an ontology representating the knowledge of the aviation sector

Here at Neo4j, we have a motto: Graphs Are Everywhere. This blog series was inspired by all the times I encountered graphs and “graph problems” in my non-working life. Hopefully these posts help you see more graphs in the world.… Read more →

december

Boettiger, (2019). Ecological Metadata as Linked Data. Journal of Open Source Software, 4(34), 1276, https://doi.org/10.21105/joss.01276

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

A piece that attempts to clarify what metadata is, and why it can be so helpful to content. Answers a frequently asked question that our integration team receives.

The most depicted humans in #paintings #SPARQL query on #Wikidata looks an #artwork itself https://t.co/MgWi4bCDPo (ht @sanseveria ) pic.twitter.com/qMjZtNkCFM— Maarten Dammers (@mdammers) January 18, 2020

Multi-model is a useful #technology for #enterprise #knowledgegraphs, say @arthurakeen @arangodb Benefits: streamlining multi-source #data to EKGs, increasing usability of EKG data for business, enabling greater scale, reducing EKG ecosystem footprint

A short article on reading-comprehension and knowledge-based dialogue systems with an overview of the SCAI workshop @ IJCAI 2019

The Centre for Digital Built Britain’s National Digital Twin programme has launched an open consultation seeking feedback on the proposed approach to the development of an Information Management Framework for the built environment. 

For more complex products such as new pharmaceutical drugs, medical equipment or healthcare treatments, identifying hubs of influencers among physicians and other healthcare providers requires deep analysis of patient claims data to uncover the referral relationships.

How do you apply graph thinking to solve complex problems? With Practitioners Guide to #Graph #Data @DeniseKGosnell @MBroecheler show #datascientists how to think about data as graph, techniques for building scalable, real-time, multimodel architectures

This story was originally published on InsideBigData .Knowledge graphs are one of the most important technologies of the 2020s. Gartner predicted that the applications of graph processing and graph databases will grow at 100% annually over the next few years.Over the last two decades, this technology was adopted mostly by engineers and ontologists, hence the majority of knowledge graph tools were designed for the users with advanced programming skills.In 1900, 40% of the population was involved in farming.Today it’s 1%. Coding is the modern day “farming” as only 0.5% of the world’s population knows how to code.NoCode brings equal opportunities to talent of all trades.Let’s just imagine, what impact this could have if the majority of world’s population was able to take advantage of cutting edge technologies to solve top of mind problems.Empowering top talent with NoCode approachEngineering and programming are important skills but only in the right context, and only for

In the spirit of H.R. 4174, EK can help make your data more organized, structured, and more accessible to technical and non-technical users.

Facilitating #journalism #automation via #knowledgegraphs. KG nodes corresponding to news articles, arrows show their connections. Generated using @sentilecto_NLU, allows navigating the spacial representation of a set of related texts #AI h/t @aaranged

Andrea Volpini describes a dance between machines and humans that means much of what we see is really a semi-automated approach to SEO. Absolutely brilliant insights. Brilliant enough to stop me talking too much, for once 🙂 A cycle of a machine and humans correcting, stimulating and teaching each other. Never forget that everything comes […]

For a domain with a strong focus on unambiguous identifiers and meaning, the Semantic Web research field itself has a surprisingly ill-defined sense of identity. Started at the end of the 1990s at the intersection of databases, logic, and Web, and influenced along the way by all major tech hypes such as Big Data and machine learning, our research community needs to look in the mirror to understand who we really are…

A semantic database is a set of interconnected resources, where each node (the starting and ending point of an arrow) is some kind of resource and each edge is a relationship.The graphs created by this are instrumental in creating context free applications and knowledge stores.

In this blog Ahren Lehnert looks at the source of the source. Information systems as ecosystems in which technology, people, and processes interact.

There is a running joke in standards circles: God must love standards. He's made so many of them. If you spend enough time working with standards, ontologies, reference data or information modeling, you'll find yourself involved in the process of creating, modifying or defending specific standards.

The core business value and use cases for a well-designed effective enterprise taxonomy design have remained true over the years.

Connected Data London community cast. Gavin Mendel-Gleason: Quick overview of query language and how we got here

.@Josh_Bersin has been writing about the explosion of #Skills #Ontology from Workday, Degreed, EdCast, etc. @CornerstoneInc, a Learning Management Systems provider, entered the game via acquisition of @Clustree #futureofwork #knowledgegraph #EmergingTech

Backed by one of Google’s earliest investors, Diffbot’s MikeTung is trying to win the information wars by analyzing nearly all of the web. Data hungry corporations like Snapchat and eBay are biting.

Mbabel #bot automatically generates article drafts based on information stored in #Wikidata. It puts generated content on a “user test page on Wikipedia”; users can expand it. Quality is influenced by heavy reliance on Wikidata #AI #opendata #semantics [LINK]https://www.vice.com/en_us/article/4agamm/the-worlds-second-largest-wikipedia-is-written-almost-entirely-by-one-bot [LINK]http://video-images.vice.com/articles/5e3c6732c62ac8009d1e9f27/lede/1581016882789-1_31_2020_THE_SECOND_LARGEST_WIKIPEDIA_SECTION_WRITTEN_BY_ONE_BOT_CV_ALT.jpeg

How graph databases can be used to explore and analyse the decentralised XRP ledger, focusing on exploring networks of fraudulent accounts and distribution patterns.

Google’s Knowledge Graph ambitions are expanding to include obviating heavy reliance on secondary sources like Wikipedia and being able instead to classify and cross-reference information as …

This is great, and don’t miss the other ontologies at this excellent subdomain name.

What do eBay, Airbnb, Microsoft, Lending Club, and Comcast have in common? They're all using knowledge graphs to understand their customers, business decisions, and product lines. Why? Because they easily and intuitively visualize the nature, depth, and interdependence of the relationships they've created with their business decisions.