- Neo4j GraphTour London
GraphTour Brings Neo4j to a City Near You Neo4j is hitting the road to bring a full day of content-rich sessions on how graph databases are revolutionising the modern enterprise. This one-day event will turn you into a graph expert — no matter your technical background or familiarity with graph technology. Meet our experts to hear first-hand about the advantages of Neo4j’s native Graph Platform, which offers not just the Neo4j database, but also Analytics, Data Import and Transformation, Visualization, and Discovery capabilities. There’s a relationship-rich community waiting for you on the Neo4j GraphTour. Pick any of the cities below to find out more about this free event. Sessions in all locations will be in English with the possible exception of local customers. GraphClinics and Solution advice may be in local language. Find out more at: https://neo4j.com/graphtour/ Free to attend, register directly on: https://www.eventbrite.com/e/neo4j-graphtour-london-tickets-52536557257
- Data Lineage in Neo4j
"Data is the new Gold", is something we hear everyone say these days. Often, they will point to "big" data as the source of wealth and knowledge. However, in many cases, we find that clients don't necessarily have "big data" problems, but rather have big "data problems". It's a subtle but important difference. Addressing these data problems often starts with understanding the story behind the data: where does it come from? How does it get processed? Who has access to it? Who manipulates it, and in what way? That understanding and governance is what many enterprises need to understand, and they do so by creating dependency graphs of their data flows - also know as a "Data Lineage" graph. In this presentation we will explore the topic, understand the context, and show how we can solve this challenge with a graph database in ways that we could not do so before. Speaker: Rik Van Bruggen
- Ontologies in Neo4j: Semantics and Knowledge Graphs
Mapping your movie DB in Neo4j to schema.org for publishing? Defining a hierarchy of labels/relationships and having Neo4j interpret it on the fly? KR is the area of AI that enables Explainable Inferences. In this talk, I’ll show how to use KR in the form of Ontologies in Neo4j w practical examples. Ontologies have two main purposes: * being explicit definitions of shared vocabularies for interoperability * being actionable fragments of explicit knowledge that general purpose engines can use for inferencing. Although they have been considered exclusive of the Semantic Web/Linked Data community, we’ll see that Graph Databases like Neo4j can democratize their use by giving them a pragmatic angle. Jesús Barrasa is a Neo4j field engineer based in London. He combines over 15 years of professional experience in consulting and professional services in the Information management space. Prior to joining Neo4j, Jesús worked at Ontology Systems for seven years where he got first hand experience with large graph database deployments in many successful graph-based projects for major telecommunications companies all over the world. Jesús holds a Ph.D. in Computing Science from the Politécnica University of Madrid, where he carried out his research on graph data modeling and Semantic Technologies.
- Knowledge Graphs: The Power of Graph-Based Search
Knowledge Graphs require highly contextual search results - something that is most efficiently realised with graph-based search. In this webinar, we will introduce what Knowledge Graphs are, how they can be used in Neo4j, and the tools and techniques that can be used to construct and enrich a Knowledge Graph, such as NLP, graph querying using Cypher, and inferencing, among others. We will also provide a brief introduction to the property graph model, Neo4j and some of its use cases. Focusing on graph querying, Petra will expand on Cypher and some of its current features, and then describe extensions - either actively being developed or under discussion - taking graph querying (as well as Knowledge Graph management) to the next level. The webinar will conclude with a brief overview of a case study on the eBay ShopBot. Dr. Petra Selmer is a member of our Query Languages Standards and Research group, undertaking research into graph query languages and language standards, with the aim of evolving property graph querying. She also supports the openCypher project at www.opencypher.org. For many years, she worked as a consultant and developer in a variety of different domains and roles and has a PhD in Computer Science from Birkbeck, University of London, where she researched flexible querying of graph-structured data.
- GraphConnect 2018
Join all of your fellow graph enthusiasts GraphConnect NYC 2018! Don’t miss the 3-day incredible line-up of conference talks, presentations, training sessions, demos, and our annual GraphHack! Grab your GraphConnect ticket now! https://graphconnect.com/ Register for GraphConnect training Sessions https://graphconnect.com/#training Sign up for GraphHack (you do not need a GraphConnect ticket to attend) http://bit.ly/graphhack2018 -------------- Also! We’re looking for Neo4j enthusiasts who are looking to be more active in their local community! Interested? Learn about our Neo4j Community Maven program! https://neo4j.com/community/neo4j-community-maven/
- Hands On Neo4j: Building Graph Backed Applications
This session will give you the opportunity to build an application using Neo4j's official drivers. Let us know in the comments which languages you'd be interested in using and we'll make sure we have suitable experts on site. We'll be exploring the driver API in detail and looking at how to assemble all the application layers from the web server down to the database. You will need to bring a laptop suitable for development and have Neo4j installed along with your preferred Python environment. Prerequisites You'll get the most from the session if you've previously attended the Hands on Intro to Cypher session or have played around with Cypher and will be comfortable diving straight in. We'll order pizza (or similar) to keep us going! 6.00 - 6.30: Refreshments, networking and getting Neo4j installed. 6.30: Session starts
- Viewing Contentful Data in Neo4j (Presentation & Hands-on Workshop)
This is a co-hosted event with Contentful, https://www.meetup.com/meetup-group-qCrvByhz/ and JS Monthly, https://www.meetup.com/js-monthly/ Chris Eyre, a Platform Architect at Pottermore (The Digital Heart of the Wizarding World), will demonstrate a utility that he wrote to visualize and query Contentful (a headless, cloud hosted Content Management System) opening opportunities to: - Check content has been entered and published - Locate duplicates - Find orphan entries or images - Allow queries across content types (the Contentful content api is one content type at a time) - Count entries with a certain attribute (i.e. colour) - Determine that a content type is unused - Determine that a field is unused. - Validate complex business rules (such as this field must have three of this entry attached) If time permits, he will also demonstrate deploying this to a Graphene database hosted in Heroku. For workshop, you will need: -A laptop -Neo4j installed (https://neo4j.com/download/) -Node plus your favourite editor -Git -A Contentful account (minimum of free tier) Optionally: -A Heroku account with a credit card attached (it won't be billed for the demo) Heroku CLI **About the Speaker Chris Eyre has worked in a number of industries including Defence (simulating blowing up tanks), Banking (we dropped £1M cash though a robotics pick and pack system test it), Insurance (insuring among other thing Satellites), Futures Trading (investing $20M via an automated genetic algorithm trading system) and Digital Publishing (launching the best selling book of the decade) during his 25 year software development career. He is a loyal Hufflepuff and lives in South East London with his wife and cats. When not coding he enjoys middle distance running, board games and trips to the cinema.
