Data Governance in the Digital Age

Rascão, José Poças

doi:10.4018/978-1-7998-4201-9.ch003

Cited by 3 publications

(2 citation statements)

References 60 publications

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“…However, data governance in this context tends to be limited to narrowly defined technical issues such as information systems and system cluster data while ignoring other factors, which could become the bottlenecks of technical applications. On the other hand, previous works regarding the theoretical construction of data governance framework often neglected technical application methods, and many of them lacked solid theoretical sources and scientific foundations, which brings about much divergence and inconsistency among previous system frameworks (Rascão, 2021). Since a framework generally requires the adjustment of organization and management system, and its ability to solve practical problems cannot be evaluated directly, it is costly to put the framework into practice and its benefits might not be obvious in the short term, which would prevent the framework from being applied.…”

Section: Challenge I: Disconnect Between Technology and Theorymentioning

confidence: 99%

A systematic framework for the complex system engineering of city data governance

et al. 2022

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The importance of data governance in the information age has become a deep consensus among all sectors. Under this context, data-driven urban governance has also become a key requirement for city development. However, as smart city and digital government continuously make progress, the utilization of urban data is still far from true intelligence, and no theoretical research on city data governance can fully guide the concrete implementation of engineering practice. In view of this, this paper proposes a systematic framework for the complex system engineering of urban data governance. We deconstruct urban data governance into a series of basic elements and discuss the key problems in urban data governance engineering regarding three dimensions, i.e., data quality, value and security. In view of the complexity of engineering projects, we establish the systematic framework of urban data governance from four levels, i.e., cognitive, methodological, technical and practical, and demonstrated the application in real practice with a case study on data-based epidemic prevention and control project in Shenzhen. The framework is proposed aiming to break through the key common difficulties in the practice of urban data governance engineering, provide systematic and operable solutions, and finally achieve the set goals.

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Section: Challenge I: Disconnect Between Technology and Theorymentioning

confidence: 99%

A systematic framework for the complex system engineering of city data governance

et al. 2022

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“…In order to achieve greater business impact and value, especially under such rapidly changing market conditions, businesses would eventually need to implement a data-driven culture built upon an adaptive and agile data governance program [14][15][16]. Data governance is a key supporting element of digitalization, enabling barrier-less knowledge flow and sharing within an organization [17]. Managing this change process would allow firms to address two key challenges, namely increasing data literacy and embedding data and analytics (deemed to be the number one game-changer against the pandemic crisis) into company-wide strategies, decision-making, and results [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Accountability through Sustainability Data Governance: Reconfiguring Reporting to Better Account for the Digital Acceleration

Liakh

2021

Sustainability

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Accountability assessment is a highly relevant challenge for companies nowadays. The COVID-19 pandemic prompted a digital acceleration in business environments, which in turn brought more focus on sustainability practices that could help organizations better demonstrate their accountability, thus making them more resilient to the ever-changing socio-economic context. Therefore, this paper aims to evaluate how to further improve corporate accountability (on a strategic and operational level), taking advantage of the digitalization changes that companies are being forced to go through and applying them to the sustainability evaluation process, including the reporting as its final output. The first research outcome is a combined framework, based on data governance and sustainability literature models, seeking to optimize the manageability of sustainability data. The second outcome is a matrix, based on a content analysis of 20 sustainability reports, representing eight possible types of behavior that companies adopt when integrating digitalization practices into their sustainability evaluation process. The aim is to explore how the communication of digital activities could refine the diligence of the sustainability assessment process, with disclosure representing its last step. Finally, the ‘leading’ case was broken down into the general strategic components that could potentially be included in a balanced data-sustainability reporting strategy.

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Data Governance to Counter Hybrid Threats against Critical Infrastructures

Pestana,

Sofou

2024

Smart Cities

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Hybrid threats exploit vulnerabilities in digital infrastructures, posing significant challenges to democratic countries and the resilience of critical infrastructures (CIs). This study explores integrating data governance with business process management in response actions to hybrid attacks, particularly those targeting CI vulnerabilities. This research analyzes hybrid threats as a multidimensional and time-dependent problem. Using the Business Process Model and Notation, this investigation explores data governance to counter CI-related hybrid threats. It illustrates the informational workflow and context awareness necessary for informed decision making in a cross-border hybrid threat scenario. An airport example demonstrates the proposed approach’s efficacy in ensuring stakeholder coordination for potential CI attacks requiring cross-border decision making. This study emphasizes the importance of the information security lifecycle in protecting digital assets and sensitive information through detection, prevention, response, and knowledge management. It advocates proactive strategies like implementing security policies, intrusion detection software tools, and IT services. Integrating Infosec with the methodology of confidentiality, integrity, and availability, especially in the response phase, is essential for a proactive Infosec approach, ensuring a swift stakeholder response and effective incident mitigation. Effective data governance protects sensitive information and provides reliable digital data in CIs like airports. Implementing robust frameworks enhances resilience against hybrid threats, establishes trusted information exchange, and promotes stakeholder collaboration for an emergency response. Integrating data governance with Infosec strengthens security measures, enabling proactive monitoring, mitigating threats, and safeguarding CIs from cyber-attacks and other malicious activities.

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Data Governance in the Digital Age

Cited by 3 publications

References 60 publications

A systematic framework for the complex system engineering of city data governance

A systematic framework for the complex system engineering of city data governance

Accountability through Sustainability Data Governance: Reconfiguring Reporting to Better Account for the Digital Acceleration

Data Governance to Counter Hybrid Threats against Critical Infrastructures

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