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A computational model for corruption assessment

Published: 04 August 2013 Publication History

Abstract

Corruption afflicts public services world-wide and is universally considered undesirable. However, there is little prior work to formalize it so that it can be attacked effectively using computational (ICT) techniques. It is believed that trends like process (service) automation and open data help tackle corruption but little is known about why and when. In this work, we address this gap by (a) presenting a meta-model for agent-delivered services motivated by real case studies in corruption, (b) describing common patterns of corruption in such service process designs, (c) formalizing the patterns via a language that instantiates the meta-model, and (d) evaluating the formal patterns on new cases of corruption. We then discuss how the formal patterns help evaluate effectiveness of the various mechanisms for addressing corruption.

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  • (2017)Utilization of open government data: A systematic literature review of types, conditions, effects and usersInformation Polity10.3233/IP-16001222:1(1-24)Online publication date: 12-May-2017

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cover image ACM Other conferences
AIIP '13: Joint Proceedings of the Workshop on AI Problems and Approaches for Intelligent Environments and Workshop on Semantic Cities
August 2013
65 pages
ISBN:9781450323468
DOI:10.1145/2516911
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 04 August 2013

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  • (2017)Utilization of open government data: A systematic literature review of types, conditions, effects and usersInformation Polity10.3233/IP-16001222:1(1-24)Online publication date: 12-May-2017

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