ABSTRACT
When pandemic rose in 2020, people were fighting against COVID-19 virus and organizations had accelerated their digitization and cloud adoption rapidly (De et al. in Int J Inf Manag 55:102171, 2020 [1]) to meet the online based business during the lockdown. This chaos helped fraudsters and attackers taking advantage of the momentary lack of security controls and oversight. Federal Investigation Bureau (FBI) Internet Crime Compliant Center (IC3) 2020 reported highest number of complaints in 2020 (791 k + ) compared to prior five years (298 k + in 2016), with peak losses reported ($4.2 Billion in 2020 compared to $1.5 Billion in 2016) (Internet Crime Complaint Center in Internet crime report. Federal Bureau of Investigation, Washington, D.C., 2020 [2]). Majority of these incidents were connected to financial fraud, identity fraud, and phishing for personally identifiable information (PII). Considering the severity and impact of personal data exposure over cloud and hybrid environment, this paper provides a brief overview of prior research and discuss technical solutions to protect data across heterogeneous environments and ensure privacy regulations. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Over the past decade, Open Government Data (OGD) strategies have become a continuing concern in administrative services. This is even truer than at any time. Given the current situation, data management, specifically consistent data publication, has been central to public institutions. The Covid-19 pandemic has shown that data collected by public administrations could make valuable contributions. However, in Switzerland, the pandemic has highlighted the limitations of public organizations' capability to lead the publication of their data. Based on an ethnography and a literature review, this paper explores how data governance components impact OGD publication process and presents a model of OGD governance. For this purpose, we identify key data governance components necessary to OGD publication-structural, procedural, and relational-And illustrate how OGD challenges rarely arise from the publication of OGD or the open nature of data itself, but a lack of data governance. © 2022 ACM.
ABSTRACT
The epidemic has had a profound impact on Chinese economy. In order to explore which factors have played an important role in Chinese economic development, this paper uses Internet software such as SPSS to construct a regression model to process and analyze economic data and evaluate its impact. First, we use SPSS software to construct a regression equation model that affects China's economic development. After that, we select four new factors affecting China's economic development : personal consumption level, financial data governance level, big data support capabilities, and robotics capabilities. After that, we use the SLOPE regression function model to calculate the P value, the correlation coefficient beta and the variance var value, and derived the regression parameter equation from this. Finally, based on regression equations and regression coefficients, new suggestions for China's economic development are put forward. © 2021 IEEE.
ABSTRACT
As the impact of COVID-19 continues, the "New infrastructure" initiative is stepping up, bringing both opportunities and challenges to smart city development. During the 14th Five-Year Plan period, the construction of smart city in China will be guided by the requirements of modernization of national governance, based on the needs, combined with the characteristics of urban capabilities, conform to the development trend of information technology, deepen digital infrastructure, improve service level, accelerate data governance, and build collaborative mechanism. © 2021 Kriedt Enterprises Ltd. All Rights Reserved.
ABSTRACT
This paper investigates the state of open government data in the Philippines by comparing access to health information during the COVID-19 pandemic with available open data prior to it. It first assesses the availability and demand for government data through Freedom of Information (FOI) requests and data posted in government Open Data platforms. It then compares this with the emerging lessons from the creation of the health data hub during the pandemic. It analyzes it by considering data openness across three dimensions: content, people, and process. The openness of content subscribes to the accepted definition of data being free to access, and free to manipulate. Openness to people refers to who can actively participate and/or collaborate. Openness of the process pertains to whether the processes involved is transparent and whether the process is open to inputs from participants. It considers lessons from the pandemic as a way forward for more systematic data sharing for the whole of government in the future. © 2021 ACM.
ABSTRACT
The COVID-19 public health crisis has accelerated the transformation of health systems to become more closely tied to citizens/patients and increasingly dependent on the provision and use of telehealth services. Internet of Things (IoT)-enabled telehealth systems (deployed in conjunction with AI systems) could facilitate the smart transformation of healthcare from a merely reactive system to a data-driven and person-centred system that provides remote health diagnosis, monitoring and treatment services, integrated real-time response solutions, as well as prospective insights. However, the realisation of these health-related benefits requires the processing of vast amounts of data concerning health. These operations and the use of new enabling technologies raises significant legal concerns and questions the applicability of existing/proposed legal concepts. For this reason, the research analyses the adequateness of EU privacy, data protection, data governance, AI governance and other regulatory rules in IoT-enabled (and AI-augmented) telehealth systems. In addition, the research aims to identify technical and organisational measures (best practices), which could facilitate the implementation of normative principles in these information systems in an effective manner. © 2021 ACM.