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Proposal for Application of Data Science Methods in E-Government

A Case-Study About the Application of Available Techniques for Performance Measurement with the Help of Data Science

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Electronic Government and the Information Systems Perspective (EGOVIS 2017)

Abstract

The business processes and workflows of Public Administration within the Hungarian Government are transformed profoundly in the past years. As more and more tasks of public administration are carried out by the assistance of electronic solutions, the tracking and monitoring of activities became possible whereby data in electronic form are available for data processing. In enterprises, the performance measurement, strategic enterprise management and similar approaches turn out to be fashionable; moreover, the techniques and methods out of data science provides the opportunities for data analytics on the collected data. As the e-public administration develops and significant amount of data will be accessible for data processing it will give the chance to apply data science for the wide spectrum of activities within public administration. There is project that is planned and dedicated to the before-mentioned task. Firstly, a data warehouse will be built that will collect and load the data from disparate sources in a data schemes within the data warehouse that will suit data analytics. We will analyze the E-government architecture, public administration processes and the available techniques of data science that will provide useful services for the senior public officers.

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Acknowledgement

This paper has been written with the support of the National University of Public Service in the framework of the priority project KÖFOP-2.1.2-VEKOP-15-2016-00001 titled “Public Service Development for Establishing Good Governance” - Ludovika Digital Governance Research Group.

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Correspondence to Bálint Molnár .

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Molnár, B. (2017). Proposal for Application of Data Science Methods in E-Government. In: Kő, A., Francesconi, E. (eds) Electronic Government and the Information Systems Perspective. EGOVIS 2017. Lecture Notes in Computer Science(), vol 10441. Springer, Cham. https://doi.org/10.1007/978-3-319-64248-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-64248-2_11

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