Semantic Web-based E-Commerce:
  The GoodRelations Ontology

     Semantic Technology Conference
              June 15, 20...
Part I: E-Commerce on the Web
History Lesson: Search for Suppliers
      1992: 1 Week      2009: 1 Minute




   Martin Hepp,                           ...
But: Search for Suppliers, 2009




   Martin Hepp,                         4
mhepp@computer.org
Limitations of the Web, 2009
Specificity vs. Keyword-based Search
•    Synonyms
•    Homonyms
•    Multiple languages
•    No parametric
     search


...
No Unified View: Jumping Back and Forth
           Across Data Silos
                                  Site   Page        ...
We know the best hits only when done.
                                Site   Page          Page
                          ...
Limited Ability to Reuse Data




   Martin Hepp,                          9
mhepp@computer.org
The Web: A Bottleneck for Sharing
            Product Data




   Martin Hepp,                        10
mhepp@computer.org
Part II: E-Commerce based on a
Web of Linked Data: The Vision
Web of Linked Data (“Semantic Web”)




   Martin Hepp,                   12
mhepp@computer.org
Core Web of Linked Data Technology Pillars
•    URIs for everything
•    RDF: A data model for exchanging conceptual graph...
E-Commerce on the Web of Linked Data




   Martin Hepp,                  14
mhepp@computer.org
Goal: A Unified View on Commerce
            Data on the Web
                                                  Extraction
...
Use Case 1: Product Search
• Find all MP3 players
  that have a USB
  interface and a color
  display, and sort them
  by ...
Use Case 2: Product Model Data Reuse (PIM)
                       World Wide Web
                                         ...
Use Case 3: Fine-grained Affiliate
              Marketing
                                              Offers of
       ...
Part III: How?

The GoodRelations Vocabulary
What Do We Need?
• Vocabularies                • Tools
   – Product or service       • Applications
     types
   – Busine...
The GoodRelations Vocabulary
 • A universal and free Web
   vocabulary for adding
   product and offering data
   to your ...
GoodRelations: Scope




   Martin Hepp,                        22
mhepp@computer.org
GoodRelations Design Principles
• Keep simple things       Lightweight         Heavyweight
  simple and make          Web ...
GoodRelations: License
 • Permanent,
   royalty-free access
   for commercial and
   non-commercial use.




            h...
Albert Einstein on Ontology
                  Engineering
quot;Make everything as simple as possible, but
               n...
What Makes for A Good Ontology?
• Main Contribution: Avoiding reclassification of
  phenomena
    – Allows for cognitive a...
Data, Standards, Ontologies




   Martin Hepp,                         27
mhepp@computer.org
Basic Structure of Offers

                                         Object or
Agent 1             Promise
                ...
GoodRelations: One Single Schema for
A Consolidated View on E-Commerce
                Data         Extraction
           ...
On the Shoulders of Giants




  A Unified View of Data on the Web
   Martin Hepp,                         30
mhepp@comput...
Minimal Example




   Martin Hepp,                        31
mhepp@computer.org
The Minimal Scenario
• Scope
    –   Business entity
    –   Points-of-sale
    –   Opening hours
    –   Payment options
...
The Simple Scenario
• Scope: Minimal scenario plus
    – Range of products or services
    – Business functions
    – Elig...
The Comprehensive Scenario
• Scope: Simple scenario plus
    –   Individual products or services
    –   Product features
...
Product Model Data Scenario
• Scope
    – Individual product
      models
    – Quantitative and
      qualitative feature...
Part IV: Trends

Data Sets & Industry Pick-up
Others Do Care: Pick-up in Industry
 • Smart Information Systems
 • ebSemantics
 • Yahoo! SearchMonkey
 • Virtuoso Sponger...
Ping The Semantic Web, May 25




   Martin Hepp,                      38
mhepp@computer.org
Yahoo Enhanced by SearchMonkey




   Martin Hepp,                    39
mhepp@computer.org
Yahoo Enhanced SearchMonkey




   Martin Hepp,                    40
mhepp@computer.org
GoodRelations Page Views




   Martin Hepp,                      41
mhepp@computer.org
Linked Open Commerce Dataspace



