A summary about MOLDEAS for non-expert users.

1. TOWARDS A PAN-EUROPEAN
E-PROCUREMENT PLATFORM TO AGGREGATE,
PUBLISH AND SEARCH PUBLIC
PROCUREMENT NOTICES POWERED BY
LINKED OPEN DATA:
THE MOLDEAS APPROACH
Dr. Jose María Alvarez Rodríguez
Research Fellow, SEERC
Thessaloniki, 22-02-2012

2. Background and Glossary
 e-Procurement • CPV
• A public procurements initiated, negotiated and/or – Common Procurement Vocabulary
concluded using electronic means, i.e. using electronic • LOD
equipment for the processing and storage of data, in
– Linking Open Data or Linked Open Data
particular through the Internet.
• NUTS
 Public procurement
– Nomenclature of Territorial Units for
• A procedure initiated by a contracting authority with a
Statistic
view of acquiring goods, services or public works for
the fulfillment of its tasks. • OWL
 Public Procurement Notice, notice, public contract, etc. – Ontology Web Language
• Being strict are not the same. • PSI
• There are distinct definitions depending on the stage: – Public Sector Information
PriorNotice, AwardNotice, etc. • RDF
• For the sake of a better understanding we will use – Resource Description Framework
these terms to refer the same thing “an • SME
announcement” of a new public procurement process – Small and Medium-sized Enterprise
(first stage and notice).
• TED
– Tenders Electronic Daily
Source: http://ec.europa.eu/internal_market/consultations/docs/2010/e-procurement/siemens-study_en.pdf
22/02/2013 Thessaloniki, Greece 2

3. The problem…
I have a family business that
produces beds and other
bedroom furniture…
but I do not have clients
Let’s search… due to the crisis…
I think we could sell our
and we could also try to sell
products in other countries…
beds to public administrations…
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4. I have
amily
22/02/2013 Thessaloniki, Greece 4

5. Some help…an expert in e-Procurement
We are a Spanish SME that sells
an alert service about public
procurement opportunities…
We need the type of
We will deliver to you a
contract…
daily report…
And other variables: value, …the region…
duration, etc.
22/02/2013 Thessaloniki, Greece 5

6. The interview…
“I can provide different types of “beds” and bedroom furniture”
“Ok! Let’s see some CPV codes…”
• 33192100-3 - Beds for medical use
• 39143116-2 – Cots
• 39143310-2 - Coffee tables
• …
I have amily
“Do you have any target region?”
“Well, Thessaloniki, Greece…but maybe other countries”
“Ok! Let’s see some NUTS codes…”
• GR-Greece
• GR1: Voreia Ellada
• GR12 Kentriki Makedonia
• GR122 Thessaloniki Prefecture, etc.
I have amily
22/02/2013 Thessaloniki, Greece 6

7. …
Is it a familiar business? Isn’t it?
“yes, we are 10 people…”
“Great!...a SME…
“Do you have any thinking about
the duration of the contract or
the value?
“I suppose we could assume
contracts about 60000€ of
one year duration…”
“Ok! I am going to collect all these features
and I will report you the new opportunities…”
“Great! I hope to get some
business opportunity…”
“For sure! Don’t hesitate about it!
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8. Let’s start…
• We need public procurement opportunities that
fulfill these requirements:
Feature Value
Type of “object” (CPV Codes): 33192100-3, 39143116-2,
39143310-2
Location (NUTS Codes) GR, GR1, GR12, GR122 and
other European countries
Type of company SME
Duration 1 year
Value 60,000 €
… …
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9. Building the alert…
• We have to retrieve information from different
– Data sources or providers
• Official Bulletins, Official web pages, Newspaper, etc.
– Formats
• PNG, JPEG, PDF, MSOffice, OpenOffice, CSV, RSS, etc.
– Languages
• 23 official languages in Europe
– Models, services and APIs
• XML-Schema, SQL, REST, WSDL/SOAP, etc.
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10. Could you understand this notice?
22/02/2013
http://bit.ly/Yw0Rpm Thessaloniki, Greece 10

