MOLDEAS at City College


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A summary about MOLDEAS for non-expert users.

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MOLDEAS at City College

  2. 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 DailySource: 22/02/2013 Thessaloniki, Greece 2
  3. 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…22/02/2013 Thessaloniki, Greece 3
  4. 4. I have amily22/02/2013 Thessaloniki, Greece 4
  5. 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 ofWe will deliver to you a contract… daily report… And other variables: value, …the region… duration, etc. 22/02/2013 Thessaloniki, Greece 5
  6. 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 amily22/02/2013 Thessaloniki, Greece 6
  7. 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!22/02/2013 Thessaloniki, Greece 7
  8. 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 € … …22/02/2013 Thessaloniki, Greece 8
  9. 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.22/02/2013 Thessaloniki, Greece 9
  10. 10. Could you understand this notice? 22/02/2013 Thessaloniki, Greece 10
  11. 11. …and this one? 22/02/2013 Thessaloniki, Greece 11
  12. 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 separator22/02/2013 Thessaloniki, Greece 12
  13. 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 Union22/02/2013 Thessaloniki, Greece 13
  14. 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 notices22/02/2013 Thessaloniki, Greece 14
  15. 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…22/02/2013 Thessaloniki, Greece 15
  16. 16. Open Data Semantic Web Linked Data22/02/2013 Thessaloniki, Greece 16
  17. 17. 8 principles-Open Data1. 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.22/02/2013 Thessaloniki, Greece 17
  18. 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.22/02/2013 Thessaloniki, Greece 18
  19. 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. 20. RDF triples foaf:name #me “Jose” jose-foaf: diego:foaf: 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” 22/02/2013 Thessaloniki, Greece 20
  21. 21. “Can we represent the information of our user using RDF?”22/02/2013 Thessaloniki, Greece 21
  22. 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. 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. 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”@ene: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. 25. “It seems better but…” “Can we also represent the data in public procurement notices?” “Yes, of course, we can follow the same approach!”22/02/2013 Thessaloniki, Greece 25
  26. 26. “Firstly we are going to introduce the concept of Linked Data…”22/02/2013 Thessaloniki, Greece 26
  27. 27. Linked Data Principles 5* Model1. Use URIs to name things2. When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL).3. Include links to other URIs.4. Use HTTP URIs. (Tim Berners-Lee and “The bag of crisps”) 22/02/2013 Thessaloniki, Greece 27
  28. 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!”22/02/2013 Thessaloniki, Greece 28
  29. 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
  30. 30. “Let’s link our data to existing datasets…” CPV 2008 (URI:{id}) Example: NUTS (URI:{id}) Example: are going to use prefixes to ease the reading of URIs… 22/02/2013 Thessaloniki, Greece 30
  31. 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 22/02/2013 Thessaloniki, Greece 31
  32. 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”22/02/2013 Thessaloniki, Greece 32
  33. 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”@el22/02/2013 Thessaloniki, Greece 33
  34. 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”22/02/2013 Thessaloniki, Greece 34
  35. 35. “Yes, there are common similarities…” Table Graph E/R model RDF/OWL semantics SQL SPARQL And…this is the Web of Data!22/02/2013 Thessaloniki, Greece 35
  36. 36. SPARQL endpoints … DBPedia UK Gov NATURE Webindex MOLDEAS GEOLD ACM AEMET PubMED And more… +300 DBLP Thessaloniki, Greece 36
  37. 37. Some Use Cases… p_index.xml bc_on_publishing_an.html /item/renaulttoys/pedalcar/eco2pedalcar/defa ult.aspx … 22/02/2013 Thessaloniki, Greece 37
  38. 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”22/02/2013 Thessaloniki, Greece 38
  39. 39. SPARQL query …PREFIX dbo: <>PREFIX dc-terms: <>SELECT ?name ?birthdate ?comment WHERE { ?person dbo:birthPlace :Thessaloniki. ?person dc-terms:subject<> . ?person dc-terms:subject<> . ?person foaf:name ?name . s-subject ?person rdfs:comment ?comment . p-predicate ?person dbpedia2:birthDate ?birthdate . o-object FILTER (lang(?comment)=en). l-literal}22/02/2013 Thessaloniki, Greece 39
  40. 40. Results… Thessaloniki, Greece 40
  41. 41. Methods On Linked Data for E-procurement Applying Semantics22/02/2013 Thessaloniki, Greece 41
  42. 42. Overview TED 1 Produce 3 Consume … XML RDFizing Semantic Services (e.g. Searching, Methods Matchmaking & BOE Prediction)BOPAOrganizations Linked Data 2 Api Pubby+Snorql CPV RDFizing PublishNUTSEurovoc 4 Validate22/02/2013 Thessaloniki, Greece 42
  43. 43. The ongoing example… 22/02/2013 Thessaloniki, Greece 43
  44. 44. Partial view in RDF22/02/2013 Thessaloniki, Greece 44
  45. 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 engine22/02/2013 Thessaloniki, Greece 45
  46. 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).22/02/2013 Thessaloniki, Greece 46
  47. 47. Results (it is now being updated)22/02/2013 Thessaloniki, Greece 47
  48. 48. Publishing Linked Data22/02/2013 Thessaloniki, Greece 48
  49. 49. Example of a simple SPARQL querySELECT DISTINCT * WHERE{ ?ppn rdf:type ppn-def:ppn. ?ppn ppn-def:nutsCode ?nutsCode. FILTER(?nutsCode = <> OR ?nutsCode = <>) . ?ppn cpv-def:codeIn2008 ?cpvCode. FILTER(?cpvCode = cpv:33192100 OR ?cpvCode = cpv:39143116 OR ?cpvCode = cpv:39143310) . ?ppn dc:date ?date .} (see Demo queries)*This is the old version of MOLDEAS. New procurement notices, etc. are coming soon… 22/02/2013 Thessaloniki, Greece #49
  50. 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 opportunities22/02/2013 Thessaloniki, Greece 50
  51. 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 notices22/02/2013 Thessaloniki, Greece 51
  52. 52. Questions Thank you for your attention!
  53. 53. Credits• – – –• –• – –• –