In today’s data-driven economy, the company with the most data wins. This means that companies go through great lengths to collect all of our data, sometimes even crossing ethical boundaries. But in the end, we all lose: having the best data process is not an indication of how well a company inno...

Vassil Momtchev announces new features of GraphDB and Ontotext platform

Grasping large Knowledge Graphs is challenging. We present SemSpect, an innovative tool that brings together overview and detail view into one perspective by visually aggregating graph nodes and relationships for efficient exploration and data-driven querying of graphs. It comes either with a rea...

The United Nations (UN) supports 17 Sustainable Development Goals (SDGs) covering topics from poverty to healthcare, education, and beyond. This workshop will gather a community from which to discuss ongoing industry work, academic research efforts, and include a collaborative ideation exercise. ...

Electronic health records (EHRs) have become a popular source of observational health data for learning insights that could inform the treatment of acute medical conditions. Their utility for learning insights for informing preventive care and management of chronic conditions however, has remaine...

In the realm of enterprise applications such as cybersecurity and anti-money laundering (AML), data and system engineers team up to deal with interconnected data of great scale and richness. The regulatory need adds requirements to instant tracibility and explanability of data and analytic models...

Knowledge Graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. We observe the adoption of Knowledge Graphs by the Googles of the world. However, not everybody is a Google. Enterprises still struggle to understand their relational datab...

A hands-on tutorial that will introduce logic knowledge graphs via TerminusDB to those beginning or looking to develop their knowledge graph journey.

Panel: Frontiers in Data Intelligence. What is data intelligence? Who owns knowledge graphs? How do we define contexts of use for knowledge graphs? How to make sure knowledge graphs offer equitable utility?

Juan Sequeda from data.world moderates this Q&A with Jans Aasman from Allegro Graph, Mike Grove from Stardog and Dr. Ora Lassila from AWS.

Q&A with Huda Khan from Cornell University, David Kamien from Mind Alliances System and Rafael Goncalves from Stanford University.

Panel: Frontiers in Data Intelligence. What is data intelligence? Who owns knowledge graphs? How do we define contexts of use for knowledge graphs? How to make sure knowledge graphs offer equitable utility?

An extremely powerful and efficient use for Knowledge Graphs is to unite well-understood domains of knowledge alongside novel and specific business/scientific questions. Using small ontologies that embed large reference taxonomies, we are able to go from tactical scientific questions (bottom-up) ...

Francois Scharffe leads the Q&A between Vassil Momtchev from Ontotext and John Sowa from Kyndi.

Law firms are starting to build knowledge graphs to power next-generation marketing and business development applications that efficiently integrate data and help deliver the most important intelligence insights to the right people sooner. These systems help firms spot opportunities sooner, autho...

Pinterest is a popular Web application that has over 250 million active users. It is a visual discovery engine for finding ideas for recipes, fashion, weddings, home decoration, and much more. In the last year, the company decided to create a knowledge graph that aims to represent the vast amount...

Juan Sequeda from data.world moderates this Q&A with Jans Aasman from Allegro Graph, Mike Grove from Stardog and Dr. Ora Lassila from AWS.

Ching-Hua Chen summarizes and talks about the workshop on Personal Health Knowledge Graph.

Lambert Hogenhout offers a summary of the workshop Knowledge Graph for Social Good

2020 Talk: Knowledge Graph for Drug Discovery: A critical barrier in current drug discovery is the inability to utilize public datasets in an integrated fashion to fully understand the actions of drugs and chemical compounds on biological systems. There is a need to intelligently integrate hetero...

Andreas Blumauer is CEO of Semantic Web Company and he is here to show how to use semantics to drive the business value of your data using the PoolParty Semantic Suite. Andreas has a mission to free customers from data silos and enrich the data with semantic metadata and he believes the software ...

The Rich Context project at NYU Wagner is the knowledge graph complement to the ADRF platform for cross-agency social science research using sensitive data, currently used by 50+ agencies. Rich Context represents metadata about datasets and their use in research which in turn influences public po...

The Curious Case of the Semantic Data Catalog: Knowledge graphs have been on the rise and organizations have found a variety of use cases for the technology. One specific type of use case is the implementation of a knowledge graph as a semantic data catalog. With the inherent power of the technol...

Enterprises that are building Knowledge Graphs are rapidly getting a grip on unstructured data with current advances in Natural Language Processing (NLP) techniques. But there is still a large mass of unstructured data that is untapped and that is spoken conversations with customers. Speech to te...

Insufficient Facts Always Invite Danger: Combat Them with a Logical Model While understanding the context of data is key, it's important to remember there is no universal context. What makes sense in one case may not in another. We see this often in MDM scenarios; we can't agree on the definition...

Yes. Why? Because building a knowledge graph means you are consolidating your important knowledge assets, and that forces you to think of the “bigger picture” of all the data you have in your organization including shared, common domain models. You are not merely shoving data into a warehouse, bu...

Q&A with Ruben Verborgh from Ghent University, Byron Jacob from data.world and Yanko Ivanov from Enterprise Knowledge

As part of the Linked Data For Production: Pathway to Implementation (LD4P2) project’s larger goal of building a pathway to the use of linked data in the description of library resources, we are exploring the integration of linked data sources in library discovery interfaces. Through a series of ...

