Linked Data and Healthcare and Life Sciences

http://www.w3.org/2009/Talks/0226-cshals-tbl/

Tim Berners-Lee

MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
Southampton University School of Electronics and Computer Science

World Wide Web Consortium

CSHALS 2009

This talk

• Levels of abstractions: links to things
• Sources of data
• Software architectures
• Mixing Vocabularies
• Lessons for Healthcare IT
• Doing your bit

Layers: Link

Layers: Link - 2

Layers: Net hides links

Layers: Web sites

Layers: Web hides computers

Layers: Semantic Web

Layers: Semantic Web

Layers: Semantic Web hides documents

Layers: Semantic Web

Atomic relation

Under the hood 1: Errors

Under the Hood 2: Trust - Provenance

that said...TheSemantic Web abstraction

Doing stuff with data

[Dr. Hans Rosling, Professor of Global Health, Karolinska Institute, Sweden; Gapminder.org]

[Flower analogy: Dr. Hans Rosling, Professor of Global Health, Karolinska Institute, Sweden]

Linked Data

Linked Data

• Use HTTP URIs to identify things
• Serve useful data about those things
• ..using URIs on other people's systems

Linking = to use, in your data, URIs for objects as described on other sites

Incentive: Reuse in ways you could never imagine.

[Chris Bizer, Richard Cyganiak, et.al.]

The Linked Data Mouvement

[Richard Cyganiak, DERI]

[Richard Cyganiak, DERI]

[Richard Cyganiak, DERI]

[Richard Cyganiak, DERI]

[Richard Cyganiak, DERI]

[Richard Cyganiak, DERI]

[W3C Healthcare & Life Sciences Interest Group, Alan Ruttenburg, Jonathan Rees.]

[W3C Healthcare & Life Sciences Interest Group, Alan Ruttenburg, Jonathan Rees.]

Government Data

• Obama commits to US data on the Internet
• UK Office of Public Sector Information
• Your town/state/national governement? UN?!!
• This is our data
• Give us the RAW DATA NOW
  • ... before making fancy front end.

Social Network Data

[Art: David Simonds. Originally for Economist mag. Used by permission]

Community Data

It is a huge world

• Managing your own data
• "Intergrative Informatics" within your company
• Peer-peer exchange within the Healthcare sector
• Reuse across sectors
• Reuse across nations

So..

• Use the same SW standards across these levels.
• Get the benefit of unexpected reuse at each scale.

Healthcare data is one of many many fields with data to be linked

Mixing Vocabularies

Message mixes vocabulary from many cultures

Data mixing: Term by term

dc:title	Data Integration and Transparency
cc:license	<http://creativecommons.org/licenses/by-nc/3.0/>
dc:creator	foaf:name Tim Berners-Lee foaf:homepage <http://ww.w3.org/People/Berners-Lee> foaf:email <mailto:timbl@w3.org>
tk:event	dt:start 2007-06-12T09:00 dt:end 2007-06-12T10:00 dt:summary W3C-WSRI eGovernment workshop geo:lat 38.9 geo:long -77
tk:slides	<http://www.w3.org/2007/Talks/0618-egov-tbl>
tim:slideCount	12

One item may involve data from many ontologies

Healthcare Applications in fact share concepts

Mixture of international, national, industry and local terms

Life sciences

[Diagram: Joanne Luciano, Predictive MedicineDrug discovery demo using RDF, Siderian Seamark and Oracle 10g]

The tradeoff

Local	Wider
Local reuse only	Wider reuse
Local terms	Global or shared terms
Fast	Takes effort

Software Architectures

Software Architectures

Reuse in unimagined ways

Components: Adapting random files

Keep your existing systems running - adapt them

Components: Triple store

Virtual severs actually figure stuff out as well as look up data

Adapting SQL Databases

Keep your existing systems running - adapt them

Probably the biggest unmet need for commercial SW Tools is in this area

See RDB2RDF work at W3C

Adapting XML

Remember- RDF on an HTTP server can always be virtual

Adapting XML: GRDDL

Remember- RDF on an HTTP server can always be virtual

Components: Smart servers

Virtual severs actually figure stuff out as well as look up data

Data Bus: Standards Roadmap

Linked Data -recap

• Use HTTP URIs to identify things
• Serve useful data about those things
• ..using URIs on other people's systems

Data owners should - short term

1. Take inventory
2. Decide priorities, most likely benefits
3. Look for existing ontologies
4. Don't change the way data is currently managed
5. Set up standard (RDF, SPARQL) portals onto existing data
6. Where necessary, adapt or write new ontology bits

Data owners should - medium term

1. Look for more connections
2. Work towards more sharing of terms
3. Do research on top of the widely connected data
4. Migrate some stuff to native RDF
5. offer and ask for feeds to/from partners

Everyone should

1. Demand government data as Linked Data
2. Give and demand data feeds in RDF/SPARQL

Benefits

1. Asking the question never asked before
2. Enhance individual creativity
3. Crisis response
4. Programming at the graph level is more robust
5. Ontologies more robust than DB,XML schemas
6. CXO total view of the company

Motivations

1. Making the world more efficient
2. Solving problems we could never solve before
3. Allowing humanity to be greater than the sum of its parts

Thank You

W3C: w3.org

Thank you for your attention

Slides: http://www.w3.org/2009/Talks/0226-cshals-tbl/