e-Government for good governance : establishing efficient governance through data-driven policymaking in Africa

Mini Dissertation (MPhil (Human Rights and Democratisation in Africa))--University of Pretoria, 2022.Governance in Africa has traditionally been hindered by a lack of accurate data and information. This has resulted in policies that are poorly informed and ineffective in addressing the needs of citizens. However, advances in technology and the increasing availability of data have provided a new opportunity for African governments to improve their decision-making processes. By collecting and analysing data, governments can identify the most pressing issues and develop targeted policies to address them. Data-driven policymaking has the potential to revolutionise the way governments in Africa make decisions, and can help address some of the challenges that Africa faces, such as poverty, inequality, and limited access to essential services. The effective use of data can also improve transparency and accountability, enabling citizens to hold their governments to account and encouraging greater public participation in the policymaking process. Having identified poor governance and ineffective public policies in Africa as major problems across the continent, this study has sought to respond to those challenges by exploring and proposing the adoption of a data-driven approach in public policies, and which could eventually improve the state of governance.Centre for Human RightsMPhil (Human Rights and Democratisation in Africa)Unrestricte

Laboratory forensics for open science readiness: an investigative approach to research data management

Recently, the topic of research data management has appeared at the forefront of Open Science as a prerequisite for preserving and disseminating research data efficiently. At the same time, scientific laboratories still rely upon digital files that are processed by experimenters to analyze and communicate laboratory results. In this study, we first apply a forensic process to investigate the information quality of digital evidence underlying published results. Furthermore, we use semiotics to describe the quality of information recovered from storage systems with laboratory forensics techniques. Next, we formulate laboratory analytics capabilities based on the results of the forensics analysis. Laboratory forensics and analytics form the basis of research data management. Finally, we propose a conceptual overview of open science readiness, which combines laboratory forensics techniques and laboratory analytics capabilities to help overcome research data management challenges in the near future.Algorithms and the Foundations of Software technolog

Laboratory forensics for open science readiness: an investigative approach to research data management

Recently, the topic of research data management has appeared at the forefront of Open Science as a prerequisite for preserving and disseminating research data efficiently. At the same time, scientific laboratories still rely upon digital files that are processed by experimenters to analyze and communicate laboratory results. In this study, we first apply a forensic process to investigate the information quality of digital evidence underlying published results. Furthermore, we use semiotics to describe the quality of information recovered from storage systems with laboratory forensics techniques. Next, we formulate laboratory analytics capabilities based on the results of the forensics analysis. Laboratory forensics and analytics form the basis of research data management. Finally, we propose a conceptual overview of open science readiness, which combines laboratory forensics techniques and laboratory analytics capabilities to help overcome research data management challenges in the near future.Prevention, Population and Disease management (PrePoD)Public Health and primary car

A Causal Comparative Analysis of Leveraging the Business Analytical Capabilities and the Value and Competitive Advantages of Mid-level Professionals Within Higher Education

The purpose of this quantitative causal-comparative study is an empirical examination of the differences in business intelligence capability and the value and competitive advantage of mid-level higher education academia professionals from community colleges, four-year public, and four-year private institutions within the United States. Institutions of higher education have an overabundant amount of student data that is often inaccessible and underutilized. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and Management Information Systems/Decision Support Systems theory, using two-way ANOVA analysis, this research examined factors to understand the mastery of readiness for mid-level professionals in higher education institutions to embrace digital technologies and resources to develop a culture of digital transformation. This study applied the Business Analytics Capability Assessment survey responses from 176 mid-level higher education professionals, from community colleges, four-year private, and four-year public institutions, to understand how higher education professionals use Business Intelligence Analytics (BIA) and Big Data (BD) to improve the organization, operational business decisions, and data management strategies to provide actionable insights. This study found no significance between the type of institution that has business intelligence capability and the value and competitive advantage. A significant difference with a medium effect was identified between the Business Analytics Capability and the Value and Competitive Advantage for mid-level professionals who do and do not utilize BIA and BD resources. Therefore, this study calls for future research to understand how successful institutions have implemented BIA and BD tools and how higher education is shaped on a macro level