Worum es bei uns geht

### Welcome to the Grakn Community.

Whether you’ve found yourself here by a happy accident or because you are actively looking for an intelligent database, a knowledge graph, for your project, team, or organisation; we are glad you’re here.

You’ll find events on techniques for knowledge engineering, representation and automated reasoning as well as various use cases and applications being produced by our community. We’ll host deep dives into the technical aspects of Grakn and our query language, Graql; community presentations and panels; as well as share exclusive opportunities to share your work with the world.

### About Grakn and Graql

Grakn is a distributed knowledge graph: a logical database to organise large and complex networks of data as one body of knowledge. Grakn provides the knowledge engineering tools for developers to easily leverage the power of Knowledge Representation and Reasoning when building complex systems. Ultimately, Grakn serves as the knowledge-base foundation for cognitive and intelligent systems.

Graql is Grakn's query language. It provides an expressive knowledge schema language through an enhanced entity-relationship model, transactional queries that perform deductive reasoning in real-time, and analytical queries with native distributed Pregel and MapReduce algorithms. Graql provides a strong abstraction over low-level data constructs and complex relationships.

### Join in the Community!

** Join us on Discord: https://discord.com/invite/grakn
Aw come on, become part of the conversation, interact in real-time with the Grakn engineering team and other members of the user community. Let’s get talking!

** Start Building, Share some Love
Check us out on GitHub ( https://github.com/graknlabs ) and give Grakn a 🌟

** Interested in learning more about Grakn
Check out our Use Cases, blogs and much more. Visit: https://www.grakn.ai (https://www.grakn.ai/)

** Swag Out!
Our community has grown so much over 2020, and as we haven’t been able to host physical events, we haven’t been able to share the love with you all.

Well, we are changing that and we have created a handful of ways for you to earn some Grakn Swag! ( https://blog.grakn.ai/need-some-swag-2fa162151737 )

Bevorstehende Events (5)

Knowledge Graphs in Financial Services with Grakn


Covid has had a massive impact on the financial services industry. Existing changes in technology, regulation, and geopolitics are radically changing the data landscape. Faced with this environment, financial services firms can take full strategic advantage of the most cutting-edge data infrastructure technologies to thrive in these unprecedented times. In this talk, we’ll explore how Grakn can be used to make the most of current challenges. We’ll explore how to unite data silos into a federated model and analyse data across an enterprise in real-time, enabling use cases such as customer 360, risk & compliance and anti-money laundering.

Beyond Text Mining - Text Mined Knowledge Graphs


Text is the medium used to store the tremendous wealth of scientific knowledge regarding the world we live in. However, with its ever-increasing magnitude and throughput, analysing this unstructured data has become a tedious task. This has led to the rise of Natural Language Processing (NLP), as the go-to for examining and processing large amounts of natural language data. This involves the automatic extraction of structured semantic information from unstructured machine-readable text. The identification of these explicit concepts and relationships help in discovering multiple insights contained in text in a scalable and effective way. A major challenge is the mapping of unstructured information from raw texts into entities, relationships and attributes in the knowledge graph. In this talk, we demonstrate how Grakn can be used to create a text mining knowledge graph capable of modelling, storing, and exploring beneficial information extracted from medical literature.

Drug Discovery with Grakn


Combinatorial chemistry has produced a huge amount of chemical libraries and data banks which include prospective drugs. Despite all of this progress, the fundamental problem still remains: how do we take advantage of this data to identify the prospective nature of a compound as a vital drug? Traditional methodologies fail to provide a solution to this. Knowledge graphs, however, provide the framework which can make drug discovery much more efficient, effective and approachable. This radical advancement in technology can model biological knowledge complexity as it is found at its core. With concepts such as hyper relationships, type hierarchies, automated reasoning and analytics we can finally model, represent, and query biological knowledge at an unprecedented scale.

Beyond SQL | comparing SQL to Graql


Using SQL to query relational databases is easy. As a declarative language, it’s straightforward to write queries and build powerful applications. However, relational databases struggle when working with complex data. When querying such data in SQL, challenges especially arise in the modelling and querying of the data. For example, due to the large number of necessary JOINs, it forces us to write long and verbose queries. Such queries are difficult to write and prone to mistakes. Graql is the query language used in Grakn. Just as SQL is the standard query language in relational databases, Graql is Grakn’s query language. It’s a declarative language, and allows us to model, query and reason over our data. In this talk, we will look at how Graql compares to SQL. Why and when should you use Graql over SQL? How do we do outer/inner joins in Graql? We'll look at the common concepts, but mostly talk about the differences between the two.

Vergangene Events (56)

Beyond SQL | comparing SQL to Graql


Fotos (23)

Du findest uns auch auf