What we're about

London Meetup for all interested in Connected Data technologies and developments. This includes Graph Database, Linked Data, semantics, Knowledge Representation and AI experts, users, enthusiasts and newbies.

Topics at meetups so far have included:

- Linked Data in publishing, Financial Services & Telecoms

- Knowledge Representation and Explainable AI

- Graph Databases in Financial Crime & Product Recommendations

- Knowledge Management

- Ontology development & Data Modelling

- Network analysis in Bioinformatics

At the 9th meetup we tried to agree a simple description for the group to help clarify the topics that we typically discuss:

“Connected Data is a collection of related Disciplines & Technologies where the relationships, rules, structure, meaning & context are treated as first class citizens”.

The group also has an annual London conference which attracts thought leaders from around the world - this year's conference is on 16th November at the IET in Central London - see the website here: http://connected-data.london (http://connected-data.london/video-gallery/)

Upcoming events (5+)

Fighting Deforestation with Knowledge Graphs & GRAKN.AI -Complex Biomedical Data

As usual doors open at 6.30 with complimentary Pizza and Beer / other drinks available thanks to our sponsors. Please join the group below to register to streamline entry to the venue on the evening: https://skillsmatter.com/meetups/12178-connected-data-london-may Title: Fighting Deforestation with Knowledge Graphs Speaker: James Phare, Founder of Neural Alpha Description: Deforestation in recent years has migrated from traditional areas & commodities such as Palm Oil to new geographies, commodities and actors. Knowledge Graphs offer an innovative approach to understanding these drivers & informing actors such as Commodity Traders, Financial Consumers, Governments and other parties for sourcing, investment and policy making decisions. James will talk about Neural Alpha's work on www.trase.earth - a multinational NGO-led project tackling these causes. He will share their experience of using Label Property Graphs alongside Linked Data technologies and standards such as SKOS. Bio: James founded Neural Alpha in 2017 to bring innovative Connected Data solutions to the financial sector with a particular focus on Sustainable Investing. James has a track record of delivering innovative data solutions within the financial sector having consulted extensively at many of the world's largest Investment Banks, Mutual Funds and Hedge Funds. Prior to becoming a Consultant James was Head of Information Management at Man Group plc following roles at Thomson Reuters. James is the Event Director of Connected Data London and holds a Bachelors Degree in Economics & Economic History from the University of York. ------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------ Title: Using GRAKN.AI for Big Complex Biomedical Data Speakers: Tomas Sabat, Chief Operating Officer @ Grakn Labs Description: The success or failure of any modern organisation relies on the way they leverage their data. However, most institutions and organisations have no way to aggregate the magnitude and complexity of their disparate data catalogs. They require a unified representation of their data which represents their specific domain truthfully as well as conceptually. In other words, they require an expressive data model and an intelligent query language to perform knowledge engineering over complex datasets. In this Meetup event, we will introduce GRAKN.AI, a distributed hyper-relational database for knowledge engineering, to Manchester's engineering community. Systems biology is one of the domains that produces huge amounts of data and presents integration challenges due to their complex nature. As understanding the complex relationships among these biological data is one of the key goals in biology, we will demonstrate how Grakn is used to integrate disparate biological data into a knowledge graph that leads to valuable new insights of our data at scale. Grakn provides the knowledge base foundation for intelligent systems to manage complex data. We will also introduce Graql: Grakn's reasoning (through OLTP) and analytics (through OLAP) query language. Graql provides the tools required to do knowledge engineering: an expressive schema for knowledge modelling, reasoning transactions for real-time inference, distributed algorithms for large-scale analytics, and optimisation of query execution. In addition, we will discuss how Graql’s language serves as unified data representation of data for cognitive systems. Bio: Tomas is the COO of GRAKN.AI, the knowledge graph for intelligent systems. He works on introducing the world on how to use a Grakn knowledge graph to build cognitive and AI systems, working in industries such a biotech, finance and cyber-security.

WEBINAR: HOW GRAPHS CONTINUE TO REVOLUTIONISE THE PREVENTION OF FINANCIAL CRIME

In lieu of June's physical meetup we have an upcoming remote webinar approaching with Tigergraph who will be speaking about some of their work in Financial Crime. You can register for this using the signup form below: https://connected-data.london/2019/05/01/how-graphs-continue-to-revolutionise-the-prevention-of-financial-crime-fraud-in-real-time/ Description: Financial crime prevention is something that affects everyone in one way or another. From the Deutsche Banks of the world to small and medium online merchants, regulations for anti-money laundering, know your customer, and customer due diligence apply. Failing to comply with such regulations can bring on substantial fines. Even more importantly, it can hurt the bottom line and reputation of businesses, having far-reaching side effects. Complying with such regulations, and actively cracking down on financial crime, however, is not easy. Cross-referencing interconnected data across various datasets, and trying to apply detection rules and to discover patterns in the data is complicated. It takes expertise, effort, and the right technology to be able to do this efficiently. A natural and efficient way of looking for patterns and applying rules in troves of interconnected data is to model and view that data as a graph. By modeling data as a graph, and applying graph-based algorithms such as PageRank or Centrality, traversing paths, discovering connections and getting insights becomes possible. Graphs and graph databases are the fastest-growing area of data management technology for a number of reasons. One of the reasons is because they are a perfect match for use cases involving interconnected data. Queries that would be very complicated to express and very slow to execute using relational databases or other NoSQL database technology, are feasible using graph databases. With the rise in complexity of modern financial markets, financial crimes require going 4 to 11 levels deep into the account – payment graph: this requires a different solution than either relational or NoSQL databases. How are organizations such as Alibaba, OpenCorporates, and Visa using graph database technology to not just stay on top of regulation, but be one step ahead in the race against financial crime? Is it possible to do this in real time? What do graph query languages have to do with this? For answers to those questions, and more, join some of the world’s Graph database leading experts in our Connected Data London live webinar on June 5, 9 am PT / 12pm ET / 4 pm BST / 6 pm CET, sponsored by TigerGraph.

Meetup title TBC

Skills Matter | Code Node

We have Joe Depeau of Neo4j speaking about some of his work at this meetup - title, description & bio to follow. We are looking for another speaker. If you are interested in speaking please do get in touch with us. As usual doors open at 6.30 with talks starting at 7.

August meetup - speakers required

Skills Matter | Code Node

We have an August meetup scheduled but currently no speakers - please let us know if youre willing to speak about anything related to graphs, semantics, AI, Knowledge Representation, NLP, Reasoning etc.! We'd love to hear from you!

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