A l’occasion de la 11ème conférence internationale sur le Web sémantique (ISWC 2012) qui a eu lieu du 11 au 15 novembre 2012 à Boston (USA), l’Institut informatique de gestion de la HES-SO Valais a présenté FairTrace, une solution permettant la traçabilité de la production de vêtements au moyen d’applications mobiles. Ce projet représente une véritable avancée technologique reconnue au niveau mondial mais également une réussite économique. En effet, en octobre dernier FairTrace est devenue une start-up de l’incubateur The Ark à Sierre!

1. Fairtrace
Tracing the textile industry
Bruno Alves
University of Applied Sciences
Western Switzerland
ISCW2012, Boston
14th Nov. 2012

2. 2
Traceability concerns
• Euro2012 Fan’s Shirts
• Greenpeace Germany
commissioned report
• REACH regulation
No or partial knowledge of
their supply chain

3. 3
Fairtrace

4. 4
Technology
Operative Backend
B2B Frontend
B2C Frontend Operative Frontend

5. 5
Little demo
DEMO
/ˈdɛm.əʊ/

6. 6
Little demo − Formulars

7. 7
Little demo − Datasets
DEMO
/ˈdɛm.əʊ/

8. Understanding the textile 8
process
Question: How do
we define our
models?
• Document search
• Link chaining
• Minimal data set

9. 9
Defining the data model(s)
RDF Schema vs OWL*

10. Implementation − problems & 10
techniques
• Data depth & query complexity
– Gather data at single points
• Link formulars to data model ;
?dataset fpos:hasDatasetUser ?user
Id: fto5
– fpos:hasDatasetForm ?form ;
Data binding and instantiation y ;
x <ftos:hasProcessedFabricOrder>
fpos:hasDatasetScope <.../order001>
x <ftos:hasProcessedFabricColor> z
mechanisms fpos:hasDatasetTimestamp ?timestamp .
-------------------------------
y <ftos:hasOrderColor> z
• Data scopeOrder#buyer_code → fpos:hasOrderBuyerCode
– Order subclassOf Scope,
Dataset

11. 11
Testing
• Tee-shirt
• Consultant in India
• No metrics
• Issues were solved
Positive
feedback

12. 12
Competitive advantage
• No dependency on the schema
– Greater adaptability
• Different product domains
– Change product ontology
• Easy data binding
– Different process / products

13. 13
Lessons learnt
• Inferrences can be confusing
– subClassOf
• Consistent naming conventions
– hasOrderId vs hasId
• Data update and deletion is scary
– is data still there ?

14. 14
Conclusions
• Traceability becomes a trend
• Start-up (CTI-Startup) with a
commercializable product
– Patent pending
– Already one customer
• Linked Data / SPARQL 1.1
• Research

15. 15
Thank you !
Bruno Alves
Senior Scientific Collaborator
Email: bruno.alves@hevs.ch
Phone: +41276069034

16. EXTRA: Choosing the 16
storage technology
Choice: Relational database
or semantic store ?
• Query
• Depth
• Missing information