1. BBY 464 Semantic Information Management (Spring 2016) Semantic Query Languages Yaşar Tonta & Orçun Madran [yasartonta, orcunmadran]@gmail.com Hacettepe University Department of Information Management

2. Semantic Web

3. From Syntactic to Semantic Interoperability

4. Search Engines According to Zadeh Insufficient Works through 2-values logic Can’t make inferences Source: Zadeh, 2005, 2006)

5. Conversion to Question Answering Systems World’s knowledge Relevance (statistical/semantic) – q: How old is Vera? – p: Vera is the same age as Irene – r: Irene is 65 Making inferences from perception-based knowledge – 2-valued logic and probability is not valid The main problem is understanding natural language Source: Zadeh, 2005, 2006)

6. Problems Query formulation – Synonymous words (“garbage theory”) Lack of semantics – “Telekom Inc. Turkey Nebi Fışkın Director” – “Istanbul-based Mobilfon’s Executive Committee appointed Nebi Fışkın as CEO Lack of context – In which context user seeks information – COntext INterchange (COIN) Presentation of search results – Users cannot look at the results beyond the first page. Source: Warren & Davies, 2007, pp. 179-181

7. Examples Google Wolfram Alpha Swoogle

8. From Databases to Data Spaces Database -> structured Data space -> not so structured – Its primary function is to simplify integration of heterogeneous data – e.g., semi-structured data such as XML documents and text files – They will be accessible via the same interface as structured data organized into tables or key/value pairs – Secondary function of a data space is to simplify data integration by providing data mapping and semantic integration facilities for hosted data collections and external data resources such as relational databases or files Source: http://www.streamscape.com/Technology/dataspaces.html

9. Database – Can be queried with SQL (Structured Query Language) Data space – NoSQL (Not only SQL) databases that specialize in semi-structured data

10. Source: http://www.streamscape.com/Technology/dataspaces.html

11. Chapter 6/11 Copyright © 2004 Structured Query Language (SQL) SELECT * FROM PROJECT WHERE Department =’Finance’ AND MaxHours > 100; Example: SELECT Statement

12. Chapter 6/12 Copyright © 2004 Subqueries Subqueries can be extended to include many levels Example SELECT DISTINCT Name FROM EMPLOYEE WHERE EmployeeNumber IN (SELECT EmployeeNum FROM ASSIGNMENT WHERE HoursWorked > 40 AND ProjectID IN (SELECT ProjectID FROM PROJECT WHERE Department = ‘Accounting’));

16. SPARQL SPARQL Protocol and RDF Query Language Semantic query language Retrieves and manipulates data in RDF format Source: https://en.wikipedia.org/wiki/SPARQL

17. Examples Returns names and emails of every person in the FOAF dataset Source: https://en.wikipedia.org/wiki/SPARQL

18. “What are all the country capitals in Africa?” Source: https://en.wikipedia.org/wiki/SPARQL

19. Web 2.0 is a critical precursor of Semantic Web and complements RDF Semantic Web will be triggered by Web apps (blogs, wikis, social networks, photo sharing services, and so on) that require open data and atomic data containment (Data Spaces) Transition from “programmable web” to “programmable and query-able web of databases” Representing non-RDF data as RDF data by way of Ontology mapping

20. How? 1. By storing app triples in an RDF Triple Store 2. By converting SPARQL queries to SQL and reformatting results back into RDF from.

21. RDF Triple Store Implementation Data types Data dictionary (System tables and indexes) Virtuoso SQL and SPARQL Fusion Join Operation Algorithms Data import and index compaction

22. RDF Data Management Xquery Xpath XSLT XMLS