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Benjamin Niedermann Evmorfia Argyriou

From Connected Data to Meaningful Visualisations

A Talk by Evmorfia Argyriou and Benjamin Niedermann

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About this Talk

Graph visualisations make complex data more accessible, but creating a meaningful graph visualisation is far from trivial. In this masterclass, we present a pipeline for transforming raw data into a visualisation that answers specific user questions.

This class is designed for anyone working in data analysis, including data scientists, application developers, and researchers. We use free tools accessible to everyone.

By the end of the masterclass, participants will have gained hands-on experience in transforming raw data into meaningful graph visualisations.

Description

Techniques of data analysis allow users to extract valuable insights from raw data. By exploring this data, they can answer specific questions, identify patterns, and make informed decisions. Graph visualisations enhance this process by making complex data more accessible.

In this masterclass, you will discover how to transform raw data into meaningful graph visualisations, covering the entire pipeline from data to the final visualisation. First, we provide an overview of how to identify key questions that can be answered with graph visualisations. Then, using Jupyter Notebook—a popular and free tool for data analysts—and Neo4j databases, you will learn how to prepare data and apply graph analysis algorithms such as centrality and other relevant measures.

Finally, you will explore how to select the appropriate visualisation style, focusing on what should be emphasised and how information can be effectively encoded in the visualisation.

Key Topics

  • Graph visualisations: enhancing data accessibility and making complex data easier to understand
  • Graph analysis techniques: extracting insights from structured data and identifying patterns
  • Visualisation style selection: choosing appropriate visualisation styles based on data
  • Information encoding: emphasising non-structural data in graph visualisations

Target Audience

  • Data Scientists and Analysts
  • Data Engineers
  • Application and Database Developers
  • Researchers and Academics

Goals

Get hands-on experience transforming raw data into meaningful graph visualisations by identifying key questions, preparing and analysing data, and selecting appropriate visualisation styles to effectively communicate insights.

Session outline:

  • Part 1 – Brief introduction
  • Questions that can be answered with graph visualisations.
  • Aspects to take into account when creating a graph visualisation.
  • Part 2 – Prepare the data
  • Present the dataset and the underlying graph structure.
  • Properties of the graph structure: e.g., centrality, or other measures.
  • Part 3 – Visualise data
  • Choose the most effective visualisation style and determine which elements of the structure should be emphasised.
  • Style the graph visualisation: Decide how to encode information through the styling of nodes and edges.

Format

The masterclass combines a lecture format with hands-on coding exercises.

We will be using Jupyter or Google Colab notebooks (participants can choose) with standard Python packages. Data will be retrieved from a Neo4j database, which we will provide. For graph analysis, we will use the Graph Data Science Library. For data visualisation, we will utilise the yFiles Jupyter Graphs for Neo4j widget. This is an open-source wrapper for yFiles Jupyter Graphs that offers a simple way to visualise Cypher queries executed against Neo4j databases.

Level

Beginner - Intermediate

Prerequisite Knowledge

Basic Python and familiarity with standard packages (pandas, numpy, scikit-learn)

11 December 2024, 09:00 AM

Network Science & DataViz Stage

09:00 AM - 11:00 AM

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About The Speakers

Evmorfia Argyriou

Evmorfia Argyriou

Senior software engineer, yWorks GmbH

Dr. Evmorfia Argyriou is a senior software engineer at yWorks GmbH, with over 10 years of industry experience in developing advanced software solutions for diagram and network visualisation.

Evmorfia Argyriou

Benjamin Niedermann

Benjamin Niedermann

senior software engineer, yWorks GmbH

Dr. Benjamin Niedermann is a senior software engineer at yWorks GmbH, where he focuses on developing algorithms for automatic graph layouts.

Location

Convene 133 Houndsditch

133 Houndsditch, London

Neo4j

Neo4j, the Graph Database & Analytics leader, helps organizations find hidden relationships and patterns across billions of data connections deeply, easily, and quickly.

Platinum Sponsor

Ontotext

Connect the dots of your data! Ontotext helps enterprises to lower data management costs by up to 30%, enable data fabric architectures, create digital twins, utilize Graph RAG benefits, and take information delivery from days to minutes!

Gold Sponsor

Semantic Web Company / PoolParty

The vendor of PoolParty Semantic Suite. Graph-based text mining, recommender systems, and data fabric solutions.

Gold Sponsor

yWorks

yWorks specializes in the development of professional software solutions that enable the clear visualization of diagrams and networks.

Gold Sponsor

Oracle

This global cloud tech company offers infrastructure and software to enhance organizational innovation and efficiency. Its autonomous database delivers top performance, security, and cost savings. Supporting businesses, governments, and research, the company embraces diversity and fosters growth.

Gold Sponsor

Ultipa

Ultipa builds next-gen graph XAI & real-time database empowering smart enterprises w/ smooth digital transformations.

Sliver Sponsor

Oxford Semantic Technologies

Oxford Semantic Technologies (OST) spun out from the University of Oxford and was acquired by Samsung in 2024. OST provides AI software to extract insights from big data, solving issues like medical diagnostics and financial crime. One founder is a BCS Lovelace Medal winner.

Sliver Sponsor

FlureeDB

Web3 data platform built on standards. Fluree powers connected, secure, and agile data ecosystems.

Bronze Sponsor

Senzing

Senzing is the first to deliver real-time, artificial intelligence for entity resolution. Senzing software enables organizations of all sizes to gain highly accurate and valuable insights about who is who and who is related to whom in data.

Bronze Sponsor

Semantic Partners

We partner with you, and your chosen semantic stack, to liberate your data's meaning from isolated silos.

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Epsilla

All-in-one platform to create AI agents powered by your private data and knowledge. Make GenAI prototype to production 10 times faster. We are backed by Y Combinator. Start free today: https://epsilla.com

Bronze Sponsor

Neural Alpha

Since 2016 Neural Alpha have delivered cutting edge, sustainability centric Connected Data solutions for blue-chip corporates, financial institutions, Governments and NGOs. Our bespoke software & data solutions fuse AI, Knowledge Graphs, Taxonomies & other technologies for unprecedented insights.

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