Title
Fiscal Knowledge discovery in Municipalities of Athens and Thessaloniki via Linked Open Data
Abstract
Data Mining and Knowledge discovery in Databases (KDD) is the process that includes data selection, pre-processing, transformation, data mining, evaluation and interpretation of the solutions from the observed results in order to discover useful knowledge from a collection of data. Semantic web and Open Linked Data can provide a higher level quality in Data Mining tasks using additional and linked information from various sources. There are many data models and different approaches that have been proposed in this area combining different aspects of Open Linked Data and Data Mining processes. OpenBudgets.eu meets this concept by modelling Open Budget data from Municipalities of Europe. This paper presents KDD process using the data model of OpenBudgets.eu in order to extract new knowledge from the budget and transaction data of Municipalities of Athens and Thessaloniki. We explored through descriptive statistics the budget phase amounts of the administrative units in Athens and Thessaloniki since 2011 and we observed that both Municipalities tried to reduce their expenditures in these years. The distributions of the expenditure amounts of services and the other descriptive measures and visualizations are provided in order to understand the structure of the expenditures of these Municipalities. Finally using cluster analysis, we built a model that categorizes what expenditure amounts an administrative unit in Athens and Thessaloniki will execute.
Year
DOI
Venue
2016
10.1109/SMAP.2016.7753405
2016 11th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)
Keywords
DocType
ISBN
Linked Open Data,Knowledge Discovery,Data Mining,Budget Data,Fiscal Data
Conference
978-1-5090-5247-9
Citations 
PageRank 
References 
0
0.34
3
Authors
5