Presentation on theme: "Filip Zavoral, Jiří Dokulil SemWex - KSI MFF UK Semantic Web infrastructure Trisolda current state and perspectives."— Presentation transcript:
Filip Zavoral, Jiří Dokulil SemWex - KSI MFF UK http://www.ksi.mff.cuni.cz/semwex/ Semantic Web infrastructure Trisolda current state and perspectives 10. Mixer 26.11.2008
Semantic web vs. semantization Semantic web vision Tim Berners-Lee “The Semantic Web,” Scientific Am. 2001 semantic research generously funded 'hardly one has ever seen...' New buzzwords Web 2.0, Web 3.0, Social web, Web of data, Meshups, … Semantic web died? no, not yet born Web Semantization
Semantic technologies TCP/IP HTTP HTML Browser Security
Trisolda Motto 'hardly one has ever seen...' the semantic web data from real life incomplete, duplicated, inaccurate, >20 millions triples Jena very slow load, over >1 million of triples → crash Sesame unable to load more then 200 000 triples exponential complexity for loading where is a working platform for semantic web research? Technology background Repository – data integration DataPile
Repository Trisolda Repository Stores incoming data Retrieves results for queries Stores used ontology DataPile structure holds data in any format Applications server Not all data and knowledge available when imported the knowledge is not accurate Background worker inferencing data unifications reasoner Framework for plug-ins
Import Direct import data in data sources converters to the used ontology Crawling wild Web Egothor web crawler AgentMat parsed pages stored deductors deduce data and ontology real life data incomplete, duplicated, inaccurate Import modes batch insert immediate insert
Querying Query API Based on simple graph matching query: set of RDF triples with var. result: multiset of possible variable mapping – a relation Not another SQL-like language set of C++ classes and operators Query evaluation levels of support by q engines Query environments present outputs examples: rep. browser, RDF visualizer, semantic executors service composition - conductors
Future work Conclusions working infrastructure currently not working - re-deployment, AgentMat & TriQ integration gathering, storing and querying of semantic data platform for research and experiments Future work & long-term goals specialized semantic data storage semantic acquisition, data semantization interface-based loosely coupled network of Semantic Web repositories semantic computing, services, composition, executors...
Selected Publications Beňo, Míšek, Zavoral: AgentMat: Framework for Data Scraping and Semantization, 3rd International Conference on Research Challenges in Information Science, IEEE, 2009 Dokulil, Yaghob, Zavoral: Trisolda: The Environment for Semantic Data Processing, International Journal On Advances in Software, IARIA, 2009 Podzimek, Dokulil, Yaghob, Zavoral: Mám hlad: pomůže mi Sémantický web?, Informačné technológie - Aplikácia a Teória, ITAT 2008 Dokulil, Tykal, Yaghob, Zavoral: Semantic Web Repository And Interfaces, International Conference on Advances in Semantic Processing, SEMAPRO 2007, IEEE Computer Society Press - Best Paper Award Dokulil, Tykal, Yaghob, Zavoral: Semantic Web Infrastructure, IEEE International Conference on Semantic Computing ICSC, IEEE Computer Society Press 2007 Yaghob, Zavoral: Semantic Web Infrastructure using DataPile, Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Itelligent Agent Technology, Hong Kong, IEEE Computer Society Press 2006
SPARQL semantics lot of changes – now stable based on algebra works with sets of variable mappings – i.e. tables very different from SQL “closed” no compositionality
SPARQL RDF is a graph SPARQL provides pattern (subgraph) matching – no other graph handling SPARQL handles only fixed-size graphs RDFS supports arbitrary hierarchy of classes SPARQL has no aggregate functions, no “group by” no constructors
Idea… ? make the language SQL-like inside not just outside joins, selection, projection, grouping, aggregation relational algebra works with relation, i.e. sets of triples, the database is made of relations RDF data is made of… RDF graphs maybe we should work with RDF graphs
Tables – Graphs JohnSmith JohnDoe JaneDoe BillJackson John Smith John Doe Jane Doe Bill Jackson
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