Connected Data

Connected Data London 2024 Program Announcement It’s the most exciting day in the course of the event, second only to the conference itself It took a while, but we think you will find it was worth the wait We had more quality submissions than ever, and that meant making hard choices We like to think that this reflects the progress and growth in the Connected Data community We are looking forward to seeing you all in London - or online 3 Keynotes 27 Presentations 6 Lightning Talks 20 Masterclasses 8 Panels 73 Speakers 8 Stages 3 Days Welcome to Connected Data London 2024 Stay tuned as we highlight gems from our program in the coming days Get ready for the best Connected Data London ever Tony Seale Matthew Adams Jessica Talisman Leah Miller Jérémy Ravenel Valentina Alto Caroline Goulard Milan Janosov Bradley Rees Friedrich Lindenberg Peter Crocker Prashanth Rao Dexter Lowe Sofus Macskássy Weidong Yang Paco Nathan Jesse Anderson Adam Wangrat Yoan Sallami, PhD Anthony Alcaraz Chess Stetson Bogdan Arsintescu Dan Selman Zornitsa Manolova Fouli Argyriou Andreas Blumauer Sebastian Müller Hans Viehmann Ricky Sun Tara Raafat, PhD Giuseppe Futia, PhD Achim Reiz Dr Orit Gal Amy Hodler Ben Gardner Russell Jurney Veronika Heimsbakk Christelle Maignan Jane Lomax Simon Jupp Joseph K Iype #ConnectedData #Announcement #Event #KnowledgeGraph #GraphDB #DataScience #AI #GenAI #LLM #RAG #GraphRAG #SemTech #CDL24 https://lnkd.in/dmrRpV4c

GenAI Beyond Chat with RAG, Knowledge Graphs and Python GenAI and Large Language Models (LLMs) have the potential to increase productivity and provide access to data, but they need grounding and good context to be truly useful. In this hands-on GenAI masterclass,?Martin O'Hanlon, Neo4j Graph Database & Analytics, will share how Knowledge Graphs and Retrieval Augmented Generation (RAG) can support your GenAI projects. You will: * Learn about Large Language Models (LLMs), hallucination and integrating knowledge graphs * Explore Retrieval Augmented Generation (RAG) and its role in grounding LLM-generated content * Use Vector indexes and embeddings in Neo4j to perform similarity and keyword search * Use Python, LangChain and OpenAI to create a Knowledge Graph of unstructured data After completing this masterclass, you will be able to explain the terms LLM, RAG, grounding, and knowledge graphs. You will also have the knowledge and skills to create simple LLM-based applications using Neo4j and Python. https://lnkd.in/dDPqGuct #KnowledgeGraph #AI #LLM #RAG #Masterclass #GenAI #DataScience #Python

?? Announcing the Stellar Talks at Connected Data London Main Conference Day - December 12th ?? ?? 27 Presentations + 6 Lightning Talks that will revolutionize how you think about data, AI, and knowledge graphs. Whether you're joining us in London or online, this is an event you won't want to miss! ?? Highlights include: 1?? Automating Rule Extraction with Ontology-Driven LLMs 2?? Creating Customer 360s Using Entity Resolution 3?? Graph Systems for Data in Motion 4?? Combatting Cyber Threats in Financial Organizations 5?? Leveraging Knowledge Graphs for Enhanced Regulatory Compliance in Finance by HSBC 6?? Project AMIGO: Diagnosing Children with Rare Diseases using Graphs …and many more groundbreaking sessions! ?? Explore the full program per day here https://lnkd.in/gGyTa3zG #DataScience #AI #KnowledgeGraphs #ConnectedDataLondon #GraphTech #LLMs #ML

I know this isnt till December but posting early so anyone that can get to London, I'd strongly encourage you to make the effort - What looks to be one of the best speaker line up's I've seen! Some proper thought leaders and use cases to be discussed especially around #knowledgegraphs and #ontologies Semantic Partners will be there, myself and Mark Wood https://lnkd.in/eAqyT525 Of course excited to see industry friends too, including Andrea Gioia Heather Hedden Veronika Heimsbakk Veronika Haderlein-H?gberg, PhD Tom Vout Peter Crocker Panos Alexopoulos Tara Raafat, PhD Tony Seale Adam Wangrat Ben Gardner Andreas Trulsson Christelle Maignan Atanas Kiryakov Andreas Blumauer Sebastian Müller Thomas Hubauer Sophia Paulett and lots of new people I look forward to meeting.