                     ...forthcoming




   Martin Hepp,                       42
mhepp@c...
Part V: Tools and Resources
GoodRelations User‘s Guide („Primer“)




   http://www.heppnetz.de/projects/goodrelations/primer/
   Martin Hepp,        ...
GoodRelations Annotator




http://www.ebusiness-unibw.org/tools/goodrelations-annotator/
    Martin Hepp,                ...
GoodRelations Validator




http://www.ebusiness-unibw.org/tools/goodrelations-validator/
    Martin Hepp,                ...
RDF2dataRSS Tool




     http://www.ebusiness-unibw.org/tools/rdf2datarss/

   Martin Hepp,                              ...
osCommerce Extension




http://code.google.com/p/goodrelations-for-oscommerce/

   Martin Hepp,                          ...
Joomla/VirtueMart Extension




     http://code.google.com/p/goodrelations-for-joomla/

   Martin Hepp,                  ...
Part VI: Recommendations

What any business should do...
       ...immediately!
Why Should I Bother?
 • Web Shops: Better visibility in latest generation
   search engines (e.g. Yahoo)
     – Same holds...
What Should I Do?
 • Web Shops: Create a GoodRelations data dump of
   your range of offers (rather simple)
 • Vendors of ...
Step-by-Step (1)
• Data Sources                   • Data Delivery Options
    –   Form-based data entry
                  ...
Step-by-Step (2)
• Update Mechanism & Data Management
    – PHP on demand
    – Script-based data dump
• Publishing the Da...
Part VII: The Sky Is the Limit

 Semantics in Affiliate Models,
  Serendipity, Matchmaking
Thank you!
                        http://purl.org/goodrelations/

                          Prof. Dr. Martin Hepp
       ...
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Semantic Web-based E-Commerce: The GoodRelations Ontology

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Semantic Web-based E-Commerce: The GoodRelations Ontology
Presentation at the Semantic Technology Conference, June 15, 2009

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Semantic Web-based E-Commerce: The GoodRelations Ontology

