Optimizing Data Quality in Interagency Data Sharing: A Framework
Dublin Core
Title
Optimizing Data Quality in Interagency Data Sharing: A Framework
Subject
data quality, government, data sharing, data exchange, framework
Description
As governments strive for openness, inclusivity, and collaboration to deliver public value and inform
policy with a data-driven approach, interagency data sharing (IDS) becomes increasingly critical.
However, challenges remain, particularly regarding data quality. This study addresses this gap by
proposing a novel framework for IDS within government agencies. This framework goes beyond
traditional approaches by proactively managing data quality throughout its lifecycle. It aims to
provide insights for fostering effective IDS practices that support collaborative and evidence-based decision-making, a cornerstone of modern government operations. This research employs a
Systematic Literature Review (SLR) to examine current IDS practices and associated challenges.
Subsequently, a case study conducted at Indonesia's Directorate General of Taxes utilizes semistructured in-depth interviews with practitioners to explore practical implementation scenarios. The framework developed through this research aims to mitigate various challenges related to IDS, particularly focusing on enhancing data quality assurance. By ensuring high-quality exchanged data, this framework empowers governments to break down silos, fostering a more coordinated and efficient approach to public service delivery.
policy with a data-driven approach, interagency data sharing (IDS) becomes increasingly critical.
However, challenges remain, particularly regarding data quality. This study addresses this gap by
proposing a novel framework for IDS within government agencies. This framework goes beyond
traditional approaches by proactively managing data quality throughout its lifecycle. It aims to
provide insights for fostering effective IDS practices that support collaborative and evidence-based decision-making, a cornerstone of modern government operations. This research employs a
Systematic Literature Review (SLR) to examine current IDS practices and associated challenges.
Subsequently, a case study conducted at Indonesia's Directorate General of Taxes utilizes semistructured in-depth interviews with practitioners to explore practical implementation scenarios. The framework developed through this research aims to mitigate various challenges related to IDS, particularly focusing on enhancing data quality assurance. By ensuring high-quality exchanged data, this framework empowers governments to break down silos, fostering a more coordinated and efficient approach to public service delivery.
Creator
Monica Vivi Kurniawati, Mohamad Faisal Zulmy, and Yova Ruldeviyani
Source
http://dx.doi.org/10.21609/jiki.v18i1.1310
Publisher
Faculty of Computer Science Universitas Indonesia
Date
2025-02-08
Contributor
Sri Wahyuni
Rights
e-ISSN : 2502-9274 printed ISSN : 2088-7051
Format
PDF
Language
English
Type
Text
Coverage
Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Files
Collection
Citation
Monica Vivi Kurniawati, Mohamad Faisal Zulmy, and Yova Ruldeviyani, “Optimizing Data Quality in Interagency Data Sharing: A Framework,” Repository Horizon University Indonesia, accessed May 23, 2025, https://repository.horizon.ac.id/items/show/8939.