Model-Driven Development of Semantic Mashup Applications with the Open-Source InfoGrid Internet Graph Database

Model-Driven Development of Semantic Mashup Applications With the Open-Source InfoGrid NoSQL Internet Graph Database Johannes Ernst NetMesh Inc. · InfoGrid.org Blog: netmesh.info/jernst · Twitter: @Johannes_Ernst · e-mail: jernst@netmesh.us Most recent version of this presentation is at: http://infogrid.org/wiki/Docs/SlidePresentations License: 2010 Johannes Ernst, Creative Commons Attribution-Share Alike 3.0

Key Points

Key Points • NoSQL is smoking hot in 2010

Key Points • NoSQL is smoking hot in 2010 • Think "object graph" instead of "table" for more effective model-driven development

Key Points • NoSQL is smoking hot in 2010 • Think "object graph" instead of "table" for more effective model-driven development • InfoGrid.org – graph database driven by conceptual-level models with code generator, REST, Java, open-source/commercial

Key Points • NoSQL is smoking hot in 2010 • Think "object graph" instead of "table" for more effective model-driven development • InfoGrid.org – graph database driven by conceptual-level models with code generator, REST, Java, open-source/commercial • Semantically-aware mashups need not be as hard as with an RDBMS

The Mashup Problem ?

Example Object Graph :Complaint :Complaint Name: Pain Name: Blood Pressure HasChiefComplaint :Doctor Name: Smith :OfﬁceVisit Date: 2009/12/15 :OfﬁceVisit Date: 2010/01/01 Prescribed During With Lipitor: By :Doctor Medication Name: Miller Amount: 100 John Doe: Patient ActiveMeds: MRN: 123456789 MedCollection Age: 57 Ibuprofen: Medication Amount: 50

Example Object Graph System 3 :Complaint :Complaint Name: Pain Name: Blood Pressure System 4 HasChiefComplaint :Doctor Name: Smith System 2 :OfﬁceVisit Date: 2009/12/15 :OfﬁceVisit Date: 2010/01/01 Prescribed During With System 1 By Lipitor: :Doctor Medication Name: Miller Amount: 100 System 5 John Doe: Patient ActiveMeds: MRN: 123456789 MedCollection Age: 57 Ibuprofen: Medication Amount: 50

The Problem • Semantically aggregate data from multiple sources • Highly interrelated data • Real-time updates (downstream and upstream) • Decentralized schema evolution

InfoGrid An Internet Graph Database

Types of Data Organization

Types of Data Organization Tabular: SQL relational database

Types of Data Organization Tabular: SQL relational database Documents: NoSQL document database

Types of Data Organization Tabular: SQL relational database Documents: NoSQL Lookup: NoSQL document database key-value database

Types of Data Organization Tabular: SQL Graph of instances: NoSQL relational database graph database : abc attribute: 1 : def : xyz attribute: 2 attribute: 5 : xyz attribute: 4 : def attribute: 3 Documents: NoSQL Lookup: NoSQL document database key-value database

Schema-Less vs. Model-Driven Instances in Graph DB: Type: OfficeVisit Type: By Date: 2009/12/15 Type: With Type: Patient Type: Doctor MRN: 123456789 Name: Miller Age: 57 Type: OfficeVisit Date: 2010/01/01 Type: Patient Type: Doctor MRN: 987654321 Name: Smith Type: OfficeVisit Age: 22 Date: 2009/12/02

Schema-Less vs. Model-Driven Instances in Graph DB: :OfficeVisit Type: OfficeVisit Date: 2009/12/15 Type: By By With Date: 2009/12/15 Type: With Type: Patient John Doe: Patient Type: Doctor :Doctor MRN: 123456789 MRN: 123456789 Name: Miller Name: Miller Age: 57 Age: 57 :OfficeVisit Type: OfficeVisit Date: 2010/01/01 Date: 2010/01/01 :Doctor Jane Doe: Patient Name: Smith MRN: 987654321 Type: Doctor Age: 22 :OfficeVisit Type: Patient MRN: 987654321 Name: Smith Date: 2009/12/02 Type: OfficeVisit Age: 22 Date: 2009/12/02

Schema-Less vs. Model-Driven Instances in Graph DB: :OfficeVisit Type: OfficeVisit Date: 2009/12/15 Type: By By With Date: 2009/12/15 Type: With Type: Patient John Doe: Patient Type: Doctor :Doctor MRN: 123456789 MRN: 123456789 Name: Miller Name: Miller Age: 57 Age: 57 :OfficeVisit Type: OfficeVisit Date: 2010/01/01 Date: 2010/01/01 :Doctor Jane Doe: Patient Name: Smith MRN: 987654321 Type: Doctor Age: 22 :OfficeVisit Type: Patient MRN: 987654321 Name: Smith Date: 2009/12/02 Type: OfficeVisit Age: 22 Date: 2009/12/02 Graph DB Meta-data: Patient By OfficeVisit With Doctor informal MRN Age 1..1 0..* Date 0..* 1..2 Name

Internet Graph Database Web clients URL URL URL… URL… Viewlets Graph Database Probe Probe Probe Probe Probe

InfoGrid Development Process

InfoGrid Development Process 1. Create domain model

InfoGrid Development Process 1. Create domain model 2. Identify data sources & key URLs

InfoGrid Development Process 1. Create domain model 2. Identify data sources & key URLs 3. Develop probes || Develop viewlets (parallel)

InfoGrid Development Process 1. Create domain model 2. Identify data sources & key URLs 3. Develop probes || Develop viewlets (parallel) 4. Integrate and test

InfoGrid Development Process 1. Create domain model 2. Identify data sources & key URLs 3. Develop probes || Develop viewlets (parallel) 4. Integrate and test 5. Incrementally augment: model, probes, viewlets

Why Does It Matter?

Why Does It Matter? • Better: model-driven dynamic graph is better abstraction than inﬂexible tables

Why Does It Matter? • Better: model-driven dynamic graph is better abstraction than inﬂexible tables • Faster: reuse and compose instead of reinvent

Why Does It Matter? • Better: model-driven dynamic graph is better abstraction than inﬂexible tables • Faster: reuse and compose instead of reinvent • Cheaper: development is shorter, but maintenance/increments much simpler

More information http://infogrid.org/ @InfoGrid jernst@netmesh.us

Model-Driven Development of Semantic Mashup Applications with the Open-Source InfoGrid Internet Graph Database

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Model-Driven Development of Semantic Mashup Applications with the Open-Source InfoGrid Internet Graph Database Presentation Transcript

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