This blog discusses SHACL capabilities and advantages of modeling in SHACL. It also debunks some myths about SHACL's shortcomings.

In the world of asset management, data exchange is a big thing. Modelling the underlying information is a central tenet in Building Information Modelling (BIM).

In recent years, knowledge graphs have been widely applied to organize data in a uniform way and enhance many tasks that require knowledge, for example, online shopping which has greatly...

Last year, we announced the general availability of the Azure Digital Twins platform. The associated open modeling language, Digital Twins Definition Language (DTDL), is a blank canvas which can model any entity. It is therefore important to provide common domain-specific ontologies to bootstrap sol...

As part of work to convert plain JSON records to proper RDF in JSON-LD I often want to convert a string value to a URI that identifies a thing (real world concrete thing or a concept). Simple string to URI mapping Given a fragment of a schedule in JSON {"day": "Tuesday"} As well as converting … Continue reading Strings to things in context →

Play detective on Reddit: Discover political disinformation campaigns, secret influencers and morehttps://t.co/J6kYL6TM2w#api #social #data #socialMedia #database #reddit #politics #etl #analytics #neo4j #graph #analysis #socialNetwork #network #graphDatabase #etl #graphdb pic.twitter.com/KjXAQMJbHI— Luc Michalski (@lucmichalski) May 8, 2021

Taxonomies are crucial for businesses and institutions to handle bigger amounts of data. Manually organizing thousands of concepts into a knowledge tree has so far been the only way to do this. Aside

Posted by Siamak Shakeri, Staff Software Engineer and Oshin Agarwal, Research Intern, Google Research Large pre-trained natural language...

Causaly, the London-based company that allows researchers and specialists to intuitively map and navigate the intricate landscape of biomedical research, has raised $17 million from investors to grow its team and expand into new markets.

Graph Theory in Machine Learning, and How it’s Changed the Game

We present Arianna+, a framework to design networks of ontologies for representing knowledge enabling smart homes to perform human activity recognition online. In the network, nodes are ontologies...

This is what happens when you bulk add keywords without paying attention to the details. If you’re searching for a specific result in a database or on... 43 comments on LinkedIn

Graph clustering aiming to obtain a partition of data using the graph information, has received considerable attention in recent years. However, noisy edges and nodes in the graph may make the...

This is a guest post by Russell Waterson, Knowledge Graph Engineer at Data Lens Ltd. Customers use knowledge graphs to consolidate and integrate information assets and make them more readily available. Building knowledge graphs by getting data from disparate existing data sources can be expensive, time-consuming, and complex. Project planning, project management, engineering, maintenance and […]

A new benchmarking study released at this week’s The Knowledge Graph Conference illustrates how large corporates are starting to embrace…

Over the recent years, Graph Neural Networks have become increasingly popular in network analytic and beyond. With that, their architecture noticeable diverges from the classical multi-layered...

With the Open Research Knowledge Graph (https://orkg.org) developed by TIB – Leibniz-Informationszentrum Technik und Naturwissenschaften and L3S Research...

Stanford / Winter 2021

Wireframing/interface design and user experience flow definition activities are a powerful tool to visualize knowledge graph applications.

Algorithms have been fundamental to recent global technological advances and, in particular, they have been the cornerstone of technical advances in one field rapidly being applied to another. We...

This paper, originally written in Hungarian by Dénes Kőnig in 1931, proves that in a bipartite graph, the minimum vertex cover and the maximum matching have the same size. This statement...

"Relational world knowledge representation in contextual language models: A review" Knowledge bases such as #Wikidata provide a high standard of factual precision which can in turn be expressively modeled by language models.(Safavi and Koutra, 2021)https://t.co/zZuhjIvCva pic.twitter.com/NCLBQBlLPL— WikiResearch (@WikiResearch) April 23, 2021

In this blog post, @ABrokenJester discusses how #RDFstar & #SPARQLstar can make provenance tracking in #RDF #KnowledgeGraphs easier, & demonstrates how RDF-star annotations can be retrieved, displayed & visualized graphically in #metaphactory: https://t.co/qbdXJvBlOp— metaphacts (@metaphacts) April 26, 2021

Network Analysis, Topic Modeling, and a Wordcloud!

Knowledge graphs bring vital changes to connected inventories for financials and enable them to save much time and expenses

Google shows us how automated data wrappers may be used to extract entity information from web pages and make The knowledge graph better.

I recently purchased a new laptop one with enough speed and space to let me do any number of projects that my nearly four-year-old workhorse was just not equipped to handle.

We are excited to announce the launch of HealthECCO, a non-profit association that builds on the amazing work of the CovidGraph Project. The core CovidGraph Neo4j Graph, applications and community were built by a loose collection of volunteers, enthusiasts and organisations. Setting up HealthECCO will allow us to build a more robust operating environment for […]

SPARQL is a powerful language for working with RDF triples. However, SPARQL can also be difficult to work with, so much so that it often is not utilized anywhere near as often for its advanced capabilities, which include aggregating content, building URIs, and similar uses.