Vital.AI's Big Data App Platform allows creating data-driven apps rapidly.

1. Creating Intelligent Apps
with Semantics & Big Data
O c t o b e r 2 , 2 0 1 3
Marc C. Hadfield, Founder
Email: marc@vital.ai
Thursday, October 3, 13

2. <introduction>
Marc Hadfield
Founder of Vital.AI
Vital.AI
Big Data Application Platform:
Semantics & Big Data in one platform,
combining multiple Data Analysis
techniques.
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3. Intelligent Applications
Development Processes
Business Value
Today:
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4. Intelligent Applications:
...learn from experience.
Thus, are experience-driven: data-driven.
“self-optimizing”
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5. Data-Driven Applications
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6. Moderni.st
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7. Moderni.st
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8. Personal Agent App
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9. Why are data-driven applications different?
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10. User Interface
Business Logic
Database
Traditional Applications
Why are data-driven applications different?
“sta%c”
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11. Why are data-driven applications different?
“dynamic”
User Interface
Business Logic
Events
Data-Driven Applications
Data
Analytics
Derived Behavior
Logic
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12. Data-Driven Applications use
many different technologies,
with many different skill sets:
greater power, higher cost.
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13. Why do we want a data-driven application?
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14. What are the components of a data-driven
application?
Data Collection
Dynamically Adjust Behaviors
Data Analysis / Feedback
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15. Implementing a Data-Driven Application.
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16. Implementation Goals:
Off the shelf?
Minimize Impedance Mismatch:
Mobile/Web User Interface vs.
Semantic vs.
Big Data vs.
...
Efficient Development Processes
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17. Vital.AI Platform Stack
Clean separation of
responsibilities and skill sets.
Rapid Development of Data-Driven
Apps.
VitalSigns: Ontology-based Data
Model.
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18. Vital Prime
REST Interface
Collects Real-Time Events
Database Interfaces:
HBase, Allegrograph, ...
Workflow Interface
Script Engine
In-Memory Analytics
User State Management
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19. Vital Flows
Implements Workflows:
Natural Language Processing
Run Predictive Analytics
Graph Analytics
Logical Inference
Many open-source components in a common workflow framework.
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20. Hadoop
Implements Big Data Analysis:
Machine Learning
Build Predictive Models
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21. Vital Core Ontology
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22. Vital Core
Ontology
Vital Domain
Ontology
Application
Domain Ontology
Extending the Ontology
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23. Generating Data Bindings with VitalSigns:
Ontology VitalSigns
Groovy Bindings
Semantic Bindings
Hadoop Bindings
Prolog Bindings
Graph Bindings
HBase Bindings
JavaScript Bindings
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24. person123.name = "John"
person123.worksFor.company456
<person123> <hasName> "John"
<worksFor123> <hasSource> <person123>
<worksFor123> <hasDestination> <company456>
<worksFor123> <hasType> <worksFor>
person123, Node:type=Person, Node:hasName="John"
worksFor123, Edge:type=worksFor, Edge:hasSource=person123, Edge:hasDestination=company456
Groovy
RDF
HBase
Data Representations
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25. Editing the Ontology
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26. Developing with the Ontology in UI, Hadoop, NLP, Scripts, ...
Node:Person Node:PersonEdge:hasFriend
Set<Friend> person123.getFriends()
“Best Practices”
in Ontology
Development.
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27. Data Analysis
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28. Using Natural Language Processing
Topic Categorization Extract Entities
Dialogue System Entity Normalization
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29. Using Graph Analytics
PageRank, Centrality,
Interest Graph, ...
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30. Using Machine Learning
Implemented via Hadoop
Algorithms from Mahout
Build Predictive Models
Models used in Workflows
Data defined in Ontology
Classification, Clustering...
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31. Data Visualization - Cytoscape
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32. Data Management - Dashboard, Wiki
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33. Examples
Shopping Recommendation App
Personal Agent App
Content Recommendation App
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34. Content Recommendation
REST Interface
Vital Client
Vital Prime
Vital Flow Queue
Integrator NLP HadoopML Model
S3
Elastic Map/Reduce
Mahout
300M Users
100K Publishers
NLP
Machine Learning
Content + User Signals
Recommendations
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35. Personal Agent
Dialogue System
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36. Personal Agent
Interest Graph
Recommendations
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47. Moderni.st
App Server
Vital
Prime
Integrator
Flow
NLP Flow Logger
Flow
Inference
Flow
VITAL API
VitalSigns
Web Browser /
Mobile Device
HDFS
Hbase Hadoop Jobs
Mahout
Vital Flows
Flume
Allegrograph
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48. Creating an Intelligent App
Create User Interface.
Use Vital Client, Send Signals
Create App Ontology, including
Domain Classes & Events/Signals
Define Workflows for Data Processing
Define Predictive Models, Build Models
Create scripts for App Functionality
Deploy Components
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49. Development Processes
Use the right tool for the right job,
& the right people for the right job.
Integrated Framework.
Coordinate on Ontology.
Eliminate Data Mis-Matches.
Clean code separation of “paradigms.”
Solve “Variety” Big Data challenge.
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50. Business Value
Intelligent App.
Efficient, Rapid Development.
Flexibility to learn, adapt, improve.
Greatly reduce risk.
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51. For more information, please contact:
Marc C. Hadfield, Founder
E: marc@vital.ai
P: 917.463.4776
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THANKYOU!
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