Non-technical Requirements Research Articles

Experiences, Lessons, and Challenges With Adapting REDCap for COVID-19 Laboratory Data Management in a Resource-Limited Country: Descriptive Study.

The COVID-19 pandemic brought challenges requiring timely health data sharing to inform accurate decision-making at national levels. In Botswana, we adapted and integrated the Research Electronic Data Capture (REDCap) and the District Health Information System version 2 (DHIS2) platforms to support timely collection and reporting of COVID-19 cases. We focused on establishing an effective COVID-19 data flow at the national public health laboratory, being guided by the needs of health care professionals at the National Health Laboratory (NHL). This integration contributed to automated centralized reporting of COVID-19 results at the Ministry of Health (MOH). This paper reports the experiences, challenges, and lessons learned while designing, adapting, and implementing the REDCap and DHIS2 platforms to support COVID-19 data management at the NHL in Botswana. A participatory design approach was adopted to guide the design, customization, and implementation of the REDCap platform in support of COVID-19 data management at the NHL. Study participants included 29 NHL and 4 MOH personnel, and the study was conducted from March 2, 2020, to June 30, 2020. Participants' requirements for an ideal COVID-19 data management system were established. NVivo 11 software supported thematic analysis of the challenges and resolutions identified during this study. These were categorized according to the 4 themes of infrastructure, capacity development, platform constraints, and interoperability. Overall, REDCap supported the majority of perceived technical and nontechnical requirements for an ideal COVID-19 data management system at the NHL. Although some implementation challenges were identified, each had mitigation strategies such as procurement of mobile Internet routers, engagement of senior management to resolve conflicting policies, continuous REDCap training, and the development of a third-party web application to enhance REDCap's capabilities. Lessons learned informed next steps and further refinement of the REDCap platform. Implementation of REDCap at the NHL to streamline COVID-19 data collection and integration with the DHIS2 platform was feasible despite the urgency of implementation during the pandemic. By implementing the REDCap platform at the NHL, we demonstrated the possibility of achieving a centralized reporting system of COVID-19 cases, hence enabling timely and informed decision-making at a national level. Challenges faced presented lessons learned to inform sustainable implementation of digital health innovations in Botswana and similar resource-limited countries.

Industrial process heat decarbonization: A user-centric perspective

Eliminating greenhouse gas emissions from industrial process heat (IPH) is considered a key element of decarbonizing the overall industrial sector. However, industrial users and the processes by which they may adopt and implement technologies for decarbonization have largely been overlooked in the United States by an emphasis on developing and commercializing new technologies. While recent deployment and demonstration programs are an indication that decarbonization policy is beginning to acknowledge industrial users, little research has been conducted to understand how users mediate technical and nontechnical requirements to decarbonize IPH. Our exploratory analysis uses interviews with industry representatives and document analysis to begin developing a user-centric perspective. We find that successful adoption and implementation of decarbonized IPH technologies may require adaptation to diverse and potentially unique combinations of user requirements and local contexts. Instead of pursuing “crosscutting” IPH technologies, a more effective and expeditious approach may be to develop crosscutting decision-making that spans multiple technologies. This approach may offer unexplored opportunities to improve demonstration and deployment programs, but more user-centric research is needed.

