @rawgraphs, a project I find super interesting for a while and now they want to rewrite it. I think SPARQL and RAWGraphs can become best friends and so do they so help them getting there! https://t.co/VI0gK0ZZIS pic.twitter.com/UszINmFyuw— Adrian Gschwend (@linkedktk) October 2, 2019

This installment leaves the CLI behind to show how we consume a knowledge graph within our programmatic environments. The framework I use to work with RDF is dotNetRdf.

Customers continue to want greater visibility and control over the services they use within AWS. When it comes to our database services, customer requests typically revolve around providing greater insights into the query optimization and processing within a given database. Database developers and administrators are mostly already familiar with the idea and use of database […]

Although we use the term “knowledge” broadly used in the AI and graph database community, it has many different meanings based on the…