Read the first post in our new series of blog posts focusing on major Ontotext’s webinars and how they fit in the bigger picture of…
At Center Stage II: Ontotext Webinars About Reasoning with Big Knowledge Graphs and the Power of Cognitive Graph Analytics
A series of blog posts focusing on major Ontotext’s webinars and how they fit in the bigger picture of what we do. In this blog post, we'll talk about two webinars that give the bird’s eye view of the enterprise knowledge graph technology we have dedicated 20+ years to develop for some of the most knowledge intensive enterprises in various industries.
August 27, 2021 4 mins. read
This post continues the series of posts we started with At Center Stage: 2 Ontotext Webinars About Knowledge Graphs and Their Application in Data Management.
We want to give you the bigger picture of what we do and where Ontotext webinars fit into it – just a couple of webinars at a time. All of our webinars are available on demand. If you’ve missed one and if we’ve managed to pique your interest with this post, you can request a free recording.
Here, we’ve decided to present another two Ontotext webinars that give the bird’s eye view of the enterprise knowledge graph technology we have dedicated 20+ years to develop for some of the most knowledge intensive enterprises in various industries. These are: Reasoning with Big Knowledge Graphs: Choices, Pitfalls and Proven Recipes and Graph Analytics on Company Data and News. Both were presented by our CEO, Atanas Kiryakov.
Reasoning with Big Knowledge Graphs: Choices, Pitfalls and Proven Recipes
The first Ontotext webinar that takes center stage in this post is Reasoning with Big Knowledge Graphs: Choices, Pitfalls and Proven Recipes. It provides a brief introduction to logical reasoning and an overview of the most popular semantic schema and ontology languages: RDFS and the profiles of OWL 2. Atanas demonstrates how reasoning works using FactForge as a playground. FactForge is our public GraphDB demonstration service. It exposes a knowledge graph of more than 2 billion statements combining DBPedia, GeoNames, the Financial Industry Business Ontology and other data. Atanas also introduces the different reasoning implementation approaches and discusses their suitability for specific application scenarios.
You will learn about which OWL profiles are appropriate for reasoning with big knowledge graphs. You will also hear about the design choices for reasoning implementation, together with their pros and cons as well as how the popular triplestores implement reasoning. Finally, you will receive quick guidance for configuration and customization of reasoning with GraphDB.
Interesting attendee question: You said that inferencing doesn’t work with virtualization? Why is that?
Ontotext’s answer: If you have virtualization, it means that some of the data is in a remote system. This also means that you can’t pre-index it, you can’t do inferred closure there, you can’t do the inference at load time because the essence of virtualization is that you don’t load the data. So, your reasoner never sees all the data. Which means that if you use virtualization, you should resort to query time reasoning. And query time reasoning just doesn’t work on big datasets because you can’t optimize the queries.
Graph Analytics on Company Data and News
The second Ontotext webinar Graph Analytics on Company Data and News focuses on the power of cognitive graph analytics to create links between various datasets and to lead to powerful knowledge discovery. Here again Atanas uses FactForge – this time to demonstrate how graph analytics on top of a big knowledge graph can provide entity awareness about the most common types of entities: people, organizations and locations. On top of combining several open data sources, FactForge has been mapped to the FIBO ontology and its entities have been interlinked to 1 million news articles.
You will learn about the importance of ranking of nodes based on graph centrality and about popularity ranking based on news mentions of the company and its subsidiaries. Atanas will also talk about retrieval of similar nodes in a knowledge graph and determining distinguishing features of an entity.
Interesting attendee question: How do you fuse two entities that are the same?
Ontotext’s answer: Essentially, to find the right match for a company from one source to a company in another source, first we have to find the likely candidates in the second source. This is called pre-selection. Then we evaluate each of these candidates and score them. For example, if one of the companies is registered in the US and the other is registered in Italy, this is strong evidence that they are not the same entity. If one of them is in the phone industry and the other is a bank, again, they are probably not the same entity.
Wrap up
That covers the 2 Ontotext webinars we wanted to draw your attention to in this blog post. We hope you’ve heard enough to want to dive straight into one of them or why not even both.
Watch out for our next post in this series At Center Stage: Ontotext’s Webinars or visit our Webinars directly to check out what is upcoming!
Article's content
Gergana Petkova
Content Manager at Ontotext
GraphDB in Action: Navigating Knowledge About Living Spaces, Cyber-physical Environments and Skies
Read about three inspiring GraphDB-powered use cases of connecting data in a meaningful way to enable smart buildings, interoperable design engineering and ontology-based air-traffic control
Your Knowledge Graph Journey In Three Simple Steps
A bird’s eye view on where to start in building a knowledge graph solution to help your business excel in a data-driven market
Data Management Made Easy: The Power of Data Fabrics and Knowledge Graphs
Read about the significance of data fabrics and knowledge graphs in modern data management to address the issue of complex, diverse and large-scale data ecosystems
GraphDB in Action: Powering State-of-the-Art Research
Read about how academia research projects use GraphDB to power innovative solutions to challenges in the fields of Accounting, Healthcare and Cultural Heritage
At Center Stage VIII: Ontotext and Enterprise Knowledge on the Role of Knowledge Graphs in Knowledge Management
Read about our partnership with Enterprise Knowledge and knowledge management as an essential business function and lessons learned from developing content recommenders using taxonomies and GraphDB.
At Center Stage VII: Ontotext and metaphacts on Creating Data Fabrics Built on FAIR Data
Read about our partnership with metaphacts and how one can use the metaphactory knowledge graph platform on top of GraphDB to gain value from their knowledge graph and accelerate their R&D.
At Center Stage VI: Ontotext and Semantic Web Company on Creating and Scaling Big Enterprise Knowledge Graphs
Read about our partnership with Semantic Web Company and how our technologies complement each other and bring even greater momentum to knowledge graph management.
At Center Stage V: Embedding Graphs in Enterprise Architectures via GraphQL, Federation and Kafka
Read about the mechanisms for building a big enterprise software architectures by embedding graphs via GraphQL, Federation and Kafka
Ontotext’s Perspective on an Energy Knowledge Graph
Read about how semantic technology can advance energy data exchange standards and what happens when some energy data is integrated in a knowledge graph.
At Center Stage IV: Ontotext Webinars About How GraphDB Levels the Field Between RDF and Property Graphs
Read about how GraphDB eliminates the main limitations of RDF vs LPG by enabling edge properties with RDF-star and key graph analytics within SPARQL queries with the Graph Path Search plug-in.
At Center Stage III: Ontotext Webinars About GraphDB’s Data Virtualization Journey from Graphs to Tables and Back
Read this second post in our new series of blog posts focusing on major Ontotext webinars and how they fit in the bigger picture of what we do
At Center Stage II: Ontotext Webinars About Reasoning with Big Knowledge Graphs and the Power of Cognitive Graph Analytics
Read this second post in our new series of blog posts focusing on major Ontotext webinars and how they fit in the bigger picture of what we do
At Center Stage I: Ontotext Webinars About Knowledge Graphs and Their Application in Data Management
Read the first post in our new series of blog posts focusing on major Ontotext’s webinars and how they fit in the bigger picture of what we do
The Gold Standard – The Key to Information Extraction and Data Quality Control
Read about how a human curated body of data is used in AI to train algorithms for search, extraction and classification, and to measure their accuracy
Study of the Holocaust: A Way Out of Data Confusion
Learn how a ML algorithm trained to replicate human decisions helped the EU-supported EHRI project on Holocaust research with record linking.