BSELA: A Blockchain Simulator with Event-Layered Architecture

Blockchain technology has found widespread use in various fields, including finance, healthcare, the Internet of Things, and supply chain management, due to its ability to meet technical and non-technical requirements. Therefore, it is crucial for system designers to evaluate the performance and characteristics of a given blockchain platform before deploying it. One way to achieve this is through the use of blockchain simulators. However, existing simulators have limitations in areas such as model scaling, event scheduling, time control, object model evaluation, and simulation magnitude. To address these limitations, we propose a Blockchain Simulator based on Event-Layered Architecture (BSELA) in this paper. BSELA comprises multiple functional modules with effective model scalability, with the core being our proposed Event-Layered Architecture. This architecture introduces a new event-driven scheduling mechanism for discrete-event simulation, which improves the efficiency, stability, and maintainability of event scheduling during blockchain simulation. Furthermore, we propose a time advancement mechanism for subsequent events based on event rounds, which improves the accuracy of time advancement, simulation complexity, and real-time demand handling capability during the simulation. We begin by validating the efficiency of our simulator by comparing experiments with those of existing blockchain simulators. We then validate the accuracy of BSELA through simulation experiments on blockchain network connectivity, block propagation latency, and the number of INV messages propagated per hour. We validated the accuracy of the experimental results by conducting a comparison with Bitcoin data. Finally, in order to address the research gap in the performance of blockchain systems at the underlying peer-to-peer network level and in other fields, we designed and experimentally validated the node-trust network construction mechanism by adjusting the simulator’s blockchain object model. Our experiments show that this tuning mechanism improves data transfer efficiency by 30%–40%, and also improves security. The design and experiments of the BSELA tuning mechanism validate the scalability and flexibility of our simulator for blockchain research.

Towards a Common Methodology and Modelling Tool for 100% Renewable Energy Analysis: A Review

Some advanced countries’ rapid population, economic growth, and energy consumption expansion contribute significantly to global CO2 emissions. And while developed countries have achieved 100% universal access to electricity, mainly from non-renewable sources, many developing countries still lack it. This presents challenges and opportunities for achieving the United Nations’ Sustainable Development Goals (SDGs) 7 and 13 of generating all energy from cleaner or low-carbon sources to reduce CO2 emissions in all countries and combating climate change consequences. Renewable energies have been widely acknowledged to greatly advance this endeavour, resulting in many studies and about 30 countries already with over 70% of their national electricity mix from RE. It has birthed a new paradigm and an emerging field of 100% RE for all purposes, recently receiving much attention from academia and in public discourse. The major challenge with this idea is that achieving such a feat requires a more diverse approach. This study emphasises the need to meet technical and non-technical requirements for working towards a 100% RE for all purposes. Therefore, our work introduces six methodological or evaluation mechanisms (herein, identified as 100% RE evaluation metrics) suitable for existing and future 100% renewable energy analysis. It then reviews energy modelling tools to identify their applicability to 100% RE analysis. The review and perspectives presented in this study will be valuable in developing a common integrated methodology and modelling tool for analysing full renewable energy adoption in countries or regions with best trade-offs, using performance indices that have not been previously used. It will also help with proper national and regional energy resources and system planning for new energy projects and installations, contributing to sustainable development.

Perspective on Code Submission and Automated Evaluation Platforms for University Teaching.

We present a perspective on platforms for code submission and automated evaluation in the context of university teaching. Due to the COVID-19 pandemic, such platforms have become an essential asset for remote courses and a reasonable standard for structured code submission concerning increasing numbers of students in computer sciences. Utilizing automated code evaluation techniques exhibits notable positive impacts for both students and teachers in terms of quality and scalability. We identified relevant technical and non-technical requirements for such platforms in terms of practical applicability and secure code submission environments. Furthermore, a survey among students was conducted to obtain empirical data on general perception. We conclude that submission and automated evaluation involves continuous maintenance yet lowers the required workload for teachers and provides better evaluation transparency for students.

Desain Business Intelligence untuk Manajemen Rumah Sakit

Organizational management, as well as hospital management, could not work precisely without defining the performance indicators to control all business process. This situation encourages the need for information and data analysis availability. BI includes applications, infrastructure, tools and practices that enable organizations to access and analyze data and information to improve and optimize the decisions and organization performance. BI has the potential to improve the quality, efficiency and effectiveness of hospital health services as well. The objective of this study was to design business intelligence prototype for the hospital. BI design was carried out with a Business Intelligence Roadmap approach which has 6 main stages, namely: (1) Justification, (2) Planning, (3) Business Analysis, (4) Design, (5) Construction and (6) Deployment. Data were collected from hospital activities includes registration, Electronic Medical Record (EMR) in the Imaging, Laboratory, Pharmacy, Operating Theater and Medical Check-Up departments activities. Designing BI was preceded by identifying technical and non-technical needs, then continued by designing BI itself. BI roadmap approach was used for this propose. Technical requirements for designing BI include hardware and software infrastructure readiness, while non-technical requirements include Business Analysis which consists of Project Requirements Definition, Data Analysis, Application Prototyping and Metadata repository Analysis. Designing BI itself includes: Designing a multidimensional database and designing ETL. The user interfaces for BI was shown in the Performance Dashboard, which allows organizations to track all aspects of their daily business activities and performance.

