Graph Hack 2016

(graphs)-[:4]->(good)

TLDR

Build something cool with Neo4j under the theme graphs4good
Register your project and team here
Present your project
Win cool prizes

Overview

WIFI

Network: ---- Passsword: ----

Schedule


6:00-6:30	Arrive
6:30-7:00	Introduction, form teams, start hacking
7:00-9:00	Hacking
9:00-9:30	Teams present
10:00	Prizes / Awards

Rules

Teams!

Teams are encouraged, but individual participation is allowed.
Teams may have up to 5 participants, but only 4 prizes are awarded per team.
Register your project and all team mates here

Winners

Most impactful idea
Best complete application
Best data visualization
Best use of Cypher

Criteria for judging - all projects must use Neo4j

Creativity (perhaps including merging disparate data sources)
Use of Cypher and Neo4j
Interesting new information uncovered
Quality of presentation (perhaps including visualization)
Completeness

Prize Distribution

A variety of prizes will be on display throughout the event
Each member of winning teams may choose (1) prize
First place team will be announced and choose prizes first, followed by 2nd place team, followed by 3rd place team
As long as prize inventory allows, honorable mention teams will be announced and be able to choose prizes
Each prize is limited in quanity. Within each winning team, individuals will need to decide who gets which prize.

Prizes

Airpod
Echo Show
Nest Camera
BB8 Droid
Google Home
Echo Dot
Exclusive GraphHack T-shirts!

Datasets

Trends in Food Prices, Food Consumtion Scores, and Poverty Baselines, by Country

The Humanitarian Data Exchange is an open platform for sharing data, launched in July 2014. The goal of HDX is to make humanitarian data easy to find and use for analysis.

bit.ly/foodgraph
username: foodgraph
password: foodgraph

Fake News Graph

bit.ly/fakenewsgraph
username: fakenewsgraph
password: fakenewsgraph

Panama Papers + (Offshore Leaks + Bahamas Leaks)

Neo4j Sandbox

NOTE: This dataset has an interactive Neo4j Browser guide for exploring the data:

Legis-graph (US Congress)

Neo4j Sandbox
:play http://guides.neo4j.com/legisgraph

Campaign Finance - FEC Filings

Available on Neo4j Sandbox with this link, then look for "IRE 2017 Workshop" use case.

US Election Data

Election Tweets

Download

wget http://demo.neo4j.com.s3.amazonaws.com/electionTwitter/neo4j-election-twitter-demo.tar.gz
tar -xvzf neo4j-election-twitter-demo.tar.gz
cd neo4j-enterprise-3.0.3
bin/neo4j start

NOTE: This dataset has an interactive Neo4j Browser guide for exploring the data:

Election Forecast

Fivethirtyeight has made the data behind their famous election forecast publicly available:

http://projects.fivethirtyeight.com/2016-election-forecast/summary.json

You can easily pull this into Neo4j using apoc.load.json:

CALL apoc.load.json("http://projects.fivethirtyeight.com/2016-election-forecast/summary.json") YIELD value AS data
RETURN data

Hillary Clinton's Emails

// Creating the graph
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "https://s3-us-west-2.amazonaws.com/neo4j-datasets-public/Emails-refined.csv" AS line
MERGE (fr:Person {alias: COALESCE(line.MetadataFrom, line.ExtractedFrom,'')})
MERGE (to:Person {alias: COALESCE(line.MetadataTo, line.ExtractedTo, '')})
MERGE (em:Email { id: line.Id })
ON CREATE SET em.foia_doc=line.DocNumber, em.subject=line.MetadataSubject, em.to=line.MetadataTo, em.from=line.MetadataFrom, em.text=line.RawText, em.ex_to=line.ExtractedTo, em.ex_from=line.ExtractedFrom
MERGE (to)<-[:TO]-(em)-[:FROM]->(fr)
MERGE (fr)-[r:HAS_EMAILED]->(to)
ON CREATE SET r.count = 1
ON MATCH SET r.count = r.count + 1;

// Updating counts
MATCH (a:Person)-[r]-(b:Email) WITH a, count(r) as count SET a.count = count;

Fivethirtyeight

The Fivethirtyeight teams does an amazing job of providing the data behind many of their stories in their Github repo. There are a lot of possibilities but here are a few ideas we hacked up:

`hip-hop-candidate-lyrics`

Import

LOAD CSV WITH HEADERS FROM "https://raw.githubusercontent.com/fivethirtyeight/data/master/hip-hop-candidate-lyrics/genius_hip_hop_lyrics.csv" AS row
MERGE (c:Candidate {name: row.candidate})
MERGE (a:Artist {name: row.artist})
MERGE (s:Sentiment {type: row.sentiment})
MERGE (t:Theme {type: row.theme})
MERGE (song:Song {name: row.song})
MERGE (line:Line {text: row.line})
SET line.url = row.url
MERGE (line)-[:MENTIONS]->(c)
MERGE (line)-[:HAS_THEME]->(t)
MERGE (line)-[:HAS_SENTIMENT]->(s)
MERGE (song)-[:HAS_LINE]->(line)
MERGE (a)-[r:PERFORMS]->(song)
SET r.data = row.album_release_date

Crime data

Many governments use the Socrata data portal software to make their data (i.e. crime, transportation, etc) available. This means that we can use apoc.load.json to import data directly from any Socrata site. For example, to import San Francisco crime data:

CALL apoc.load.json("https://data.sfgov.org/resource/cuks-n6tp.json?$limit=5000&$offset=0") YIELD value AS crime
MERGE (c:Crime {incidntnum: crime.incidntnum})
ON CREATE SET c.address=crime.address, c.time=crime.time, c.dayofweek=crime.dayofweek
MERGE (cat:Category {name: crime.category})
CREATE (c)-[:HAS_CATEGORY]->(cat)
MERGE (dis:District {name: crime.pddistrict})
CREATE (c)-[:OCCURRED_IN]->(dis);

Other resources

Beyond the resources listed above.

We don't have Neo4j import scripts or graph exports for these, but we think they might be interesting to explore:

Resources

Neo4j

You'll need to use Neo4j to participate in the hackathon. You can download Neo4j here or use one of the hosted versions above.

APOC - Awesome Procedures on Cypher

Graph algorithms, data import, job scheduling, full text search, geospatial, ...

Neo4j Folks

Grab your friendly Neo4j staff and community members if you have any questions.

neo4j-meetups/graph-hack-nyc-2017