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  4. Cross-Administration Comparative Analysis of Open Fiscal Data
 
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2020
Conference Paper
Title

Cross-Administration Comparative Analysis of Open Fiscal Data

Abstract
To improve governance accountability, public administrations are increasingly publishing their open data, which includes budget and spending data. Analyzing these datasets requires both domain and technical expertise. In civil communities, these technical and domain expertise are often not available. Hence, despite the increasing size of the open fiscal datasets being published, the level of analytics done on top of these datasets is still limited. There is a plethora of tools and ontologies for open fiscal data e.g., transformation, linking, multilingual integration, and classification. These existing technologies enable the development of a pipeline that could be used for comparative analysis of open fiscal data. In this paper, we demonstrate the comparative analysis over linked open fiscal data. Open fiscal data are cleaned, analyzed, transformed (i.e., semantically lifted), and have their related concept labels connected across different public administrations so budget/spending items from related concepts can be queried. Additionally, the information on linked open data (e.g., DBpedia) has been used to provide additional context for the analysis. We provide a proof-of-concept and demonstrate that such a cross-comparison is possible using the existing tools.
Author(s)
Musyaffa, Fathoni A.
Lehmann, Jens  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Jabeen, Hajira
Mainwork
13th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2020. Proceedings  
Project(s)
LAMBDA  
Funder
European Commission EC  
Conference
International Conference on Theory and Practice of Electronic Governance (ICEGOV) 2020  
DOI
10.1145/3428502.3428573
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Keyword(s)
  • Semantic Web

  • budget and spending

  • knowledge graph

  • linked open data

  • comparative analysis

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