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Modern information systems (MIS) have increased the variety of information systems which have been and can be designed to such an extent that auditors must finally recognise the Law of Requisite Variety. The auditability of MIS is a double‐edged proposition since the variety of the MIS must be matched by auditors if they want to be recognised as control agents. Thus, either MIS variety must be reduced to match the audit variety achievable or the audit variety must be increased to match the existing MIS variety. In other words, an intelligent interface is needed between auditors and MIS. Auditors require a language and a communication channel to evaluate the internal controls of the MIS as well as the information generated by the MIS.

The Covid-19 pandemic has profoundly affected urban communities, generating the need for an immediate response from local governance. The availability of urban data platforms in some smart cities helped the relevant actors to develop various solutions in an innovative and highly contextual way. The purpose of this paper is to explore the role of data platforms in smart cities in the context of the Covid-19 crisis.

A total of 85 studies were identified using the Clarivate Analytics Web of Science electronic library. After applying exclusion and inclusion criteria, 61 publications were considered appropriate and reasonable for the research, being read in-depth. Finally, only 52 studies presented relevant information for the topic and were synthesized following the defined research questions. During the research, the authors included in the paper other interesting references found in selected articles and important information regarding the role of data in the fight against Covid-19 in smart cities available on the Internet and social media, with the intention to capture both academic and practical perspectives.

The authors' main conclusion suggests that based on their previous expertise in collecting, processing and analyzing data from multiple sources, some smart cities quickly adapted their data platforms for an efficient response against Covid-19. The results highlight the importance of open data, data sharing, innovative thinking, the collaboration between public and private stakeholders, and the participation of citizens, especially in these difficult times.

The city managers and data operators can use the presented case studies and findings to identify relevant data-driven smart solutions in the fight against Covid-19 or another crisis.

The performance of smart cities is a social concern since the population of urban communities is continuously growing. By reviewing the adoption of information technologies-based solutions to improve the quality of citizens' life, the paper emphasizes their potential in societies in which information technology is embedded, especially during a major crisis.

This research re-emphasizes the importance of collecting data in smart cities, the role of the diversity of their sources and the necessity of citizens, companies and government synergetic involvement, especially in a pandemic context. The existence of smart solutions to process and extract information and knowledge from large data sets was essential for many actors involved in smart cities, helping them in the decision-making process. Based on previous expertise, some smart cities quickly adapted their data platforms for an efficient response against Covid-19. The paper analyzes also these success cases that can be considered models to be adopted by other municipalities in similar circumstances.

The other day I was at a meeting with several government officials to discuss the establishment of a retention, conservation and disposition schedule for a large, complex, automated information system. Around the table were users, systems people, the head of data administration and the departmental records manager. The first thing that intrigued me about this meeting was that the records manager and the systems people (including the data administrator) had never met each other, even though all had worked in the department for at least 2 years. For someone who was concerned with launching an initiative that would depend on the cooperation of these areas I was more than a little shaken.

Despite several big data maturity models developed for businesses, assessment of big data maturity in the public sector is an under-explored yet important area. Accordingly, the purpose of this study is to identify the big data maturity models developed specifically for the public sector and evaluate two major big data maturity models in that respect: one at the state level and the other at the organizational level.

A literature search is conducted using Web of Science and Google Scholar to determine big data maturity models explicitly addressing big data adoption by governments, and then two major models are identified and compared: Klievink et al.’s Big Data maturity model and Kuraeva’s Big Data maturity model.

While Klievink et al.’s model is designed to evaluate Big Data maturity at the organizational level, Kuraeva’s model is appropriate for assessments at the state level. The first model sheds light on the micro-level factors considering the specific data collection routines and requirements of the public organizations, whereas the second one provides a general framework in terms of the conditions necessary for government’s big data maturity such as legislative framework and national policy dimensions (strategic plans and actions).

This study contributes to the literature by identifying and evaluating the models specifically designed to assess big data maturity in the public sector. Based on the review, it provides insights about the development of integrated models to evaluate big data maturity in the public sector.

The purpose of this study is to underpin the impact of cloud computing in global accounting information systems (AIS). Moreover, it investigates the key aspects that ought to be considered by the organization before choosing to pick the correct accounting system.

The study looks at and depends on narrative investigation of previous studies. In the examination talked about the principle issues with respect to the utilization of cloud and database the executives in the AIS through developing research model.

