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Using Open Government Data for Teaching Data Analytics in Public Sector Management

aWU Vienna University of Economics and Business Department of Management, Austria
bUniversity College London Department of Economics, UK

Reimagining Public Sector Management

ISBN: 978-1-80262-022-1, eISBN: 978-1-80262-021-4

Publication date: 18 November 2022

Abstract

Purpose

Digitalisation, big data and data analytics are hot topics for today's economic sectors. Given these trends, developing information technology capabilities of those who wish to join the public sector workforce has been emphasised in public administration teaching curricula. In this chapter, focusing on the public sector, we ask: What kind of data is published by governments and how can these data be used in teaching data analytics?

Design/Method

Against the backdrop of the growing importance of data analytics in public sector management curricula, this chapter uses the IMPACT cycle model to demonstrate how datasets from open government data portals can be used for teaching.

Findings

Several examples are shown to illustrate the different steps of the IMPACT cycle model. Concluding remarks include a reflection where potential caveats, dysfunctions and limits of data analytics are outlined.

Originality

The chapter explicitly focuses on ‘real world’ open government data published on open data portals. A holistic approach to data analytics ‘from start to finish’ is shown, including preparing datasets for the analysis and presenting results to line managers, whereas some of the previous work solely shows parts (e.g. testing the data).

Keywords

Citation

Polzer, T. and Li, D. (2022), "Using Open Government Data for Teaching Data Analytics in Public Sector Management", Diamond, J. and Liddle, J. (Ed.) Reimagining Public Sector Management (Critical Perspectives on International Public Sector Management, Vol. 7), Emerald Publishing Limited, Leeds, pp. 123-135. https://doi.org/10.1108/S2045-794420220000007010

Publisher

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Emerald Publishing Limited

Copyright © 2023 Tobias Polzer and Dunli Li. Published under exclusive licence by Emerald Publishing Limited