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Kirk Borne on Twitter: ".@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) ht
Kirk Borne on Twitter: ".@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) ht
.@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
·twitter.com·
Kirk Borne on Twitter: ".@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) ht
Knowledge Graph Comparison: GDELT VS. Diffbot
Knowledge Graph Comparison: GDELT VS. Diffbot
There are only a handful of publicly available knowledge graphs. And among those, only a few provide data with enough breadth to in some way represent the entire internet, and with enough granulari…
·blog.diffbot.com·
Knowledge Graph Comparison: GDELT VS. Diffbot
Knowledge graphs in the fight against COVID-19
Knowledge graphs in the fight against COVID-19
19, trying to make sense of the data surrounding the virus is a Herculean task. Vast in volume and ceaselessly produced, this data emanates from domains as different as virology and economics and is produced by a multitude of people and organizations. Unsurprisingly the standards to which this data conforms are as multitudinous as its sources. It just so happens that making sense of messy data from disparate sources is one of the things at which knowledge graphs excel. Moreover, knowledge graphs make it possible to derive new knowledge from intelligently connecting information residing in those disparate data repositories. Given that the ability to better analyze data and gain new insights is of obvious use to people trying to respond to the pandemic, those working with knowledge graph technologies have started to talk about how those technologies – and their skills – might
·thegraphlounge.com·
Knowledge graphs in the fight against COVID-19
Language Servers for Everybody - Stardog
Language Servers for Everybody - Stardog
At Stardog, we’re all about making it easy to unify data. That’s why we’ve just open sourced a set of tools to make working with Stardog even easier than before.
·stardog.com·
Language Servers for Everybody - Stardog
Lets talk about plugs – Lost Boy
Lets talk about plugs – Lost Boy
This is a summary of a short talk I gave internally at the ODI to help illustrate some of the important aspects of data standards for non-technical folk. I thought I’d write it up here too, i…
·blog.ldodds.com·
Lets talk about plugs – Lost Boy
LinkedIn
LinkedIn
GQL is an effort to standardize property #GraphDB query language. GQL project lead leaving #Neo4j, WG3 is now responsible. "There is no certainty about the success of the GQL project, but there are good objective and subjective grounds for optimism"
·linkedin.com·
LinkedIn
LinkedIn
LinkedIn
#smartcity stakeholders must build #datagovernance & management ready for all categories of #data. Required:assessment of expected current/future categories, scalable, flexible, modular design. Shared, unified, standards-based graph data model: #ontology
·linkedin.com·
LinkedIn
LinkedIn
LinkedIn
Graph databases are finding a place in analytics applications at organizations that need to be able to map and understand the connections in large and ...
·linkedin.com·
LinkedIn
Managing Delivery Networks: A Use Case For Graph Databases - DEV Community 👩‍💻👨‍💻
Managing Delivery Networks: A Use Case For Graph Databases - DEV Community 👩‍💻👨‍💻
An analysis of the unique problem @TAKEALOT faced in facilitating reliable deliveries to customers and how they use a #graphdatabase to deliver a performant and scalable solution, by @filipe_ppt #retail #business #innovation #data https://dev.to/fppt/managing-delivery-networks-a-use-case-for-graph-databases-2jb0
·dev.to·
Managing Delivery Networks: A Use Case For Graph Databases - DEV Community 👩‍💻👨‍💻
Microsoft to introduce a free tier of its Cosmos DB NoSQL database
Microsoft to introduce a free tier of its Cosmos DB NoSQL database
at Build 2017. Azure Cosmos DB was designed t be a superset of Microsoft's existing NoSQL Document DB database. Its codename was "Project Florence," and Microsoft execs consider it a "born in the cloud/cloud native" database that's designed to be scalable and usable by customers of any size.Microsoft currently charges by provisioned throughput and consumed storage by the hour for Azure Cosmos DB. Before the introduction of the free tier, M
·zdnet.com·
Microsoft to introduce a free tier of its Cosmos DB NoSQL database
Moving Toward Smarter Data: Graph Databases and Machine Learning - DZone Database
Moving Toward Smarter Data: Graph Databases and Machine Learning - DZone Database
When we used to think about data, it was most often in regard to where data was going to be stored and how we would manage it. Yes, files worked for a while, but when manipulating data became an important business priority across industries, the “file” solution didn’t work so well anymore. To meet these increasing demands, applications were designed and developed, addressing data storage and manipulation needs simultaneously — thus, the “database” was born. Today, data is viewed quite differently. Beyond data manipulation, organizations are focusing on mining their data for more visibility into and a deeper understanding of the intelligence within that data. Utilizing the insights acquired from their data to help make informed business decisions is a key priority for business leaders and a major concern in the development, evolution, and adoption of database solutions. A new term emerged in the industry — digital assets. That data the world has been obsessing over.
·dzone.com·
Moving Toward Smarter Data: Graph Databases and Machine Learning - DZone Database
Neo4j CEO talks growing enterprise graph adoption and why partnering with Google makes sense
Neo4j CEO talks growing enterprise graph adoption and why partnering with Google makes sense
(Image sourced via Neo4j’s Twitter)I last met Emil Eifrem, the highly energetic and persuasive founder and leader of graph database and software tools firm Neo4j for diginomica back in May 2017. As he was quick to point out in our latest meeting, a lot’s changed for his company and the market he’s tried to so hard to dominate.
·diginomica.com·
Neo4j CEO talks growing enterprise graph adoption and why partnering with Google makes sense
Neo4j Is in Bloom Everywhere This Spring
Neo4j Is in Bloom Everywhere This Spring
Two years ago, Neo4j Bloom™ was announced to the world. Today, I’m excited to announce that we’re bringing graph visualization and exploration to everyone using Neo4j – on any platform.
·neo4j.com·
Neo4j Is in Bloom Everywhere This Spring
Neo4j retweeted: The Supreme Court of the United States as a graph database, with Justices as brown nodes, Presidents as green nodes, and appointment, promotion, succession, and the 17 historical periods/Courts associated with each Chief Justice shown thr
Neo4j retweeted: The Supreme Court of the United States as a graph database, with Justices as brown nodes, Presidents as green nodes, and appointment, promotion, succession, and the 17 historical periods/Courts associated with each Chief Justice shown thr
The Supreme Court of the United States as a graph database, with Justices as brown nodes, Presidents as green nodes, and appointment, promotion, succession, and the 17 historical periods/Courts associated with each Chief Justice shown through relationships. @mad_cat @tcjericho pic.twitter.com/FdDXHo82H0— 🌍 Јаков Минг Дановић 🌏 (@chenx064) March 4, 2020
·twitter.com·
Neo4j retweeted: The Supreme Court of the United States as a graph database, with Justices as brown nodes, Presidents as green nodes, and appointment, promotion, succession, and the 17 historical periods/Courts associated with each Chief Justice shown thr