The Connected Data Podcast

May graph technology improve the deployment of humanitarian projects? The goal of using what we call “ Graphs for good at Action Against Hunger ” is to be more efficient and transparent, and this can have a crucial impact on people’s lives. Is there common behaviour factors between different projects? Can elements of different resources or projects be related? For example, security incidents in a...

Big Data has transformed the world big time. It led many companies to strongly focus on data analytics, trying to collect and control gigantic amounts of data. After years in the rat race, several of them are slowly realizing that the continuous striving for having more data than others is maybe not the most meaningful business objective for everyone. In fact, the data collection craze is steadily...

AI is transforming the financial media industry, impacting everything from content creation to consumption trends. Childs shares insights into how Dow Jones is reimagining what the news looks like. Learn how Dow Jones’ knowledge graph platform – powered by Stardog – enables the company to unify structured and unstructured data from a vast range of news sources and deliver cutting-edge insights for...

“Knowledge Graph” is an overloaded term. Today Knowledge Graphs are becoming mainstream, and as this happens, more and more people associate Knowledge Graphs with data models, semantics, knowledge management, and ontologies For many other people, however, Knowledge Graphs still mean Google Search Info Boxes, panels, SERPs, and SEO (Search Engine Optimization). They are all right. The term Knowledg...

The Financial Industry Business Ontology, FIBO, is a business conceptual model of how all financial instruments, business entities and processes work in the financial industry. FIBO combines existing financial industry data standards with ontological approaches. It has been developed by the EDM Council, a non-profit global association created to advance Data Management best practices, standards an...

Data integration, data interoperation and data quality are major challenges that continue to haunt enterprises. Every enterprise either by choice or by chance has created massive silos of data in different formats, with duplications and quality issues. Knowledge graphs have proven to be a viable solution to address the integration and interoperation problem . Semantic technologies in particular pr...

Knowledge graphs generation is outpacing the ability to intelligently use the information that they contain . Octavian's work is pioneering Graph Artificial Intelligence to provide the brains to make knowledge graphs useful. Our neural networks can take questions and knowledge graphs and return answers. Imagine: a google assistant that reads your own knowledge graph (and actually works) a BI tool...

In recent years graphs have been increasingly adopted in financial services for everything from fraud detection to Know Your Customer (KYC) to regulatory requirements. At the same time Environmental Social Governance (ESG) investing has become the fastest growing segment of financial services. In this session James Phare, Neural Alpha CEO and Founder, discusses how many of these historical graph t...

What is graph all about, and why should you care? Graphs come in many shapes and forms, and can be used for different applications: Graph Analytics, Graph AI, Knowledge Graphs, and Graph Databases. Up until the beginning of the 2010s, the world was mostly running on spreadsheets and relational databases. To a large extent, it still does. But the NoSQL wave of databases has largely succeeded in ins...

Knowledge graphs are all the rage these days , but for many they are still an exotic notion which is hard to come to terms with. In this panel, experts who have been working with knowledge graphs before it was cool will share their experience. More specifically, we’ll be looking into the interplay between semantics, SEO, schema.org, JSON-LD, and knowledge graphs. Though it may not be obvious, if y...

David Amerland, George Anadiotis, Panos Alexopoulos, and Teodora Petkova, have a few things in common. Besides being successful professionals, each in their own way, they also share a passion not many people share: the Semantic Web. As the Semantic Web is turning 20, they come together to talk about the passion. The first rule of the Semantic Web in the 2020's is, you don't talk about the Semantic...

Find the answers to: Why go semantic? Should i use RDF or OWL? What is the difference, what is the link? Did you say smart data? In this podcast you can check RDF Integration examples, learn about Ontologies and OWL Presentation by Tara Raafat, (PhD) Chief Ontologist at Mphasis. Slides available at https://www.slideshare.net/ConnectedDataLondon/tara-raafat --- Connected Data London 2024 has been a...

Whether we call it Semantic Web or Linked Data, Tim Berner Lee’s vision never really caught on among users and developers. Although part of this vision is about decentralization, and this is something a few people are working on, Semantic Web technology remains largely underutilized by them. In this panel, we will explore how the Semantic Web and decentralization can benefit each other. Getting to...

Scientists, health researchers and policymakers are using all the tools they can get their hands on to try and beat the current global pandemic. Germany’s National Centre for Diabetes Research (DZD) is one of the organizations turning to Artificial Intelligence, advanced visualisation techniques and other tools to aid the search for a vaccine and effective treatments.  Graph technology is key in t...

For as long as people have been thinking about thinking, we have imagined that somewhere in the inner reaches of our minds there are ghostly, intangible things called ideas which can be linked together to create representations of the world around us — a world that has a certain structure, conforms to certain rules, and to a certain extent, can be predicted and manipulated on the basis of our idea...

Some of us may have been saying that for years, but now the Gartners of the world are picking up on it too. So, the oracles have spoken: “The application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science”. That all sounds great, in theory. In practice, however, things are...