- GraphConnect Preview: Neo4j Drivers, Bloom, Graph Algorithms
In this session we'll be doing a preview of some of the talks for the GraphConnect 2018 conference in New York. We'll have talks on the state of Neo4j drivers, Neo4j Bloom, and a NetworkX API for Graph Algorithms. Please sign up on the Skillsmatter page (https://skillsmatter.com/meetups/11260-neo4j-user-group) The Neo4j Driver Ecosystem in 2018 - Nigel Small Nigel will talk about the evolution of Drivers from community and HTTP, through the introduction of Bolt and official drivers, cluster routing and async. He'll then show the future with new languages (e.g. Go), flow control and the upcoming “connector architecture” platform and resource site for driver authors. Bloom tips and tricks for domain knowledge experts - Ljubica Lazarevic In this talk Lju will introduce tips and tricks to attendees who are domain knowledge experts, but don’t necessarily have a background in SQL/Cypher-led data exploration. The talk will cover: - The importance of a good data model, and how Bloom uses it - Thinking about the types of patterns you can replicate and apply to a specific domain - Converting some Cypher queries into their Bloom equivalents A NetworkX-esque API for Neo4j Graph Algorithms - Mark Needham When I first started learning Python I came across the NetworkX library and always enjoyed using it to run graph algorithms against my toy datasets. Nowadays Neo4j has its own Graph Algorithms library but we have to call that via Cypher procedures which isn’t quite as nice. I wanted to fix that. As a result, a few months ago I started writing a NetworkX-esque API that would provide a nice wrapper around Neo4j’s algorithms. In this talk I’d like to show off the library and how easy it is to use the networkx function calls that you’re used to without having to worry whether your graph will fit in memory in your Python program.
- POLE Investigations with Neo4j
The POLE data model - Person, Object, Location, Event - is commonly applied to security and investigative use cases such as policing, anti-terrorism, border control, and social services. It’s also a great fit for the graph and graph algorithms. Joe Depeau demonstrates how Neo4j, graph algorithms, and the POLE data model can support police and social services investigations and generate real-time insights using the Neo4j browser as well as some sample Tableau visualisations. The speaker Joe Depeau Sr. Presales Consultant, Neo4j Originally from the USA but now living in the UK, Joe has over 20 years of varied experience in the IT industry across a number of domains and specialties. Most recently, Joe has focused on technical pre-sales and solution architecture in the data and analytics space. When not geeking out over data and technology he enjoys camping, tending to his garden and allotment, reading, and playing boardgames and RPGs. He also bakes a mean cheesecake.
- Quick Graphs: Extracting Taxonomies, Strava, Wikipedia, Python Dependencies
In this session Jesús Barrasa and Mark Needham will present 4 15 minute lightning talks showing you how to quickly analyse some fun datasets with Neo4j. We'll show how to extract taxonomies from tagged data, analyse Strava runs, build a Wikipedia Knowledge Graph, and look into Python dependencies Please sign up on the Skillsmatter page (https://skillsmatter.com/meetups/11220-neo4j-july) Taxonomies from tagged data Say we have a dataset of multi-tagged items: books with multiple genres, articles with multiple topics, products with multiple categories. We want to organise logically these tags - the genres, the topics, the categories - in a descriptive but also actionable way. A typical organisation will be hierarchical, like a taxonomy. But rather than building it manually, we are going to learn it from the data in an automated way using Neo4j. Jesus will show how this taxonomy can be used and will present an example on content recommendation / enhanced search. Strava Mark is an avid runner and tracks his run using the popular Strava application. In this talk we'll learn how to load data into Neo4j using APOC's Load JSON procedure and then slice and dice the data using the temporal datatype released in Neo4j 3.4. We'll be able to answer questions such as: * How many runs were there with a pace under 7:30 minutes per mile? * What's my quickest 10k run? * How many runs have I done in a given month? Wikipedia For this QuickGraph Jesus will use data about Wikipedia Categories. You may have noticed at the bottom of every Wikipedia article a section listing the categories it’s classified under. Every Wikipedia article will have at least one category, and categories branch into subcategories forming overlapping trees. It is sometimes possible for a category (and the Wikipedia hierarchy is an example of this) to be a subcategory of more than one parent category, so the hierarchy is effectively a graph. Python Dependencies In this QuickGraph Mark will show you how to find the dependencies between your pip modules and import them into Neo4j. We'll import the dependency graph of a few popular libraries - scikit-learn, tensorflow, pandas, and neo4j - and see what they have between them. If we get time we'll even run graph algorithms over the dependency graph to see what it reveals.