1. FORTH-ICS, email: fgeo@ics.forth.gr With some help from: Irini Fundulaki, Vassilis Papakonstantinou Linked Open Data Giorgos Flouris 20/03/14

2. What Is Linked Open Data OR: What is wrong with the current Web … and why bother

3. Weather Data

4. Euribor Rates

5. Hellenic Police (Crimes) http://greek-lod.math.auth.gr/police/

6. The Evolution of the Web Web of DocumentsWeb of Data HTML (markup language) RDF (semantical language) SPARQL (SQL-like query language) Search engine (keywords) UI Human-readable results Machine-processable results

7. The Vision of Linked Open Data Turn the web into a global database As opposed to a global file system (web of documents) Linked: One global database, rather than several isolated ones Open: The idea that certain data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control (http://en.wikipedia.org/wiki/Open_data) Data: Designed for machines, not for direct consumption by humans

8. Using Data from Hellenic Police  Which area of Greece had the most house break-ins in 2012?  Which area of Greece had the most house break-ins per capita in 2012?

9. From Documents to Linked Open Data

10. Linked Open(?) Data  “Open” means “available on the web”  Open is not necessarily free in the full sense — Various types of licenses (attribution, non-commercial, no-derivatives, share- alike, CC0, open government license, …) — Different licenses for the database and for the content — http://discovery.ac.uk/files/pdf/Licensing_Open_Data_A_Practical_Guide.pdf  OpenStreetMap — Share-alike  IATA TIMATIC (visa, passport and health information for travelers) — Companies must buy access, but their customers have free access  Roadblocks to “openness”  Part of the data may be related to IPR  Privacy and data protection rights (for living persons)  …

11. Evolution of the Linked Open Data Cloud  Linked Open Data Cloud (May 2007)

12. Evolution of the Linked Open Data Cloud  Linked Open Data Cloud (September 2008)

13. Evolution of the Linked Open Data Cloud  Linked Open Data Cloud (March 2009)

14.  Linked Open Data Cloud (September 2011) Evolution of the Linked Open Data Cloud Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/

15. Evolution of the Linked Open Data Cloud  Linked Open Data Cloud in numbers (September 2011)

16. Why to Publish Linked Open Data OR: Why let others benefit from your data... … and gain some profit yourself as well in the process

17. For Government Data (1/3)  http://www.mckinsey.com/insights/business_technology/open_d ata_unlocking_innovation_and_performance_with_liquid_inform ation

18. For Government Data (2/3)  http://www.epsiplatform.eu/content/finnish-study-psi-pricing- geo-data  “Firms functioning in the countries in which public sector agencies provide fundamental geographical information either freely or at maximum marginal costs have grown, on average, about 15 percent more per annum than the firms in the countries in which public sector GI is priced according to the cost-recovery principle.”  http://www.epsiplatform.eu/content/value-danish-address-data  “The conclusion of this study is that the direct financial benefits from the agreement for society during the period 2005 – 2009 amount to around EUR 62 million (~ DKK 471 million). Until 2009 the total costs of the agreement has been around EUR 2 million. In 2010 it is estimated that the social benefits from the agreement will be about EUR 14 million, while costs will total about 0.2 million. About 30% of benefits will be in the public sector and around 70% in the private sector.”

19. For Government Data (3/3)  http://okfn.org/opendata/  UK released information on 300.000 bus stops; community (OpenStreetMaps) corrected 18.000 of them, improving accuracy  http://eaves.ca/2010/04/14/case-study-open-data-and-the-public- purse/  Fraud revealed: Canada saved $3,2billion  For tourism:  Promote the “assets” of cities for visitors (points of interest etc)  Personalized services can be built on top of such data — Trip customization given information such as maps, weather, proximity between points of interest, accommodation, restaurants, special interests, …  Analysis of touristic data (for strategic, political decision making) — TourMIS (http://www.tourmis.info/index_e.html)

20. For Enterprise Data  Benefits  Free promotion of business  Improvement of services  Improve visibility  Ability to establish collaborations between different businesses  Others can use the data  Improve them  Exploit them  In ways that could not be imagined beforehand

21. Publishing Non-Confidential Data

22. Conclusion  Linked Open Data are already a reality  Even though still not fully developed  Various problems exist — Quality — Size — Licenses — Multi-linguality — …  Provide lots of potential  For governments  For companies  But also for scientists, aware citizens, … practically for everyone

23. Ευχαριστώ

24. BACKUP SLIDES

25. et.diavgeia.gov.gr

26. Applications Using Maps (OpenStreetMap)

27. Application for Buses

28. Data Providers

29. Generic Applications

30. Naïve Application Example

31. Outline 1. What is linked open data a. What is data? b. What is open? c. What is linked? 2. How to use linked open data a. Examples 3. Why to publish your data as linked open data a. For government data b. For enterprise data 4. How to publish your data as linked open data a. Main technologies b. Tools, software

32. How to Publish Linked Open Data OR: How to make your data a part of the global database

33. The Basics  URIs act as identifiers for “resources”  People, places, objects, ideas, …  RDF triples connect resources  (s p o) means “s is connected to o with p” — Same as (subject verb object) in natural language sentences  (El_Greco was_born_in Crete)  (El_Greco has_name “Δομήνικος Θεοτοκόπουλος”)  Link URIs across datasets

34. Datasets  Basic structures  Classes (or concepts): collections of objects (e.g., Actor, Politician)  Properties (or roles): binary relationships between objects (e.g., started_on, member_of)  Instances (or individuals): objects (e.g., Giorgos, B. Obama)  Relations between them  Subsumption (Parliament_Member subclass_of Politician), instantiation (B. Obama instance_of Politician), …  The allowed relations and their semantics depend on the language  Different representation languages  RDF/S, DLs, OWL  Allow the definition of formal semantics and reasoning  Different expressive power, complexity

35. Relational to RDF RDF SPARQL D2R/D2RQ R2RML Virtuoso RDF Views Relational SQL Company D2R/D2RQ Triplify Materialize Virtual (View)