Discovering Corruption & Innovating Health Care with Graphs
Details
Food provided by Neo4j (https://neo4j.com/)
Drexel University (http://drexel.edu/) location provided by CompassRed Data Labs (http://compassred.com/)
Discovering Corruption with Data: Pulitzer Prize-winning Panama Papers
(by Ryan Boyd)
The Panama Papers (https://en.wikipedia.org/wiki/Panama_Papers) represent one of the world's largest data leaks in history: 11.5 million records exposing a system that enables crime, corruption, and wrongdoing, hidden by secretive offshore companies. Over 400 journalist members of the International Consortium of Investigative Journalists (ICIJ) worked for a year mining and investigating the data stored in a Neo4j graph database. This resulted in the resignation of the PM of Iceland, Supreme Court hearings for Pakistan's PM, the arrest of people money laundering for Mexican drug cartels, and plenty of more investigations and regulatory reforms.
In this talk, Ryan Boyd will demonstrate how Neo4j graph database powered this investigation, showing queries and visualizations highlighting the relationships between offshore companies, corporate officers, law firms and addresses. He'll use the Neo4j Sandbox to show you how you too can dive into the data which has been opened up by the ICIJ for the world to investigate. You'll learn to write basic Cypher queries for finding nodes, relationships, and paths. We'll also provide an intro to how Graph Algorithms in the APOC open source library can help better understand the networks in the Panama Papers data.
About Ryan Boyd:
Ryan is a San Francisco-based software engineer, authNZ geek, data geek and graph geek. He's Director of Developer Relations for Neo4j, an open source graph database which powers connected data analysis in data journalism, cancer resource, and some of the world's top companies. Prior to Neo4j, he was Head of Developer Relations for Google Cloud Platform and worked on over 20+ different APIs and developer products during his 8 years at Google. Ryan is the author of "Getting Started with OAuth 2.0," published by O'Reilly. He no longer skydives now that he has a young daughter, but enjoys the adventures of sailing and cycling.
Introduction to Hetnets
(by Daniel Himmelstein)
Hetnets are networks with multiple node and relationship types. He will discuss when hetnets are the right tool for integrating and analyzing diverse types of data. Specifically, he'll showcase Project Rephetio (https://thinklab.com/p/rephetio), which predicts new uses for existing drugs. This project created Hetionet (https://neo4j.het.io/browser/), a network with 2.25 million relationships of 24 types, allowing researchers to ask questions that span the many realms of biomedical knowledge.
About Daniel Himmelstein
Daniel Himmelstein (https://twitter.com/dhimmel) is a "digital craftsman of the biodata revolution" who works in the Greene Lab (http://www.greenelab.com/) at Penn. In 2016, he received his PhD in Biological & Medical Informatics from UCSF. Daniel leads the Cognoma (https://github.com/cognoma/cognoma) (DataPhilly) Datathon and was a finalist for "Scientist of the Year" in the 2016 Philly Geek Awards. His research focuses on integrating open data to uncover the secrets of human health.
Also, as an added treat....!!
Real-time Meatspace Data Science
(by Michael Becker and Jason Walsh)
Our very own, Michael Becker, (founder of DataPhilly and Data Scientist at University of Pennsylvania Health System) along with his co-worker, Jason Walsh, will be doing a sneak peak of their talk scheduled at the Data Intelligence Conference (http://www.data-intelligence.ai) on 6/24!!
Discovering Corruption & Innovating Health Care with Graphs