RDF Public Budget Data and Application

• Thesis title in Czech: RDF Public Budget Data and Application
• Thesis title in English: RDF Public Budget Data and Application
• Key words: RDF, public budgets, linked data
• English key words: RDF, public budgets, linked data
• Academic year of topic announcement: 2011/2012
• Thesis type: Bachelor's thesis
• Thesis language: angličtina
• Department: Department of Software Engineering (32-KSI)
• Supervisor: doc. Mgr. Martin Nečaský, Ph.D.
• Author: hidden - assigned and confirmed by the Study Dept.
• Date of registration: 03.11.2011
• Date of assignment: 03.11.2011
• Confirmed by Study dept. on: 06.12.2011

Guidelines

Linked Data [1,2] is a set of principles, which will in the future lead to a new generation of the Web. The new generation will be a current Web of Documents of data enriched with so called Web of Data. The basic Linked Data principle is publishing data packages on the Web with unique identifiers in a form of URI. The packages will be linked on each other, which will form the mentioned Web of Data.

The aim of this thesis is to (1) design an ontology for public budgets and create its reference and user documentation, (2) transform data about public budgets of Czech administrations acquired from UFIS [3] in XML format to RDF format with respect to the designed ontology and (3) store the data into an RDF database. On top of the RDF databse the author will build an experimental application which visualizes the budget data in a user friendly way. He will also maintain a parallel relational database with the budged data and will allow a user to switch between the RDF and relational database to compare database performance. Finally, the author will use the SILK tool [4,5] to link the Czech budget data to the linked data cloud.

References

[1] Christian Bizer, Tom Heath, Tim Berners-Lee: Linked Data - The Story So Far. Int. J. Semantic Web Inf. Syst. 5(3): 1-22 (2009) [http://tomheath.com/papers/bizer-heath-berners-lee-ijswis-linked-data.pdf]
[2] http://linkeddata.org/
[3] wwwinfo.mfcr.cz/ufis/
[4] Rober Isele, Anja Jentzch, Chris Bizer, Julius Volz. Silk - A Link Discovery Framework for the Web of Data. [http://www4.wiwiss.fu-berlin.de/bizer/silk/]
[5] Axel-Cyrille Ngonga Ngomo, Jens Lehmann, Sören Auer and Konraf Höffner: RAVEN – Active Learning of Link Specifications. ISWC'11 Workshop on Ontology Matching (OM-2011)