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Grant Carlson – Development Manager Binh (James) Tham – Lead Solution Architect Integrity Systems Company
Protecting Australia’s red meat industry with interactive data visualisation
YOW! Data 2018
Protecting Australias red meat industry with interactive data - - PowerPoint PPT Presentation
Protecting Australias red meat industry with interactive data - - PowerPoint PPT Presentation
Protecting Australias red meat industry with interactive data visualisation Grant Carlson Development Manager Binh (James) Tham Lead Solution Architect Integrity Systems Company YOW! Data 2018 About us About us Livestock Production
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Market access Customer expectations Safe red meat
F
- d
s a f e t y A n i m a l w e l f a r e B i
- s
e c u r i t y T r a c e a b i l i t y
National Livestock Identification System Livestock Production Assurance National Vendor Declaration
About us
220,000 Customers
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Why traceability matters
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National Livestock Identification System
A Foot & Mouth Disease (FMD) outbreak
$50 Billion
In Australia UK (FMD) outbreak
£11 Billion
in 2001 BSE (Mad Cow)
$7 Billion
2003, 40 countries ban imports From Canada BSE cost
$11 Billion
In USA beef exports 2004-2007
Disease outbreaks are catastrophic
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Australia exports 70% of production
2 4 6 8 10 12 14
United States Brazil EU China India Argentina Australia
‘million
7th largest beef producer in the world World beef production: Ranking of countries
0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
Brazil India Australia United States New Zealand Canada Paraguay
‘million
3rd largest beef exporter in the world World beef exports: Ranking of countries
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How traceability happens
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What happens if a disease is found?
Within48 hours it must be possible to determine
the location(s) where a specified animal has been establish a listing of all cattle that have lived on the same property the current location of all cattle
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Current property
Starting point Property
Trace forward Trace back
Traceability
Cohorts
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National Livestock Identification System
All cattle are RFID tagged All movements recorded
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National Livestock Identification System stats
80,000
users 230,000 Properties 205 million RFID tags (30 million active cattle) Over 500 million movement records 2 to 3 million movements per month
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Cow Catcher – a national test of the system
SQL SQL Scripts Emails
CSV
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Database modelling with graph database
Tag= WJWK0034XBM30929 PIC = WGED0026
Graph = Nodes + Relationships
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Graph = Nodes + Relationships
Database modelling with graph database
Tagx stayed on PICy
- 2. Relationship “stayed” from a TAG to a
PIC
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Graph = Nodes + Relationships
Database modelling with graph database
Tagx stayed on PICy Movements from PICx to PICy
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Graph = Nodes + Relationships
Database modelling with graph database
PIC PIC PIC TAG
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Validate database model with CowCatcher
PIC-A PIC-B PIC-C
Within48 hours it must be possible to determine
A live demonstration with Neo4J TAG
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Architecture
GraphDB
Neo4j browser
DEMO
Queue
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with native browser
Use the built in browser for the POC? Issue 1: Deleting nodes is a nightmare! Have to deal with orphan nodes
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with native browser
Use the built in browser for the POC? Issue 2: No “undo” for expansion
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DEMO BROWSER
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with enhanced browser
Source code: For community
- Added in “cut” button
- Dealt with fixed and floating nodes differently when delete
For tracing purpose:
- Parameterized expansion especially for tracing
- Cohort calculation and expansion for tracing
- Trace further - cohorts of cohorts (not in the demo)
https://github.com/btham/neo4j-browser
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Interactive visualisation can help simplify tracing A graph database model is perfect Building on the open source browser quick and easy – vote for Binh to push the feature request! Eat more beef AgTech is the place to be!
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THANK YOU! Questions? No animals were harmed in the creation
- f this presentation