Using LLMs and Graph Modeling Fundamentals to create graphs from CSV files Modeling data as a graph is a fine art, and also something that can be a challenge for users, especially in the early days. There are many resources available to help on this, such as Neo4j's Graph Data Modeling Fundamentals course. But what if we could use Large Language Models for that? What Adam Cowley found in his initial attempt to do this was that the LLM became easily distracted when dealing with larger schemas, and the prompts quite quickly reached the LLM’s token limits. Therefore, he devised an iterative approach to help avoid distraction: Load the CSV file into a Pandas dataframe. Analyze each column in the CSV and append it to a data model loosely based on JSON Schema. Identify and add missing unique IDs for each entity. Review the data model for accuracy. Generate Cypher statements to import the nodes and relationships. Generate the unique constraints that underpin the import statements. Create the constraints and run the import. Read the step by step elaboration in the article: https://lnkd.in/dv2hYmdy #KnowledgeGraph #DataModeling #LLM #GenAI #GraphDB #EmergingTech

Connected Data Knowledge Graph Challenge update #2 A couple of weeks back, we unveiled the Connected Data Knowledge Graph open source project and the CDKG Challenge for building applications on top of our Connected Data. This is our second update, in which we share news about: * What we are working on: metadata and meta-modeling * How you can learn more: join us in Connected Data London 2024 * A demo: Epsilla's chatbot As you know if you've been following Connected Data London, we unveiled our full program last week. This is something that is connected with this project in a number of ways, which we explore here. With our attention fully given to compiling the program, curating content, and going live with the announcement, the meta-modeling effort suffered as a consequence. That's not to say we are not making progress, but we don't have a meta-model we can share yet. We now have more complete metadata for all the talks in our dataset, as well as a complete set of baseline Questions and Answers to drive application development. You can find both in our Github repository. Connected Data London 2024 features an exceptional program, and everything in the conference will eventually populate the Connected Data Knowledge Graph too. The Connected Data Knowledge Graph team will also be there. We will deliver a Masterclass in Connected Data London 2024. The Masterclass will consist of two parts. In the first part, we will go over our experience and lessons learned building the Connected Data Knowledge Graph. In the second part, we will show demos. In fact, we are happy to announce we have another demo to share with everyone today. In parallel to the CDKG effort, we have been working with Epsilla to develop an application based on our dataset. Even though the Connected Data Knowledge Graph is not live yet, a preview of Epsilla's application is! Epsilla (YC S23) helps businesses develop production-ready RAG systems, enabling them to extract transformative insights from large-scale proprietary data and drive AI-powered innovation. With our data and metadata and some help from our team, our friends at Epsilla developed a chatbot that can answer questions based on the collective knowledge of our Connected Data experts. The link is in the comments - check it out! We'd also love to hear from anyone with questions they would like to have the CDKG help answer. We have compiled an initial list of questions to test drive demo question-answering applications to be built on top of the CDKG. What questions would you ask? Let us know in the comments, and we'll add them to our list! Hope to see as many of you as possible in our Connected Data London 2024 Masterclass - sign up here: https://lnkd.in/dSd-rUt4 #ConnectedData #KnowledgeGraph #Community #DataModeling #OpenSource #CDL24 #RAG #GenAI #Chatbot #Application

?? Announcing 20 Cutting-Edge Masterclasses at Connected Data London — Day 1 ?? ?? December 11th | In-Person and Online Get ready for an incredible lineup of masterclasses designed to transform the way you work with data, AI, and knowledge graphs. From GenAI and Graph Neural Networks to practical applications and industry best practices, we’ve curated sessions led by the brightest minds in the field! Here’s a sneak peek at what’s in store: 1?? From Connected Data to Meaningful Visualisations 2?? Building Sustainable GenAI Systems: The Critical Role of Knowledge Graphs & Ontologies 3?? Building Your Knowledge Graph with RDF: An Introduction 4?? Mastering Graph Neural Networks: From Fundamentals to Applications 5?? Creating Enterprise Knowledge Graphs One Data Product at a Time 6?? How to Perform Visual Analytics of Graph Data 7?? Introducing GraphRag with LangChain and Neo4j 8?? Taxonomy Design Best Practices for Knowledge Graphs 9?? Full Stack Graph Machine Learning ?? Cypher vs. SQL: When Do You Need a Graph Database? … And 10 more dynamic sessions! Whether you're an expert or just getting started, there's something for everyone. ?? Explore the full program here https://lnkd.in/gPeCU7xb #DataScience #AI #KnowledgeGraphs #ConnectedDataLondon2024 #GraphTechnology #GenAI #ML https://lnkd.in/gGyTa3zG