11. …and this one?
22/02/2013
http://bit.ly/WTIRYA Thessaloniki, Greece 11

12. Yes, you can speak/read/write Spanish…
…and the location, where is “Asturias”?
…and the format?
you have software to read PDFs, PNGs, etc. files
…and what is the meaning of “2012”?
“2012” it is clearly a year
…and what is the meaning of “3.371.282,99 €”?
It is clearly a value (~three million of Euros) using “.” as decimal separator
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13. Yes, but…we seek for an alert service…
• The information and data should be…
– Automatically processed
• Machine-processable format
– Validated against a common data model
– Available for querying via a formal language such as SQL
– Usable to build added-value services
– …
• Someone could say: ”Ok! But I can search by myself
in the web and manually check the features”
– Yes, why not? You can perfectly check an average of 16K
notices per day in the European Union
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14. and Why?
• e-Procurement is a strategic sector
– 17% of the GDP
• Action Plans 2004 and 2020
• Projects
– E-Certis, Fiscalis 2013, E-Prior, PEPPOL, STORK, etc.
• Other actions
– TED, RAMON metadata server, CPV, NUTS, etc.
• Legal framework (to be transposed in each European country)
• Boost participation (specially SMEs)
– First action could be to alert about new public procurement notices
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15. …But
• …a tangled realm of data and information…
– Formats, models, APIs, providers, classifications,
locations, etc.
It is not easy to reuse this valuable
public sector information (PSI)
We should make this information/data
available to be machine-processable…
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16. Open Data
Semantic Web
Linked Data
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17. 8 principles-Open Data
1. Data Must Be Complete.
2. . . . Primary.
3. . . . Timely.
4. . . . Accessible.
5. . . . Machine processable.
6. Access Must Be Non-Discriminatory.
7. Data Formats Must Be Non-Proprietary.
8. Data Must Be License-free.
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18. Public Procurement Data
is a clear example of Open Data
…and due to its relevance for the
economic sector we should ensure
all the principles of this initiative.
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19. Semantic web
 Common & shared data model
 Graph (subject, object, predicate) foaf:name
 RDF with different serialization #me “Jose”
formats
 Implicit multilinguism support
 Knowledge-representation foaf:family:name
 Ontologies
 OWL (Ontology Web Language)
 Logic formalism: DL, F-Logic, etc.
 Reasoning foaf:knows “Alvarez”
 Knowledge-management
 Expert systems
 Standards foaf:name
 Query languages #diego “Diego”
 Vocabularies
 Datasets
 …
22/02/2013 Thessaloniki, Greece 19

20. RDF triples
foaf:name
#me “Jose” jose-foaf: http://www.josemalvarez.es/foaf.rdf#.
diego:foaf: http://berrueta.net/foaf.rdf#.
foaf:family:name
jose-foaf:me foaf:name “Jose”.
jose-foaf:me foaf:family_name “Alvarez”.
foaf:knows
“Alvarez”
jose-foaf:me foaf:knows diego-foaf:me.
foaf:name diego-foaf:me foaf:name “Diego”.
#diego “Diego”
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21. “Can we represent the
information of our user using
RDF?”
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22. “Beds and
User e:topic
bedroom
furniture”
RDF Graph
e:located-in
#u1 “Greece, Thessaloniki,
others, etc.”
e:value
… “60000 euros”
“33192100-3,
39143116-2,
39143310-2” e:topic
e:located-in
“GR, GR1, GR12,
GR122, …”
#e1
Expert
e:value RDF Graph
“60000 euros” …
22/02/2013 Thessaloniki, Greece 22

23. “There is not so much gain,
it is just another way to represent
information…”
“Yes, but it is machine-processable
(properties have semantics)
and we can do better!”
• Re-using well-know vocabularies, properties, etc.
• Making use of data properties
• Labeling all resources
• …
22/02/2013 Thessaloniki, Greece 23

24. RDF Graph 33192100-3
rdfs:label
“Beds for medical use”@en
…
rdfs:label
33192100-3 “Cots”@en
foaf:topic
#e1
rdfs:label
33192100-3 “Coffee tables”@en
e:value
e:located-in rdfs:label
#v1 GR “Greece”@en
e:quantity e:currency rdfs:label
GR1
“Voreia Ellada”@en
“60000” #c1
^^xsd:double GR12 rdfs:label
e:symbol rdfs:label “Kentriki
Makedonia”@en
“€” “Euro” GR122 …
24