Leveraging a graph of causal forces acting on financial markets

Q&A with Thorsten Liebig from Derivo, Gavin Mendel-Gleason from TeminusDB, and Chen Yong Cher from Graphen

The Yahoo Knowledge(YK) graph crawls, reconciles and blends information (around 10B fact triples) from 200 M entities across 30 semi-structured source (crawlable sites like Wikipedia, IMDB, LonelyPlanet etc and as well licensed feeds) graphs to a merged graph of 75 M entities, 5B facts distribute...

The Rich Context project at NYU Wagner is the knowledge graph complement to the ADRF platform for cross-agency social science research using sensitive data, currently used by 50+ agencies. Rich Context represents metadata about datasets and their use in research which in turn influences public po...

Graphs provide a new dimension to managing and analyzing data, and enterprises are keen to explore and adopt this technology. There have been some barriers to adoption, including a lack of familiarity with graph query languages and tools and challenges in integrating graph analytics into existing...

Predictive analytics in inventory management has not been the traditional domain of knowledge graphs and semantics; however, it is a surprisingly natural fit. This talk will review knowledge graphs in the supply chain and look into the details of implementation. In our central case, using a seman...

In this presentation, we'll cover why a data catalog is the first knowledge graph that an organization should build. Most organizations don't have a clear picture of their data assets and how they're being used - a data datalog helps provide that picture and unlock the value of data. We'll explor...

The development and availability of Web knowledge repositories, in particular Wikipedia, as the largest general-knowledge encyclopedic collection, have changed remarkably not only the way in which individual users fulfill their informational needs but also the way in which information providers o...

Expressing opinions and interacting with others on the Web has led to the production of an abundance of online discourse data, such as claims and viewpoints on controversial topics, their sources and contexts (e.g., events, entities). These data constitute a valuable source of insights for studie...

In today’s world understanding the full context of an event is not an easy thing, especially in a world where there’s countless sources of low quality one dimensional content is fighting for our attention. Which leaves most readers of the news uniformed or spending time piecing together incomplet...

One of the challenges in protecting consumer privacy and managing data risk is the ability to validate that privacy-related data from across our data ecosystem has been identified and categorized accurately and consistently. This challenge has become especially salient in light of recent legislat...

The Information Management team (including Nicolas Seyot) at Morgan Stanley has built an RDF graph and a semantic knowledge base to help answer domain specific questions, formulate classification recommendations and deliver quality search to our internal users. In doing so over the past 4 years, ...

The Financial Industry Business Ontology (FIBO) has matured in significant areas over the last few years, but until recently there were few examples to help users understand how to interpret it and build it into their own knowledge graphs. Since early 2019, the FIBO development team has been focu...

Akash Magoon presents Nayya, the winner of the startup-investor pitch event. Nayya is a digital health platform that integrates with a company's benefit to help employees find, book, and access high-value care.

Q&A of the 4th session with Silviu Cucerzan of Microsoft Research, Konstantin Todorov of the University of Montpellier, and Dylan Roy from Dow Jones.

KGC organizer François Scharffe opening address

The proposed meta-graph solution for recommender systems is a living process for semi-automatically resolving recommendations using guided queries upon a knowledge graph. In addition, this solution is explainable; it can provide comprehensible recommendations which show the reason for each result...

Q&A of Session 5 with Bethany Sehon, & Brian Donohue from Capital One, Radu Marian from Bank of America and Nicolas Seyot from Morgan Stanley.

Knowledge graphs are increasingly built using complex multifaceted machine learning based systems relying on a wide of different data sources. To be effective these must constantly evolve and thus be maintained. I present work on combining knowledge graph construction (e.g. information extraction...

Cherre’s knowledge graph is a model of the entire US real estate ecosystem. The graph incorporates hundreds of millions of entities such as properties, addresses, individual and commercial owners, lenders, brokers, estate managers, lawyers etc. as nodes – while the edges are various types of conn...

The enterprise knowledge graphs help modern organizations to preserve the semantic context of abundant accessible information. They become the backbone of enterprise knowledge management and AI technologies with the ability to differentiate things versus strings. Still, beyond the hype of repacka...

Q&A of the first session of day 1. Here our own Francois Scharffe, Neda Abolhassani from Accenture Labs, Paul Groth from the University of Amsterdam and Ron Bekkerman from Cherre answer some questions from the audience.

Francois Scharffe leads the Q&A between Vassil Momtchev from Ontotext and John Sowa from Kyndi.

Electronic health records (EHRs) have become a popular source of observational health data for learning insights that could inform the treatment of acute medical conditions. Their utility for learning insights for informing preventive care and management of chronic conditions however, has remaine...

Boost your Graph with Semantic NLP: Nicole Moldovan from Lymba talks about the Lymba platform and how Knowledge Graphs help produce better results in this demo called Boost your Graph with Semantic NLP. Nicole shows the viewers a problem some customers face with unstructured data. Afterwards, Nic...

Since the 1960s, semantic networks of various kinds have been used for knowledge representation in AI and NLP. From the mid 1990s to 2005, Tim Berners-Lee and his colleagues adapted that technology to the Semantic Web. During the past 15 years, research in AI and related fields has created new op...

This is a product demonstration presented by Marta Lopata from KgBase and she is here to show their knowledge graph tool. She is here to show why they created the tool and how it is used to develop their graphs itself. #knowledgegraphs #knowledgegraphconference #knowledgegraphsoftware