Ilities Semantic Basis: Research Progress and Future Directions

This paper summarizes progress on the investigation of an ilities semantic basis. One of the fundamental challenges for developing a clearer understanding of the semantics of “ilities” (sometimes referred to as system qualities) is continuing ambiguity in these terms. Prior and ongoing research on use of a prescriptive semantic basis has resulted in a framework for formulating ility “definitions.” Progress has been made on evolving the semantic basis construct, a translation layer, and ilities metrics. Synergies with other relevant research are explored. Potential application of the semantic basis approach is discussed, including near-term application in education and longer-term application in technical document comprehension of non-technical requirements. Several future directions for ilities research within the systems community are proposed.

Future electrical energy supply for the Isle of Pellworm

The electric power generation, transmission and distribution are in a profound process of change, particularly related to the activities of the various regions. It is currently not clear enough for each region, what technical requirements and non-technical requirements for a successful operation of such a smart grid must be met. It is currently not known, how to build it up and what results can be achieved. This paper describes the key technical and non-technical aspects for the successful operation of a smart grid in a certain region. It takes into account the lessons learned from the activities for the development of a smart grid on the Isle of Pellworm.

Extracting Soft Issues during Requirements Elicitation:A Preliminary Study

Requirements Engineering (RE) is a critical process in Software Engineering (SE) activities. RE helps stakeholders to manage requirements appropriately before dedicated requirements are used to design and implement software. The first stage in RE process is known as requirements elicitation whereby during elicitation, stakeholders will perform a set of activities to permit understanding in problem domain for respected scenario and hence proposing a set of established requirements in developing software. In elicitation, stakeholders need to collaborate and communicate in order to produce unambiguous requirements and create mutual agreement for software design and development. This can produce desired solution for all stakeholders. Soft issue is one of non-technical requirements that can associate with social presence, social interaction elements such as comfort, connectedness and motivation. This requirements need to be emphasized during RE process especially for a system that is categorized in Computer- Supported Collaboration Working (CSCW) domain. Users need CSCW domain system to carry out virtual communication, knowledge sharing via system's features. The aim of this paper is to carry out a preliminary study on RE process and requirements elicitation activities by identifying whether soft issues have been engaged in existing requirements elicitation process. Another aim is to compare stakeholders' roles based on selected articles. The method to investigate requirements elicitation process is done by identifying existing elicitation processes as well as involvement of stakeholders' collaboration during elicitation. According to the study, the comparison of existing requirements elicitation processes and comparison of job roles have been produced as a result in this paper.

Technical safety vs. public involvement? A case study on the unrealized project for the disposal of nuclear waste at Wellenberg (Switzerland)

The disposal of radioactive waste is a striking example with which to trace the changing relationship between technology, society and policy when dealing with societally relevant controversial issues. The change is characterized by a transition from a technocratic approach to an approach with more intense cooperation and public participation. We analyze the societal discourse of a failed disposal project for low- and intermediate-level waste at the Mount Wellenberg site, Canton of Nidwalden (Central Switzerland). Insights are based on a case study in 2006, with focus groups, expert interviews, a media analysis, a representative canton-wide postal survey and targeted in-depth stakeholder interviews. The article focuses on the relationship of safety and process aspects. The data suggest that both are prime issues and people recognize the need for disposal of radioactive waste in a technical system but only if a fair procedure is guaranteed. We conclude that a sound balance between safety and procedural aspects needs to be found and thus a functional-dynamic view of public involvement is necessary, i.e. distinct levels of involvement (ranging from mere information up to empowerment) must fit the corresponding technical and non-technical requirements of a stepwise decision-making process.