25. “It seems better but…”
“Can we also represent the data
in public procurement notices?”
“Yes, of course, we can follow
the same approach!”
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26. “Firstly we are going to
introduce the concept of
Linked Data…”
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27. Linked Data
Principles 5* Model
1. Use URIs to name things
2. When someone looks up a
URI, provide useful
information, using the
standards (RDF*, SPARQL).
3. Include links to other
URIs.
4. Use HTTP URIs.
http://www.youtube.com/watch?v=ga1aSJXCFe0 (Tim Berners-Lee and “The bag of crisps”)
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28. “These principles can be achieved by
applying RDF to represent data and
we can reach 5*!”
“Yes, but you should make links to existing
datasets”
“Where Can I find them?”
“In the LOD Cloud there are some RDF
datasets and they are also open!”
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29. Linked Open Data
Cloud
 203 datasets ( 25 Billions of rdf triples) and
 395 millions of links (Sept. 2010).
 Domains: Media, Geographic, Government (42,09 %),
 Publications, Cross-domain, Life sciences, etc. (Ago. 2011).
 393 datasets (Jun. 2012).
22/02/2013 Thessaloniki, Greece 29
http://richard.cyganiak.de/2007/10/lod/

30. “Let’s link our data to existing
datasets…”
CPV 2008
(URI: http://purl.org/weso/pscs/cpv/2008/resource/{id})
Example: http://purl.org/weso/pscs/cpv/2008/resource/33192100
NUTS
(URI: http://nuts.psi.enakting.org/id/{id})
Example: http://nuts.psi.enakting.org/id/GR
We are going to use prefixes to ease the reading of URIs…
22/02/2013 Thessaloniki, Greece 30

31. RDF Graph External Datasets “Ιατρικές κλίνες”@el
rdfs:label
…
cpv-2008:
“Beds for medical use”@en
33192100
foaf:topic dc:identifier
skos:broader
“33192100”
dc:subject
cpv-2008:
#e1 33192000
“33192100-3”
rdfs:label “ΕΛΛΑΔΑ”@el
e:located-in
nuts: nuts:
GR GR1
contains
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32. “Great! We can reuse the information and
data…but…
Can we enrich that data?”
“Yes, you can create a “proxy” resource
with new data and link to the existing one”
“For instance, we are going to add lat/long
to the NUTS code GR”
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33. RDF Graph
… “39.074208” “21.824312”
External Dataset
wgs84_pos:lat wgs84_pos:long
e:located-in e:has-nuts-code contains
nuts: nuts:
#e1 GR
GR GR1
rdfs:label
“ΕΛΛΑΔΑ”@el
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34. “We can easily extend the RDF model to
represent information keeping the
semantics”
“Yes, exactly.”
“Wait, wait, wait…we have a data model,
an implicit semantics and a query
language…so this is like a traditional
database”
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35. “Yes, there are common similarities…”
Table Graph
E/R model RDF/OWL semantics
SQL SPARQL
And…this is the
Web of Data!
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36. SPARQL endpoints …
DBPedia UK Gov
NATURE Webindex
MOLDEAS
GEOLD
ACM AEMET
PubMED
And more… +300 DBLP http://labs.mondeca.com/sparqlEndpointsStatus/
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37. Some Use Cases…
http://www.data.gov/
http://data.worldbank.org/
http://www.bestbuy.com/sitemap_
http://geodata.gov.gr/geodata/index.php p_index.xml
http://www.w3.org/QA/2012/05/interview_b
bc_on_publishing_an.html
http://eurostat.linked-statistics.org/
http://open-data.europa.eu/open-data/linked-data
http://www.bioontology.org/ http://www.renault.co.uk/ownerservices/shop
/item/renaulttoys/pedalcar/eco2pedalcar/defa
ult.aspx
http://data.gov.uk/
http://data.webfoundation.org/
http://data.nature.com/
http://aims.fao.org/standards/agrovoc/linked-open-data
http://datos.gob.es/datos/
… http://datos.bcn.cl/es
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38. “Can I execute SPARQL queries?”
“Yes, you could ask….”
“Give me gymnasts, born in Thessaloniki
that have won an Olympic gold medal,
including their name, date of birth and
some comment about them”
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39. SPARQL query …
PREFIX dbo: <http://dbpedia.org/ontology/>
PREFIX dc-terms: <http://purl.org/dc/terms/>
SELECT ?name ?birthdate ?comment WHERE {
?person dbo:birthPlace :Thessaloniki.
?person dc-terms:subject
<http://dbpedia.org/resource/Category:Olympic_gymnas
ts_of_Greece> .
?person dc-terms:subject
<http://dbpedia.org/resource/Category:Olympic_gold_m
edalists_for_Greece> .
?person foaf:name ?name .
s-subject
?person rdfs:comment ?comment . p-predicate
?person dbpedia2:birthDate ?birthdate . o-object
FILTER (lang(?comment)='en'). l-literal
}
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40. Results…
http://bit.ly/Xz3asA
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41. Methods On
Linked Data
for
E-procurement
Applying
Semantics
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42. Overview
TED 1 Produce
3 Consume
…
XML RDFizing Semantic
Services
(e.g. Searching,
Methods Matchmaking &
BOE Prediction)
BOPA
Organizations
Linked Data
2 Api
Pubby+Snorql
CPV RDFizing Publish
NUTS
Eurovoc
4 Validate
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43. The ongoing
example…
22/02/2013
http://bit.ly/WTIRYA Thessaloniki, Greece 43

