Read about the significant advantages that knowledge graphs can offer the data architect trying to bring a Data Fabric to their organization.
In the last few years, we’ve had so many Ontotext webinars on interesting topics, attended by an increasing number of people, asking more and more questions that we’ve decided to start a new series of blog posts dedicated to them.
The idea is to give you the bigger picture of what we do and where our webinars fit into it – 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 blog post, you can request a free recording.
As a global leader in enterprise knowledge graph technology and semantic database engines, we have 20+ years of experience with knowledge graphs and their applications. We’ve worked with some of the most knowledge intensive enterprises in Financial Services, Publishing, Healthcare, Pharma, Industry and the Public sector.
As a result, we know a lot about what our customers’ needs and pain points are. We can address many of their challenges with our products – GraphDB and Ontotext Platform. And on top of that, we have created a rich ecosystem with partners to further help with the complexity of modern architecture and the journey from modular to composable solutions.
So, we’ve decided to start this series with a couple of Ontotext webinars giving the bird’s eye view: Knowledge Graph Maps: 20+ Application and 30+ Capabilities and Knowledge Graphs for Enterprise Data Management.
Now, let’s say a few words about each of them.
Our webinar Knowledge Graph Maps: 20+ Application and 30+ Capabilities focuses on enterprise knowledge graphs as hubs for data, metadata and content that offer unified views to diverse information. Our CEO Atanas Kiryakov presents two maps, which have distilled our knowledge about the variety of Applications that benefit from knowledge graphs and the Capabilities needed to deliver solutions and to operate systems based on knowledge graphs. At the end, our CTO, Vassil Momtchev joins him to answer some of the questions.
You will learn more about knowledge graphs, the role of semantic metadata and the advantages of the RDF stack of standards for representation and management of knowledge graphs as compared to the Property graph model. Atanas also examines how Ontotext GraphDB and Ontotext Platform address these capabilities and provides an overview of Ontotext’s partner ecosystem.
Interesting attendee question: What is the main challenge faced by organizations trying to adopt a knowledge graph, e.g. the definition of the taxonomy to use, the adoption of the right ontologies, integrating the data on the graph, retrieving and analyzing the data, etc.?
Ontotext’s answer: Based on our extensive experience, one of the main challenges is that people often try to build an application instead of creating a well-defined model of the knowledge in their organization. What’s the difference? In the first case, the focus is to collect the data that will be served by this application, while in the second, all data is gathered in one place to be used for compatibility between many applications. The other big challenge is that people try to boil the ocean. They try to model everything, which is aiming too high at the start of a project. So, our recommendation is to start small and to abstract the organizational knowledge graph model from its applications.
The second webinar we want to draw your attention to in this post is Knowledge Graphs for Enterprise Data Management. It provides a quick introduction to knowledge graphs and presents application patterns and use cases in Media, Financial Services, Pharma and Government. The speakers, Jarred McGinnis and Atanas Kiryakov, also present Ontotext’s 10-step methodology for developing enterprise knowledge graphs and give an overview of Ontotext Platform.
You will learn more about what is and what isn’t a knowledge graph and what are the types of problems that knowledge graphs solve. Jarred and Atanas provide examples from different industries of how knowledge graphs bring value through cost savings, new revenue opportunities and a sustainable AI strategy. They also explore how Ontotext Platform enables organizations to build, use and evolve knowledge graphs as a hub for data, metadata and content.
Interesting attendee question: What happens to the business logic when building a knowledge graph? Can that also be translated?
Ontotext’s answer: Knowledge graphs are mostly paradigms for knowledge, content and data management. Much of the business logic can be represented in the data schema. But often there is business logic related to the organizational processes and knowledge graphs can’t help much there. In such cases, one should either program it as part of the the middleware or use rule engines such as JBoss.
That covers the 2 webinars that take center stage today. 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 posts in this series At Center Stage: Ontotext Webinars. And be sure to visit our Webinars regularly to check out what is upcoming!