What we're about
Upcoming events (5)
Join the Grakn Labs Community for an introduction to knowledge graphs, featuring Grakn and Graql.
Hosted by: Tomás Sabat and Daniel Crowe
Cognitive/AI systems process knowledge that is far too complex for current databases. They require an expressive data model and an intelligent query language to perform knowledge engineering over complex datasets.
In this talk, we will discuss how Grakn, a database to organise complex networks of data and make it queryable, provides the knowledge graph foundation for intelligent systems to manage complex data.
We will discuss how Graql, Grakn's reasoning (through OLTP) and analytics (through OLAP) query language, provides the tools required to do the job: a knowledge schema, a logical inference language, a distributed analytics framework.
And finally, we will discuss how Graql’s language serves as unified data representation of data for cognitive systems.
Tomás is the Chief Operating Officer at Grakn Labs, dedicated to building a distributed Knowledge Graph for intelligent systems. He works directly with Grakn's open source and enterprise users so they can fulfil their potential with Grakn and change the world. He focuses mainly in finance, life sciences and robotics.
Daniel is the Global Community and Partnerships manager for Grakn Labs, working to build a world class community of engineers, innovators, breakers of things. He works directly with the Grakn Community to accelerate projects, solve ever more complex problems and bring people together all over the world towards this common mission.
Semantic Web technologies enable us to represent and query for very complex and heterogeneous datasets. We can add semantics and reason over large bodies of data on the web. However, despite a lot of educational material available, they have failed to achieve mass adoption outside academia.
TypeDB works at a higher level of abstraction and enables developers to be more productive when working with complex data. TypeDB is easier to learn, reducing the barrier to entry and enabling more developers to access semantic technologies. Instead of using a myriad of standards and technologies, we just use one language - TypeQL.
In this talk:
- we will look at how TypeQL compares to Semantic Web standards, specifically RDF, SPARQL RDFS, OWL and SHACL.
- cover questions such as, how do we represent hyper-relations in TypeDB? How to use rdfs:domain and rdfs:range in TypeDB? And how do the modelling philosophies compare?
Graph databases have matured into mainstream technologies and deliver tremendous value to organisations across any industry. They are more flexible than traditional relational databases as they enable us to leverage the relationships in our data in a way relational databases cannot do. In the time of AI and Big Data, this creates opportunities for any organisation.
However, developing with graph databases requires us to overcome plenty of challenges when it comes to data modelling, maintaining consistency of our data among others.
In this talk, we discuss:
- how TypeDB compares to labelled property graphs and how it addresses these challenges. While both technologies share similarities, they are fundamentally different.
- We'll cover how to read & write data
- how to model complex domains
- TypeDB's ability to perform machine reasoning at scale
Building on previous success in this area, the BioCorteX team have used TypeDB to map the therapeutic patent landscape providing unique insights and opportunities. We are able to establish the patent structure for potential therapeutics in a matter of seconds. Importantly, at BioCorteX we are able to quickly highlight the gaps that we refer to as the undiscovered country.
# About the Speaker:
Nik Sharma is the CEO/Co-founder of BioCorteX. He is a clinician scientist at UCL with a specialist interest in neurodegenerative disease and the microbiome. Nik leads the first clinical trial of direct microbiome manipulation in people living with motor neuron disease (MND also known as ALS). The unique multidisciplinary team at BioCorteX combines expertise from neuroscience and aerospace with the explicit aim of developing a new approach to therapeutic optimisation. The four BioCorteX engines are purpose-built to develop enhanced therapeutics to address a range of disorders at scale. BioCorteX’s mission is to cure neurodegenerative diseases by hacking the microbiome and delivering enhanced therapeutics.