Learn why semantic technology is not only about technology, but also about the way an enterprise sees the world and its place in the digital landscape.

What to expect of Semantic Web and other Semantic Technologies? Knowledge Graphs have gotten a lot of attention as a backbone for Machine Learning, Deep Learning, and AI business use cases. Expect that to continue. There has been a growing appreciation of Knowledge Graphs — ontologies — to provide an umbrella overlay for cross-walks across siloed information resources.

#SemanticWeb and #Semantic #Technology Trends in 2020. One way or another, it’s all about graphs. And #machinelearning. And #AI. And what their connections to each other are. Welcome to the world of semantic technology in 2020.

Semantic Web Company and Ontotext implemented a seamless integration of their products to solve numerous use cases in knowledge graph management.

Edwin Toonen Edwin is a strategic content specialist. Before joining Yoast, he spent years honing his skill at The Netherlands’ leading web design magazine. Search engines love entities. Entities can be people, places, things, concepts, or ideas and they will often appear in the Knowledge Graph. Lots of search terms can be an entity, but specific search terms can also have different meanings and thus, be different entities. Take [Mars] for example; are you talking about the planet entity or the candy bar entity? The context you give these entities in your content determines how search engines see and file your content. Find out how to link entities to your content using Yoast SEO. Let’s talk semantics Semantics is the search for meaning in words. In theory, you could write an article about Mars without ever mentioning it directly. People would understand it if you provide enough context in the form of commonly used terms and phrases. To illustrate this, we’ll take

SERP analysis is an essential step in the process of content optimization to outrank the competition on Google. In this blog post I will share a new way to run SERP analysis using machine learning and a simple python program that you can run on Google Colab. SERP (Search Engine Result Page) analysis is part of keyword research and helps you understand if the query that you identified is relevant for your business goals. More importantly by analyzing how results are organized we can understand how Google is interpreting a specific query. What is the intention of the user making that search?What search intent Google is associating with that particular query?The investigative work required to analyze the top results provide an answer to these questions and guide us to improve (or create) the content that best fit the searcher. While there is an abundance of keyword research tools that provide SERP analysis functionalities, my particular interest lies in understanding the semanti

Given set of SHACL constraints & set of datalog rules, #research detects which constraints could be violated by application of inference rules on some graph instance of the schema, updates original schema to capture new facts #semantics #knowledgegraph http://arxiv.org/abs/1911.00598

Decentralized apps will need a lot of flexibility, which they will gain through data shapes ◆ Ever since Ed Sheeran’s 2017 hit, I just can’t stop thinking about shapes. It’s more than the earworm though: 2017 is the year in which I got deeply involved with Solid, and also when the SHACL recommendation for shapes was published…

As interest grows in new technologies, many enterprises are reconsidering their data warehouses. What makes graph databases different from traditional RDBMSs?

Recently the Scandinavian banks have once more been showcased in a money laundering case. Unnecessarily so, according to the graph database Neo4j’s founder.

Solid developer and inrupt advisor on progress with Berners-Lee's vision of re-decentralising the web.

With many thanks to @A_A and @bourgeoa, I’m glad to announce that Solid-IDE and solid-file-client now support file uploads (including binary files like *.mp3, *.png) and selecting multiple files at a time. With Solid-IDE, select the green folder icon next to the name of the folder to hold the uploads, then select “Choose Files”. With solid-file-client in a node.js script, simply call the upload() method (see the README for details). With solid-file-client in a browser script you can can uplo...

GDELT is the largest, most comprehensive, and highest resolution open database of human society ever created. Its vast archives of more than a quarter billion georeferenced records covering the entire world over 30 years, coupled with massive networks that connect all of the people, organizations, locations, themes, and emotions underlying those events, offers unprecedented opportunities to understand and interact with our world in fundamentally new ways.

All organisations find it difficult to fully describe their organisation in data. One of the most common pitfalls is underestimating the number of human-driven connections between data which have never been captured digitally.

This article has two sections. The first describes the longstanding difficulties in integrating data for analytics and more recently, data science and AI.

timers (sourcerers? targeteers?) may recall I originally expected the newsletter to dig into releases and updates to graph technologies. Six months in, I'm finding myself less interested in that and focused more on the intersection between graphs and other topics. I think the result is a newsletter that’s little more compelling than just a record of point releases from graph database vendors.For the graph database vendors reading, ignore the above. I love your point releases and read every single changelog,

More and more #opendata platforms are becoming linked #data. The ONS, @WikiData & Scottish Government all offer SPARQL endpoints to their #linkeddata. SPARQL acts as pattern-matching language @digidatajen @ODcamp #tutorial #knowledgegraph h/t @linkedktk

Incident response involving human responders requires context of systems and services that are encountering issues. Getting this context…

The final blog from the Synaptica team on the Stanford University course series on Knowledge Graphs. This week looked at open research questions.

Bob Kasenchak and Ahren Lehnert, Synaptica

Bob Kasenchak and Ahren Lehnert, Synaptica

Bob Kasenchak and Ahren Lehnert, Synaptica

The team continue their blogs on the Stanford University course on Knowledge Graphs. This week “What is the role of knowledge graphs in machine learning?”

/PRNewswire/ -- Stardog, the leading Enterprise Knowledge Graph platform, today announced the release of the first data model template compatible with the...

market,” said Kendall Clark, CEO and Founder of Stardog. “We plan to expand our successful EU operations, strengthen our work in the public sector, and to develop tools and partnerships to broaden access to knowledge graphs.” Stardog’s Enterprise Knowledge Graph platform is used by industry leaders including Morgan Stanley, NASA, Schneider Electric and Bayer. Customers use Stardog for a range of solutions including operational resilienc