  1. 1. Semantic Web-based E-Commerce: The GoodRelations Ontology Semantic Technology Conference June 15, 2009 Martin Hepp http://www.unibw.de/ebusiness/ http://purl.org/goodrelations/
  2. 2. Part I: E-Commerce on the Web
  3. 3. History Lesson: Search for Suppliers 1992: 1 Week 2009: 1 Minute Martin Hepp, 3 mhepp@computer.org
  4. 4. But: Search for Suppliers, 2009 Martin Hepp, 4 mhepp@computer.org
  5. 5. Limitations of the Web, 2009
  6. 6. Specificity vs. Keyword-based Search • Synonyms • Homonyms • Multiple languages • No parametric search Martin Hepp, 6 mhepp@computer.org
  7. 7. No Unified View: Jumping Back and Forth Across Data Silos Site Page Page Search Engine Results Search Engine Results 1 1 2 Search Engine Results Search Engine Results Page Page 3 4 Site Page 2 5 Site Page Page Page 3 6 7 8 Martin Hepp, 7 mhepp@computer.org
  8. 8. We know the best hits only when done. Site Page Page 1 1 2 Search Engine Results Page Page 3 4 Site Page 2 5 Site Page Page Page 3 6 7 8 Martin Hepp, 8 mhepp@computer.org
  9. 9. Limited Ability to Reuse Data Martin Hepp, 9 mhepp@computer.org
  10. 10. The Web: A Bottleneck for Sharing Product Data Martin Hepp, 10 mhepp@computer.org
  11. 11. Part II: E-Commerce based on a Web of Linked Data: The Vision
  12. 12. Web of Linked Data (“Semantic Web”) Martin Hepp, 12 mhepp@computer.org
  13. 13. Core Web of Linked Data Technology Pillars • URIs for everything • RDF: A data model for exchanging conceptual graphs based on triples – Triple: (Subject, Predicate, Object) – Exchange syntax: RDF/XML, N3, etc. • RDFS and OWL: Formal languages for that help reduce ambiguity and codify implicit facts – foo:human rdfs:subClassOf foo:mammal • SPARQL: Standardized query language and endpoint interface for RDF data • LOD Principles: Best practices for keeping the current Web and the Web of Data compatible Martin Hepp, mhepp@computer.org 13
  14. 14. E-Commerce on the Web of Linked Data Martin Hepp, 14 mhepp@computer.org
  15. 15. Goal: A Unified View on Commerce Data on the Web Extraction Arbitrary Query and Reuse Manufacturers Retailers Payment Delivery Product Model Warranty Master Data Shop Spare Parts & Offerings Auctions Consumables Martin Hepp, 15 mhepp@computer.org
  16. 16. Use Case 1: Product Search • Find all MP3 players that have a USB interface and a color display, and sort them by weight (lightest first). ...on a Web Scale! Martin Hepp, 16 mhepp@computer.org
  17. 17. Use Case 2: Product Model Data Reuse (PIM) World Wide Web World Wide Web Manufacturer Retailer / Web Shop Structured Structured Data on Data on Products Products and Product Specifications: and Services Type of Product, Features etc. Services Martin Hepp, 17 mhepp@computer.org
  18. 18. Use Case 3: Fine-grained Affiliate Marketing Offers of computer add-ons that have an USB interface Screenshot from http://en.wikipedia.org/wiki/USB Martin Hepp, 18 mhepp@computer.org
  19. 19. Part III: How? The GoodRelations Vocabulary
  20. 20. What Do We Need? • Vocabularies • Tools – Product or service • Applications types – Businesses – Offerings • Data Sets – Product model data – Businesses, contact details, opening hours – Offering data Martin Hepp, 20 mhepp@computer.org
  21. 21. The GoodRelations Vocabulary • A universal and free Web vocabulary for adding product and offering data to your Web pages. • Compatible with all relevant W3C standards and recommendations – RDF – OWL http://purl.org/goodrelations/ Martin Hepp, 21 mhepp@computer.org
  22. 22. GoodRelations: Scope Martin Hepp, 22 mhepp@computer.org
  23. 23. GoodRelations Design Principles • Keep simple things Lightweight Heavyweight simple and make Web of Data Web of Data complex things possible LOD OWL DL • Cater for LOD and OWL RDF + a little bit DL worlds • Academically sound • Industry-strength engineering • Practically relevant Martin Hepp, 23 mhepp@computer.org
  24. 24. GoodRelations: License • Permanent, royalty-free access for commercial and non-commercial use. http://purl.org/goodrelations/ Martin Hepp, 24 mhepp@computer.org
  25. 25. Albert Einstein on Ontology Engineering quot;Make everything as simple as possible, but not simpler.“ Albert Einstein Martin Hepp, 25 mhepp@computer.org
  26. 26. What Makes for A Good Ontology? • Main Contribution: Avoiding reclassification of phenomena – Allows for cognitive and computer processing at the level of category membership • Good ontologies provide universally valid yet specific categories • Category membership should remain valid – Over time – Between individuals – Across contexts Martin Hepp, 26 mhepp@computer.org
  27. 27. Data, Standards, Ontologies Martin Hepp, 27 mhepp@computer.org
  28. 28. Basic Structure of Offers Object or Agent 1 Promise Happening Compensation Transfer of Rights Agent 2 28
  29. 29. GoodRelations: One Single Schema for A Consolidated View on E-Commerce Data Extraction Arbitrary Query and Reuse Manufacturers Retailers Payment Delivery Product Model Warranty Master Data Shop Spare Parts & Offerings Auctions Consumables Martin Hepp, 29 mhepp@computer.org