44. Partial view in
RDF
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45. What we did…
 Define the processes to produce, publish, consume and validate the Linked Data
generated from public procurement notices
 Design an ontology for representing domain knowledge
 Entities and relationships
 ..
 Apply the aforementioned points to public procurement data:
 1M of Public Procurement Notices
 9 Product Scheme Classifications (PSCs) from UN, EU, etc.
 50K companies/people
 +200 Countries
 Validate the generated Linked Data and make a comparison with existing
approaches
 A survey of 196 criteria
 Consume and exploit the generated Linked Data creating a matchmaking service
using different methods
 Syntactic search, concept query expansion and a recommending engine
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46. If we talk the same language (RDF)
we can easily fulfill the requirements of our
“bed manufacturer”.
We would report the possibility of tendering in
“Asturias” (ES12)
to provide
“Beds” (CPV-33192100)
and other furniture
(CPV-39143116 & CPV-39143310-2).
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47. Results
http://purl.org/weso/moldeas/ (it is now being updated)
22/02/2013 Thessaloniki, Greece 47

48. Publishing Linked Data
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49. Example of
a simple SPARQL query
SELECT DISTINCT * WHERE{
?ppn rdf:type ppn-def:ppn.
?ppn ppn-def:nutsCode ?nutsCode.
FILTER(?nutsCode = <http://nuts.psi.enakting.org/id/ES12> OR
?nutsCode = <http://nuts.psi.enakting.org/id/GR>) .
?ppn cpv-def:codeIn2008 ?cpvCode.
FILTER(?cpvCode = cpv:33192100 OR
?cpvCode = cpv:39143116 OR
?cpvCode = cpv:39143310) .
?ppn dc:date ?date .
}
http://purl.org/weso/moldeas/
http://bit.ly/XQ0uUV
(see Demo queries)
*This is the old version of MOLDEAS. New procurement notices, etc. are coming soon…
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50. What we got…
 New way for representing the valuable information of public
procurement notices applying semantic technologies
 New datasets that are now part of the LOD Cloud
 Dissemination and networking
 Expertise, know-how generation and new research lines
 …maybe
A step forward to a new way of publishing public data, more
specifically procurement data
 Enabling cross-border business opportunities
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51. Main Conclusion
 We can represent information and
data in public procurement notices
using semantic technologies
(vocabularies, datasets, etc.)
 Overcoming most of the problems
in public procurement notices
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52. Questions
Thank you for
your attention!

53. Credits
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