The Critical Role of Knowledge Graphs and Ontologies in Building Sustainable GenAI Systems As enterprises rush to adopt generative AI, many are overlooking a critical foundation needed for long-term success and scalability: knowledge graphs and ontologies. Generative AI models excel at producing human-like text, images, and other content. However, they often lack the structured knowledge and reasoning capabilities needed to consistently generate accurate, contextually relevant, and trustworthy outputs for enterprise applications. This is where knowledge graphs and ontologies become crucial. Knowledge graphs provide a flexible, interconnected representation of domain knowledge, while ontologies define the concepts, relationships, and rules governing that knowledge. Together, they form a powerful knowledge foundation that can be leveraged to enhance generative AI systems in several key ways: ??Grounding AI outputs in factual knowledge ??Enabling multi-hop reasoning and inference ??Providing explanations and provenance for AI-generated content ??Facilitating data integration across enterprise silos ??Ensuring consistency and reducing hallucinations Anthony Alcaraz, Senior Strategist and BD AIML at AWS, will explain why this "knowledge stack" is essential for creating truly sustainable and impactful generative AI systems. This Masterclass will explore how leading companies are integrating knowledge graphs and ontologies with large language models and other generative AI technologies to build more robust, explainable, and trustworthy AI systems. We'll examine real-world use cases, discuss implementation strategies, and provide guidance on getting started with this critical knowledge stack. Seats are limited, and tickets are going fast - get yours today! #KnowledgeGraph #GenAI #LLM #RAG #Ontology #Masterclass #Tutorial #ThoughtLeadership #CDL24 https://lnkd.in/dBhC9fEX

We’re thrilled to welcome Ultipa as a Silver Sponsor of Connected Data London 2024! ?? ? Ultipa builds next-generation leading real-time graph XAI & database products, and empowers smart enterprise with graph augmented intelligence. Augmented Intelligence is a form of AI that's not artificial intelligence, but augmented intelligence. It has the salient benefits of: having AI accelerated, explainable, and augmented, for instance, offering speed and depth in terms of advanced and networked data analytics, and flexibility in terms of data modeling to reflect real-world scenarios ). Ultipa is founded by entrepreneurs and tech veterans from Silicon Valley and from around the world, backed by world renowned sovereign wealth fund and corporate VCs, is currently serving some of the world's largest banks, insurance companies, securities companies and regulatory bodies. ? Join us in London to explore cutting-edge tech with the top minds in the industry! ?? Event: 11-13 December ?? Learn more: https://lnkd.in/gYR7Z9gf ? #ConnectedData #GraphTech #TechConference #SemTech #DataViz

Knowledge-driven data access means accessing data through an ontology used to represent its meaning at a conceptual level Connecting an enterprise ontology to data that instantiate its concepts is equivalent to building a virtual knowledge graph. A knowledge graph is a semantic layer that allows for searching first for the data (search for things) and only then into the data (search for strings). This type of semantic search simplifies life both for business users, who can access data in a way that aligns with their mental model of the processes that generated the data, and for intelligent agents, who need the right context to operate in unfamiliar domains. To leverage an enterprise ontology for accessing data, it is first necessary to connect it to the data. For this purpose, it is possible e to use ontologies such as DPROD as a basis to represent all metadata related to the developed data products. This is how Andrea Gioia thinks about working with Semantic Data Products. Andrea Gioia has been among the people driving the creation of DPROD, the Data Products Ontology. Join him in Connected Data London 2024, as he shares how to Build your Enterprise Knowledge Graph one data product at a time. This masterclass aims to present a new distributed, iterative, and value-driven approach to knowledge modeling, taking participants from business cases and raw data into the creation of a full knowledge graph. #KnowledgeGraph #DataProduct #Ontology #DataModeling #Masterclass #Event #CDL24 https://lnkd.in/dqeruS7V Link to Andrea’s post in the comments