  30. 30. On the Shoulders of Giants A Unified View of Data on the Web Martin Hepp, 30 mhepp@computer.org
  31. 31. Minimal Example Martin Hepp, 31 mhepp@computer.org
  32. 32. The Minimal Scenario • Scope – Business entity – Points-of-sale – Opening hours – Payment options • Suitable for – Every business – E-commerce and brick-and-mortar Martin Hepp, 32 mhepp@computer.org
  33. 33. The Simple Scenario • Scope: Minimal scenario plus – Range of products or services – Business functions – Eligible regions or customer types – Delivery options • Suitable for – Any business: E-Commerce and brick-and-mortar – Specific products or services Martin Hepp, 33 mhepp@computer.org
  34. 34. The Comprehensive Scenario • Scope: Simple scenario plus – Individual products or services – Product features – Pricing, rebates, etc. – Availability • Suitable for – Any business: E-commerce and brick-and-mortar – Specific products or services – Structured product database Martin Hepp, 34 mhepp@computer.org
  35. 35. Product Model Data Scenario • Scope – Individual product models – Quantitative and qualitative features • Suitable for – Manufacturers of commodities Martin Hepp, 35 mhepp@computer.org
  36. 36. Part IV: Trends Data Sets & Industry Pick-up
  37. 37. Others Do Care: Pick-up in Industry • Smart Information Systems • ebSemantics • Yahoo! SearchMonkey • Virtuoso Sponger Cartridges for Amazon, eBay, and others expected • Major German mail order companies • etc. Martin Hepp, 37 mhepp@computer.org
  38. 38. Ping The Semantic Web, May 25 Martin Hepp, 38 mhepp@computer.org
  39. 39. Yahoo Enhanced by SearchMonkey Martin Hepp, 39 mhepp@computer.org
  40. 40. Yahoo Enhanced SearchMonkey Martin Hepp, 40 mhepp@computer.org
  41. 41. GoodRelations Page Views Martin Hepp, 41 mhepp@computer.org
  42. 42. Linked Open Commerce Dataspace ...forthcoming Martin Hepp, 42 mhepp@computer.org
  43. 43. Part V: Tools and Resources
  44. 44. GoodRelations User‘s Guide („Primer“) http://www.heppnetz.de/projects/goodrelations/primer/ Martin Hepp, 44 mhepp@computer.org
  45. 45. GoodRelations Annotator http://www.ebusiness-unibw.org/tools/goodrelations-annotator/ Martin Hepp, 45 mhepp@computer.org
  46. 46. GoodRelations Validator http://www.ebusiness-unibw.org/tools/goodrelations-validator/ Martin Hepp, 46 mhepp@computer.org
  47. 47. RDF2dataRSS Tool http://www.ebusiness-unibw.org/tools/rdf2datarss/ Martin Hepp, 47 mhepp@computer.org
  48. 48. osCommerce Extension http://code.google.com/p/goodrelations-for-oscommerce/ Martin Hepp, 48 mhepp@computer.org
  49. 49. Joomla/VirtueMart Extension http://code.google.com/p/goodrelations-for-joomla/ Martin Hepp, 49 mhepp@computer.org
  50. 50. Part VI: Recommendations What any business should do... ...immediately!
  51. 51. Why Should I Bother? • Web Shops: Better visibility in latest generation search engines (e.g. Yahoo) – Same holds for any business that has a Web page, from A as in Amusement Park to Z as in Zoo. • Manufacturers: Allow your retailers to reuse product feature data with minimal overhead at both ends. • Software Developers: Help your customers to use and generate open, linked Web data. It’s easy! Martin Hepp, 51 mhepp@computer.org
  52. 52. What Should I Do? • Web Shops: Create a GoodRelations data dump of your range of offers (rather simple) • Vendors of Web Shop Software: Create GoodRelations import and export interfaces (we can help you with that) • Every Business: Ask your webmaster to create at least a basic description of your range of products or services • Entrepreneurs: Invent new business models based on GoodRelations data Martin Hepp, 52 mhepp@computer.org
  53. 53. Step-by-Step (1) • Data Sources • Data Delivery Options – Form-based data entry – RDFa: Embedding meta- – RDBMS data in XHTML – XML, e.g. BMEcat – RDF/XML: Extra file – CSV – dataRSS: Yahoo feed – Google CSV, RSS 1.0, format RSS 2.0 • Amount of Detail and Data Model – What shall be included? – How shall the type of products be represented? Martin Hepp, 53 mhepp@computer.org
  54. 54. Step-by-Step (2) • Update Mechanism & Data Management – PHP on demand – Script-based data dump • Publishing the Data – Server configuration – Notifying Semantic Web crawlers, Yahoo, … – Semantic Sitemaps • Applications Martin Hepp, 54 mhepp@computer.org
  55. 55. Part VII: The Sky Is the Limit Semantics in Affiliate Models, Serendipity, Matchmaking
  56. 56. Thank you! http://purl.org/goodrelations/ Prof. Dr. Martin Hepp Chair of General Management and E-Business Universitaet der Bundeswehr University Muenchen Werner-Heisenberg-Weg 39 D-85579 Neubiberg, Germany Phone: +49 89 6004-4217 Fax: +49 89 6004-4620 http://www.unibw.de/ebusiness/ http://purl.org/goodrelations/ mhepp@computer.org Martin Hepp, 56 mhepp@computer.org

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