SuDaMa: Sustainable Open Government Data Management Framework for Long-Term Publishing and Consumption

Sánchez-Nielsen, Elena; Morales, Alejandro; Mendo, Omar; Chávez-Gutiérrez, Francisco

doi:10.1109/access.2021.3127472

Cited by 8 publications

(6 citation statements)

References 37 publications

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“…Open data lakes: We classify research on open data lakes into (1) data platforms, [34][35][36][37] (2) government open data portals, 33,38,39 (3) systems operating on open data lakes, [40][41][42][43] and ( 4) custom open data lakes. 16 First, research on data platforms is mainly to improve or expand CKAN, and there are also studies on new data platforms that focus on sustainability and improve user consumption environments, such as SuDaMa.…”

Section: Related Workmentioning

confidence: 99%

“…16 First, research on data platforms is mainly to improve or expand CKAN, and there are also studies on new data platforms that focus on sustainability and improve user consumption environments, such as SuDaMa. 37 Second, in the government data portals, R. Machova et al 38 evaluated the data portals of each country based on various items and presented comprehensive evaluation results. However, there are a few cases where the evaluation results are outdated and do not match the current portal status (e.g., the evaluation results are 1st in the UK, 3rd in the US, and 6th in Canada).…”

Section: Related Workmentioning

confidence: 99%

“…Open data lakes : We classify research on open data lakes into (1) data platforms, 34–37 (2) government open data portals, 33,38,39 (3) systems operating on open data lakes, 40–43 and (4) custom open data lakes 16 . First, research on data platforms is mainly to improve or expand CKAN, and there are also studies on new data platforms that focus on sustainability and improve user consumption environments, such as SuDaMa 37 . Second, in the government data portals, R. Machova et al 38 evaluated the data portals of each country based on various items and presented comprehensive evaluation results.…”

Section: Related Workmentioning

confidence: 99%

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Demeter: An automatic framework for data migration in open data lakes

Kim,

Han,

Son

et al. 2023

Softw Pract Exp

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An open data lake stores various forms and types of open data, and there is an increasing demand to manage raw data in tables rather than files for efficient data exploration and analysis. In this paper, we investigate the data management of open data lakes and recognize the limitations of table migration and related problems. First, open data lakes have problems of preprocessing complexity, scale limitation, and platform dependency due to the traditional data management method and open data characteristics. Second, existing studies for table migration have problems of lack of scalability, migration incompleteness, and scale limitation. In this work, we present a novel automation framework, called Demeter, which solves three problems inherent in open data lakes by expanding automation. Specifically, it supports automating catalog collection and preprocessing tasks to solve preprocessing complexity and scale limitation. It also supports platform universality for representative data platforms through the automation of catalog analysis and detailed processing logic. Demeter then solves three problems in table migration by adopting Airbyte, an open‐source ELT platform, and by enhancing automation capability with the Airbyte manager. We verify that Demeter resolves all the problems above through extensive experiments and proves its scalability and universality. In addition, significantly outperforms CKAN by Demeter up to 508.5% in automation performance, up to 207.28% in processing time, and up to 917.17% in migration performance. These results indicate that Demeter is an excellent automation framework that increases the utilization of large‐scale open data and supports reliable Internet‐scale migration.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Demeter: An automatic framework for data migration in open data lakes

Kim,

Han,

Son

et al. 2023

Softw Pract Exp

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“…The OGD infusion is intended to ensure that OGD publishing occurs on a continual basis rather than as a one-time activity for data providers. This is because OGD must be sustained over an extended period of time in order to gain benefits and generate more value for the citizen [20,21]. Moreover, Zuiderwijk and de Reuver [17] found that lack of sustainability appears as the new concern to achieving OGD's intended objective.…”

Section: Infusionmentioning

confidence: 99%

“…Hassandoust, et al [19] suggested that one of the main reasons why organizations fail to fully reap the advantages of their investments in IS/IT is the under-utilization of the technology. This is due to, in many cases, opening up data began as part of a politically motivated effort rather than focusing on the main objective of OGD implementation [20,21]. In a similar case, Zhu [22] revealed that one of the earliest open data initiatives in the United States, JURIS, failed to achieve its goals due to a lack of social-political support.…”

Section: Introductionmentioning

confidence: 99%

Factors influencing open government data post-adoption in the public sector: The perspective of data providers

Mustapa

Hamid²,

Nasaruddin³

2022

PLoS ONE

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Providing access to non-confidential government data to the public is one of the initiatives adopted by many governments today to embrace government transparency practices. The initiative of publishing non-confidential government data for the public to use and re-use without restrictions is known as Open Government Data (OGD). Nevertheless, after several years after its inception, the direction of OGD implementation remains uncertain. The extant literature on OGD adoption concentrates primarily on identifying factors influencing adoption decisions. Yet, studies on the underlying factors influencing OGD after the adoption phase are scarce. Based on these issues, this study investigated the post-adoption of OGD in the public sector, particularly the data provider agencies. The OGD post-adoption framework is crafted by anchoring the Technology–Organization–Environment (TOE) framework and the innovation adoption process theory. The data was collected from 266 government agencies in the Malaysian public sector. This study employed the partial least square-structural equation modeling as the statistical technique for factor analysis. The results indicate that two factors from the organizational context (top management support, organizational culture) and two from the technological context (complexity, relative advantage) have a significant contribution to the post-adoption of OGD in the public sector. The contribution of this study is threefold: theoretical, conceptual, and practical. This study contributed theoretically by introducing the post-adoption framework of OGD that comprises the acceptance, routinization, and infusion stages. As the majority of OGD adoption studies conclude their analysis at the adoption (decisions) phase, this study gives novel insight to extend the analysis into unexplored territory, specifically the post-adoption phase. Conceptually, this study presents two new factors in the environmental context to be explored in the OGD adoption study, namely, the data demand and incentives. The fact that data providers are not influenced by data requests from the agency’s external environment and incentive offerings is something that needs further investigation. In practicality, the findings of this study are anticipated to assist policymakers in strategizing for long-term OGD implementation from the data provider’s perspective. This effort is crucial to ensure that the OGD initiatives will be incorporated into the public sector’s service thrust and become one of the digital government services provided to the citizen.

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