A mathematical theory is presented for the representation of knowledge in the

Discover a new way to visualize and explore your connected data with SemSpect: a unique approach to graph visualization that doesn't depend on using random or best-guess Cypher queries in order to explore your data's meta-graph and that is compatible with Neo4j (including RDF datasets).

Graphs are a general-purpose #datamodel, as relational was a general-purpose #data model a generation ago. A supply chain is a graph. Knowledge is a graph. Graphs are very applicable in a wide range of use cases @jimwebber @TheRegister #GraphDB #tech [LINK]https://www.theregister.co.uk/2020/02/05/graph_database_neo4j_chief_scientist/ [LINK]https://regmedia.co.uk/2016/04/26/graph_database.jpg

#Neo4j #GraphDB has added sharding @adamcowley shows when and how to use it #softwareengineering #data #tech #opensource #tutorial [LINK]https://adamcowley.co.uk/neo4j/sharding-neo4j-4.0/ [LINK]https://neo4j.com/docs/operations-manual/4.0-preview/images/fabric-single-instance.png

.@CamSemantics announces Anzo #GraphDB v.2: RDF*, Custom SDK, Free Edition. "Imagine being able to do labeled properties, just like you do in Neo4j & other property graphs, but also have capability of RDF to help w ontologies & inferencing" #data #tech

Creating Graphs in Python using Networkx #dataviz #tutorial #datascience #data #tech

#Semantic #technology, decision intelligence, knowledge #datascience will be our companions in the next years, so it's recommended to start exploring #graphdatabases, #ontologies, knowledge representation systems #knowledgegraph #AI #2020NewYear #trends

.@TigerGraph #graphDB updates its #Cloud offering with configuration for distributed graphs, replica instances for high availability, EFS for backup/restore. Updates available by end of 2019 on #AWS, #Azure to follow in Q1 2020

Graphs are common #data structures to represent #connecteddata. To use graphs with #deeplearning, we use graph embeddings, a low dimension representations which helps generalize input data. Node2Vec aims to preserve network neighborhoods #datascience #AI

Updates on #knowledgegraphs affect services built on top of them. But not all changes are the same: some updates drastically change the result of operations based on knowledge graph content; others do not lead to any variation #research #award #iswc_conf

Managing multiple truths in #datamodeling, #ontologies & #knowledgegraphs by @palexop #semantics #vagueness #datascience #dataengineering #EmergingTech #dmzone #presentation

Graphs #Analytics for Fraud Detection, using Graph #NeuralNetworks for Anomaly detection. GraphSAGE is Stanford #opensource project: deep neural network-based NRL toolkit, implemented in Tensorflow, making it ideal to develop an anomaly detection system

.@NvidiaAI RAPIDS cuGraph #opensource library is on a mission to provide multi-GPU graph #analytics for billion/trillion scale graphs. Experimental results on release of a single-node multi-GPU version of PageRank: on average 80x faster than #ApacheSpark

Property graphs provide a lot of flexibility in data modeling; but how do you know when to use which feature?

Relevance search is to find top-ranked entities in a #knowledgegraph that are relevant to a query entity. #Research paper on novel generative model over #knowledgegraphs for relevance search, named GREASE

MP voting records are public record in the UK, detailed #data is available about how each MP has voted in each bill @PublicWhip collect data & make it accessible @joshua_e_k explores how to use a #GraphDatabase to look at MP’s voting record similarity

.@jQAssistant is a #QA tool which allows definition & validation of project specific rules on a structural level. Built upon #Neo4j #graphdatabase, can be plugged into build process. Now w/ #PlantUML class diagrams #dataviz #softwareengineering

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

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

Visualize Kafka Streams with Neo4j by taking any data, turning it into a graph, leveraging graph processing, and piping the results back to Apache Kafka, adding visualizations to your event streaming applications.

Your one-stop introduction to the world of graph tech.

A look at why graphs improve predictions and how to create a workflow to use them with existing machine learning tasks.

Read latest news about Reltio Connected Customer 360. Connected customer data at the heart of customer experience.

.@DDIAlliance releases XKOS v1.2 (Extended Knowledge Organization System) specification →facilitates sharing & management of statistical classifications.(For building #Semantic Taxonomies to tag Datasets & #DataScience outputs)https://t.co/HZD1nl5Nu0#BigData #Ontologies #RDF pic.twitter.com/DDYbHqCvm7— Kirk Borne (@KirkDBorne) June 21, 2019

When building graph data models we frequently have to deal with a degree of polymorphism for our entities just like the real world. For instance – I’m a person, but I’m also a parent, a spouse, a sibling, a child, a… Implicit categorisation Sometimes the entity categories are entirely defined by relationships to other entities. […]

Read the first installment of this blog series on artificial intelligence on the ways graph technology adds necessary context for powerful AI solutions.

"In very simple terms, if you want your article, product, corporate identity, or anything else, really, to be relevant in this new world, you also need to be in the Knowledge Graphs." Richard Wallis (@rjw) on his involvement with Google and #schema.org https://t.co/6ldtlcLpHF— Aaron Bradley (@aaranged) July 8, 2019

Big data, semantic searches, and real-time responses are the reason behind the growing demand for graph databases. This article talks about what a graph database is, why graph databases are popular, and why and when we should use a graph database.

Stardog 6.2 just shipped with scalable virtual graph caching, better Kubernetes integration, support for Amazon Redshift, and many new optimizations . Read on for the details.

This is what the resultant 100 retail outlet isochrone map looks like, built using Spatia and @rapidsai #cuGraph SSSP using @OrdnanceSurvey Open Roads as road graph + drive times estimated from @transportgovuk road stats #opendata cc @puntofisso pic.twitter.com/rGhDinkaVX— John Murray (@MurrayData) May 28, 2019