The focal point of the paper is the impact of cloud computing worldview on the business area. This paper highlights different facts of cloud accounting, published research papers and the benefits and possible risks determined by the implementation of cloud services, mostly in relation to the accounting department.

Considering the numerous ramifications of cloud advancements on the present business process, there is a need for an examination of how these innovations will be used in AIS to improve precision, benefits and risks. At the same time, there is need to investigate the determinant elements of actualizing cloud advances in the AIS. More importantly, to the author’s knowledge, this is the first study that focuses on the number of published research works to show the importance of cloud computing in accounting and information systems.

Argues that online privacy rights of consumers are not absolute rights but joint ownership privileges they share with online marketers. Consumers can voluntarily transfer these privileges to online marketers under certain mutually agreeable conditions. Accordingly, online marketers can facilitate, motivate and compensate such transfers by designing various innovative personalization strategies that, rather than jeopardize the privacy privileges of consumers, would benefit them. Technology and society can progress only through such partnerships. Cites two consistently successful net companies, Dell and eBay, as examples of such partnered personalizations.

In this paper we discuss an area of information systems management and development that appears to have been practised by many major European and US organisations: the area of corporate data modelling. However, rather suprisingly perhaps, it is clear that there is little theoretical or empirical literature devoted to this important issue. There is little empirical evidence to indicate the actual scale of adoption of this practice, and there is certainly little analytical material devoted to questions of the efficacy of this activity or considerations of good practice in this area. The main aim of this paper is to begin to offer some early empirical and analytical material on corporate data modelling. We have been conducting a study of a number of organisation’s experience of corporate data modelling in the UK. We would hope that an examination of the current corporate experience of corporate data modelling will stimulate a clearer discussion of the purposes and practices of this important area of modern information systems planning.

The purpose of this paper is to explore the information landscape of organizations by focusing on the evolution of the fields of so‐called records management and data management.

The author draws on his personal experience with the National Archives of Canada.

Records management and data management quite literally mean the same thing. There is no “gap”, as indicated in the title. The only gaps that exist are in the perceptions of what each concept means and the functions and status of the information jurisdictions that have claimed each for their own.

The paper recommends an integration of what has been perceived to be the disparate fields of records management and data management, finding that records or data should be managed from a global and corporately defined perspective

This paper aims to present pertinent research challenges in the field of (big) data-informed policy-making based on the research, undertaken within the course of the European Union-funded project Big Policy Canvas. Technological advancements, especially in the past decade, have revolutionised the way that both every day and complex activities are conducted. It is, thus, expected that a particularly important actor such as the public sector, should constitute a successful disruption paradigm through the adoption of novel approaches and state-of-the-art information and communication technologies.

The research challenges stem from a need, trend and asset assessment based on qualitative and quantitative research, as well as from the identification of gaps and external framework factors that hinder the rapid and effective uptake of data-driven policy-making approaches.

The current paper presents a set of research challenges categorised in six main clusters, namely, public governance framework, privacy, transparency, trust, data acquisition, cleaning and representativeness, data clustering, integration and fusion, modelling and analysis with big data and data visualisation.

The paper provides a holistic overview of the interdisciplinary research challenges in the field of data-informed policy-making at a glance and shall serve as a foundation for the discussion of future research directions in a broader scientific community. It, furthermore, underlines the necessity to overcome isolated scientific views and treatments because of a high complex multi-layered environment.

The purpose of this paper is to explore the breadth of the challenges and issues facing institutional repositories in academic libraries, based on a survey of academic librarians. Particularly, this study covers the challenges and barriers related to data management facing institutional repositories.

The study uses a survey method to identify the relative significance of major challenges facing institutional repositories across six dimensions, including: data, metadata, technological requirements, user needs, ethical concerns and administrative challenges.

The results of the survey reveal that academic librarians identify limited resources, including insufficient budget and staff, as the major factor preventing the development and/or deployment of services in institutional repositories. The study also highlights crucial challenges in different dimensions of institutional repositories, including the sheer amount of data, institutional support for metadata creation and the sensitivity of data.

This study is one of a few studies that comprehensively identified the variety of challenges that institutional repositories face in operating academic libraries with a focus on data management in institutional repositories. In this study, 37 types of challenges were identified in six dimensions of institutional repositories. More importantly, the significance of those challenges was assessed from the perspective of academic librarians involved in institutional repository services.