.@cytoscape is an #opensource #software platform for complex networks #dataviz. #Neo4j Graphs are often too large for Cytoscape; this plugin allows you to write Cypher queries, import result as a network. Queries can be parameterized & stored for reuse
Daimler drives new HR insights with graph database technology
The German automotive giant is using Neo4j to help its HR team better understand its constantly changing corporate structure and reporting lines at a time when employees increasingly work in ‘swarms’
Dan Brickley retweeted: Really excited to present our new paper on "Fast and Deep Graph Neural Networks" at #AAAI2020, in a few days in New York. Can't wait for it. @RealAAAI Have a look at the pre-print with supplementary material on ArXiv: https://t.co/
Really excited to present our new paper on "Fast and Deep Graph Neural Networks" at #AAAI2020, in a few days in New York. Can't wait for it. @RealAAAIHave a look at the pre-print with supplementary material on ArXiv: https://t.co/Tt2Q8EQKcR#deeplearning #machinelearning— Claudio Gallicchio (@claudiogallicc1) February 4, 2020
Dario Taraborelli on Twitter: "“We are also releasing the first published embeddings of the full @Wikidata graph of 50M Wikipedia concepts, which serves as structured data for use in the AI research community. The embeddings can help other researchers per
“We are also releasing the first published embeddings of the full @Wikidata graph of 50M Wikipedia concepts, which serves as structured data for use in the AI research community. The embeddings can help other researchers perform machine learning tasks on Wikidata concepts.” https://t.co/1nqwaJvD8d— Dario Taraborelli (@ReaderMeter) April 3, 2019
Data Ontology is the Future, and I Can’t Wait - DATAVERSITY
#ontology has advantages over more common #data structures: Easy Architectural Changes, Inference, Linking Systems Together, Data Surfing. Ontology will become fundamental to how we organize and distribute data @ExagoInc h/t @aaranged
Data Science Demystified: The Data Modeling Proposition
In this contributed article, editorial consultant Jelani Harper discusses how data modeling is the foundation of the data science discipline that’s [...]
The #knowledgegraph--smart data that can describe your business and its domains--is now eating software. We won't be able to scale AI or other emerging tech wi…
Data.world joins forces with Capsenta to bring knowledge graph-based data management to the enterprise | ZDNet
Data.world has been expanding its footprint in the enterprise. The acqui-hiring of Capsenta complements its portfolio with knowledge graph virtualization to connect data in the cloud and on premise, and a UI to build knowledge graphs
In the third installment of Database Deep Dives, we caught up with JanusGraph PMC members Florian Hockmann and Jason Plurad to get some guidance on the wide world of Graph.
We provide some of the most useful/popular datasets from the LOD cloud in HDT for you to use them easily. If the dataset you need is not available here, you can create your own or kindly ask the data provider to publish their datasets in HDT format for all the community to enjoy.
DataStax Presents - Intro to Graph Databases for Data Scientists By Dave Bechberger - YouTube
With the rise of graph databases, graphs are no longer just a data structure but a powerful set of capabilities at the persistence layer which data scientists can leverage to accelerate the speed to insight. Unlike the relational world, we can now create graph models that work on 10k records or 10’s of millions of records and do so in real time. In this talk, we will walk someone familiar with building for relational databases through the process of how to start leveraging the power graph databases. We will talk about what makes a good and bad use cases, how to building effective models, an...
DataStax Presents: Property Graph Modeling with an FU Towards Supernodes - Jonathan Lacefield - YouTube
Graph databases are receiving a lot of hype these days because of the promise of fast and flexible queries that aren’t possible within either traditional RDBMs or NoSQL stores built on simple/singular access patterns. There are some practical tips and tricks that ensure that your graph database project is going to live up to the hype. In this talk, we will walk through the data modeling tips and tricks that are being used to help graph users achieve success. We’ll also highlight how to avoid the largest graph problem that can plague any graph database project, the dreaded supernode. This wi...
DataStax releases enterprise platform making graph fully native
DataStax Enterprise 6.8 fulfills the promise of integrating the graph engine and is another step in the road toward realigning the flagship platform with the Apache community.
DBpedia + SQL = timbr-DBpedia… Querying The DBpedia Open Knowledge Graph With standard SQL
bases and in addition, it includes a multitude of different international chapters/language communities.On the other hand, timbr DBpedia represents a synergy between DBpedia + SQL. Permits the querying of the DBpedia ontology/Open Knowledge Graph (OKG) via s
The interest in Freebase, Wikidata, and DBpedia since Wikidata's launch and geographically over the world (based on Google Trends).Fascinating to see the local distributions, and how slow the decline of Freebase is. pic.twitter.com/EstBNjCT2g— Denny Vrandečić (@vrandezo) February 27, 2020
Deciphering Product DNA: Next-Level PDM with AI & Knowledge Graphs - Neo4j Graph Database Platform
Increasingly complex products undoubtedly require greater management of components, function and data. Classic product data management (PDM) has long reach its limits in this respect. Breaking down product DNA is now driven by artificial intelligence (AI) and knowledge graphs. In… Read more →