A method and tool for rapid consumer application development

In recent years, consumer oriented information systems (IS) development has become an increasingly important matter, as more and more complex IS are targeted towards consumer markets. We suggest that developing IS for consumers creates practical and research challenges, which researchers should attend to. In this paper we offer a straightforward way of gathering non-technical requirements from consumers and integrating them into a rapid IS development process. To demonstrate the feasibility of such an approach, we have constructed a support environment within metaedit+ meta computer-aided software engineering (CASE) tool to link an existing consumer requirements elicitation method, critical success chains (CSC), to a domain specific method (DSM) for rapid application development for mobile phones. The developed approach facilitates the development of mobile application prototypes, which can be used by end-users in an emulator or actual phone. These prototypes can be used to confirm and refine the requirements gathered from consumers.

Hierarchies of Architectures of Collaborative Computational Intelligence

Computational Intelligence (CI) supports a wealth of methodologies and a plethora of algorithmic developments essential to the construction of intelligent systems. Being faced with inherently distributed data which become evident, the paradigm of CI calls for further enhancements along the line of designing systems that are hierarchical and collaborative in nature. This emerging direction could be referred to as collaborative Computational Intelligence (or C2I for brief). The pervasive phenomenon encountered in architectures of C2I is that collaboration is synonym of knowledge sharing, knowledge reuse and knowledge reconciliation. Knowledge itself comes in different ways: as some structural findings in data and usually formalized in the framework of information granules, locally available models, some action plans, classification schemes, and alike. In such distributed systems sharing data is not feasible given existing technical constraints which are quite often exacerbated by non-technical requirements of privacy or security. In this study, we elaborate on the design of information granules which comes hand in hand with various clustering techniques and fuzzy clustering, in particular.

Exploring the Gap Between Water Managers and Researchers: Difficulties of Model-Based Tools to Support Practical Water Management

Supported by EU funds, the European research community has been putting much effort into providing model-based tools to support water resource managers in implementing water management as well as the implementation of the Water Framework Directive. This paper presents the results of a two-year long elicitation phase which aimed to explain why the use of tools in water management is not as great as the corresponding investment in applied research in this area might suggest it should be. The paper identifies a gap between water managers and research community that is evidence of a mutual misunderstanding of the fundamental activities of both communities. We elaborate on these misunderstandings between these two communities by focussing on their attitudes towards seven assumptions that derived from an elicitation phase carried out between 2003 and 2004. These misunderstandings appear to revolve around the issues of the role and importance of model-based tools in water management; the transferability of models to new target sites; the role of participatory modelling in water management; how to solve lack of confidence in model-based tools; the development of computer user interfaces to improve tool usability; and the nature of model integration. Based on these insights, recommendations for improving research, development and ultimately the use of model-based tools in river basin management processes are proposed. The recommendations include improving researchers’ understanding of water management processes and the role their tools play within such a process; identifying for both communities the importance that such tools can play as part of social learning-oriented management processes; improving the role of software consultancies as carriers of research results; considering new methods of model transferability between target basins; and expanding the structure of funding for academic research and development projects to allow the greater provision of non-technical requirements such as post-development tool maintenance and transferability, required by water managers.

Algorithmic Statistical Process Control: Some Practical Observations

Algorithmic Statistical Process Control (ASPC) is an approach to quality improvement that reduces predictable quality variations using feedback and feedforward techniques, and then monitors the entire system to detect changes. As such, it is a marriage of control theory and statistical process control (SPC). Control theoretical concepts are used to minimize deviations from target by process adjustments; sec is used to gain fundamental improvements. Where applicable, ASPC is a logical next step in the drive for continuous quality improvement. This paper presents the ASPC concept and its applications to practitioners. Technical and non-technical requirements and factors conducive to the use of ASPC are emphasized, and pre-planning for the use of ASPC in new processes is discussed.