Overview

• Semantic Web adoption curve
• Choosing URIs
• Supporting URIs

Build on existing systems

Innovators have now made lots of exciting new systems, but:

• Practical deployment involves interfacing to existing systems
• Don't change way data is managed
• Put on a thin layer adaptor, such as
  • GRDDL adaptor for XML
  • Adaptor for SQL (e.g. D2R server, R2O, SPA-SQL, DBView)
  • Adapt to generate RDF and/or support SPARQL

Practical Semantic Web

• A web of data.
• Don't change existing practices
• Instrument and augment
• Use standards: (RDF, OWL, SPARQL*, RIF**)

Practical Semantic Web

• Take inventory of your data to see what you have
• Modeling data to see how it connects
• Map each thing into URI space
• Connect on RDF views, SPARQL services
• Agree on ontologies with others

Bottom-up ontology design

1. Start with existing SQL databases
2. Add information about how keys and foreign keys connect
3. Remove other artifacts of the DB schema
4. Note relationships to other people's concepts

RDF views of data

RDF is to data what HTML is to documents

• Technique: PHP scripts accessing relational DB
• XSLT or XQ scripts accessing XML DB
• Looking up a URI for something gives you info about it
• Relations with other things expressed using their URIs

SPARQL access to data

Query interface

• Use the same mapping as the RDF views
• XSLT or XQ scripts accessing XML DB
• Looking up a URI for something gives you info about it
• Relations with other things expressed using their URIs

SPARQL - the universal query service

• How many Web Services ask for info?
• Each can be SPARQL
• Extensible - without re-architecting
• Independent of database schema/XML schema
• Combinable
• Optimizable - mapping, caching, federating

Clients of the RDF bus

New data applications can be built on top of RDF bus, for example:

Components: Adapting random files

Keep your existing systems running - adapt them

See: Wiki list of Converters To RDF

Example: Course participants

I had a list of course participants collected as an address-book group in Thunderbird.

• LDIF file from Thunderbird
• ldif2n3.py converter
• N3 file generated
• RDF/XML file
• Makefile

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

Tool: dbview.py

• By Dan Connollyand Rob Crowell/MIT
• source
• Point it raw database
• Add metadta to improve the mapping
• Serves linked RDF
• Tested against mySQL
• unsupported

Tool: D2R Server

• By Chris Bizer and Richard Cyganiak, Freie Universität Berlin
• D2R server home page
• Uses a mapping file in N3
• Tested with Oracle, MySQL, PostgreSQL
• Serves linked RDF and SPARQL
• Also provides HTML interface
• 6 public servers (2007/1), Eg: DBLP bibliographic data
• unofficially supported

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

(See: GRDDL Spec.; Connolly, Practical Semantic Web Deployment with Microformats and GRDDL (slides))

Components: Smart servers

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

Timing strawman

• This year. Have your data modeled. Build RDF and SPARQL access for analytics and CEO questions as a start.
• Next year. Build added value on top of your data web:
  • Analysis - using rules, programs on RDF API
  • Visualization
  • Sanity checks - OWL, Rule-based, etc.
  • Offer filtered RDF data to partners
• In 2 years, demand your partners give you RDF for data which is important to the relationship
• In 3 years, Build new applications on top of semantic web base
• In 10 years, Start to replace legacy systems with semantic-web native systems

More Information

• This presentation : http://dig.csail.mit.edu/2007/Talks/0108-swdb-tbl/

This work is licensed under a Creative Commons Attribution - Non-Commercial - No Derivatives 2.5 License.