Information Systems Engineering Research Articles

Editorial on the Special Issue of the World Wide Web journal with selected papers from the 22nd International Conference on Web Information Systems Engineering (WISE)

Editorial on the Special Issue of the World Wide Web journal with selected papers from the 22nd International Conference on Web Information Systems Engineering (WISE)

Automated system for the control of the substantive processes of linkage with society of the information systems engineering career at the UMET

The following research presents a system to optimize the control of the processes of Linkage with society within the Information Systems Engineering career at the Metropolitan University of Ecuador (UMET). Currently, the management of students' academic information is affected by the dispersion of data in printed documents, which makes access and a prompt response to the information requirements formulated in the different processes difficult. Currently, career procedures are carried out manually, which leads to the loss of documents and the possibility that coordinators forget to provide answers about the current status of the processes that students are carrying out. The proposed system seeks to mitigate these problems, providing support to both the process coordinator and the student. The system makes it easier for the coordinator to keep precise control of which students are immersed in each process and in what phase they are. Additionally, it allows you to approve or reject the documentation associated with the process, ensuring that it is completed correctly. This procedure is essential so that the coordinator can approve the process and the student obtains a certificate that validates their participation in said activity, essential for their degree. In addition, the system offers students the possibility of enrolling in any of the available processes and completing them efficiently. All the documentation necessary to carry out the process in which you register will be available in the system, thus facilitating your participation and contributing to a more fluid and efficient experience.

Використання засобів штучного інтелекту в інженерії вимог: аналіз можливостей та чат-бот для валідації

This study investigates the processes and means of requirements engineering (RE) of software and complex information systems (SWS). The subject of this study is the instrumental means of SWS RE based on the methods of artificial (computational) intelligence (AI). The goal is to improve the accuracy and efficiency of CCD requirements development processes using AI tools by providing better communications between business teams and technical teams and automating complex requirements collection and documentation processes. The tasks are as follows: to analyze the principles and means of integrating AI tools into requirements engineering processes, the development and verification of which is a critical stage in the development of SWS; to determine the problems of using traditional SWS RE methods and perform their comparative analysis with AI-based methods; and to develop a chatbot architecture for requirements validation and identify characteristics of RE processes that are improved through its use. The results. The results of this study demonstrate that AI tools can significantly improve the accuracy, timeliness, and efficiency of requirements development processes and project team communication. An architecture and software solution for an intelligent chatbot for requirements validation is proposed, and the benefits and limitations of its application are discussed. Directions for further development and research regarding the end-to-end implementation of AI tools in IP processes have been developed.

Data Skills for Everyone! (?) – An Approach to Assessing the Integration of Data Literacy and Data Science Competencies in Higher Education

The proficient handling of data can undoubtedly be regarded as a key skill for the future. However, the need for data competencies is not limited to traditional professions in the information technology environment but is rather necessary across industries and work fields. Consequently, there is a call to integrate such Data Literacy and Data Science competencies into higher education teaching across the breadth of study programs. This study, descriptive in nature, sheds light for the first time on the status quo of this integration. For this purpose, a “Data Science Dictionary” has been developed, that structurally maps a corresponding curriculum of the German Informatics Society (GI). Using quantitative content analysis, more than 13,950 distinct modules from three German study programs (Business Administration, Business & Information Systems Engineering, Computer Science) at two different types of universities are examined. As a result of this comparative study, concise “teaching portfolios” are compared between disciplines, whereby the prevalence, proportion, and depth of the competencies integrated into the study programs become transparent. Thus, this approach can provide a basis for discourse on the future integration of data competencies into, e.g., business study curricula; furthermore, it can track the resulting progress in a longitudinal study.

Data-Centric Artificial Intelligence

AbstractData-centric artificial intelligence (data-centric AI) represents an emerging paradigm that emphasizes the importance of enhancing data systematically and at scale to build effective and efficient AI-based systems. The novel paradigm complements recent model-centric AI, which focuses on improving the performance of AI-based systems based on changes in the model using a fixed set of data. The objective of this article is to introduce practitioners and researchers from the field of Business and Information Systems Engineering (BISE) to data-centric AI. The paper defines relevant terms, provides key characteristics to contrast the paradigm of data-centric AI with the model-centric one, and introduces a framework to illustrate the different dimensions of data-centric AI. In addition, an overview of available tools for data-centric AI is presented and this novel paradigm is differenciated from related concepts. Finally, the paper discusses the longer-term implications of data-centric AI for the BISE community.

Integrate between information systems engineering and software engineering theories for successful quality engineering measurement of software: Valid instrument pre-results

An extensive number of instruments and systems assessment tools are weak and not good enough in the appraisal of systems’ quality engineer success measurement. Thus, the comprehension of systems’ success is very serious. One of the purposes of this research topic is to develop a successful, novel, validated instrument for measuring system quality success based on the integration between theories of information systems (Seddon and DeLone & McLean) and software engineering theory (ISO 25010). To ensure the quality of the instrument before use, eight academic experts have validated. The reason for expanding the number of experts to eight is to accurately build and evaluate the instrument because this instrument is the first one erring. After expert validation done successfully, researchers started the process of instrument pre-test. Pre-test verification and validation results done by test the instrument of 74 users. The results of the statistical testing were perfect. The Composite reliability proposed value is 0.7, The average variance extracted value is 0.5. Cronbach’s alpha is higher than 0.7. The value of Spearman’s reliable rhea is >0.6. Results approved that this instrument is strong and perfect to be used as a valid tool for system success measurement.

Research on continuous authentication using dynamic biometrics during information terminal operation

Cyberattacks and cybercrime have increased along with digitisation, causing financial damage and putting lives at risk. It‘s difficult to stop criminals attempting attacks, but more can be done to thwart these efforts. Measures such as 2FA (two factor authentication) aren‘t foolproof. At the Department of Information and Electronic Systems Engineering, Daiichi Institute of Technology, Japan, researchers are conducting research on continuous authentication. They are developing a method by which the identity of a user can be continuously authenticated in order to improve security measures and reduce incidences of fraud, cyberattacks and cybercrime. Professor Takeshi Yamada leads the team, bringing his research background in physics, biometrics, information theory and Artificial Intelligence (AI) to overcoming the limitations of current user authentication systems. Even with continuous authentication, there are challenges to overcome such as interruptions caused by regular requests for ID and password authentication and what is known as ‘leakage’, whereby the leakage of IDs and passwords can enable unauthorised users to freely operate systems. These challenges led the team to the idea of continuous authentication by biometrics. The researchers decided to focus on continuous authentication using behavioural features, which includes handwriting, voiceprint and gait, and, for computer and smartphone security, authentication using features obtained from keyboard, mouse and touch operations.

Information Systems and Software Engineering: The Case for Convergence

Information Systems and Software Engineering: The Case for Convergence

Uncovering Patterns Beneath the Surface: A Glimpse into the Applications of Algebraic Topology

This paper explores the significant impact of algebraic topology on diverse real-world applications. Starting with an introduction to the historical development and essence of algebraic topology, it delves into its applications in neuroscience, physics, biology, engineering, data analysis, and Geographic Information Systems (GIS). Remarkable applications incorporate the analysis of neural networks, quantum mechanics, materials science, and disaster management, showcasing its boundless significance. Despite computational challenges, this study outlines prospects, emphasizing the requirement for proficient algorithms, noise robustness, multi-scale analysis, machine learning integration, user-friendly tools, and interdisciplinary collaborations. In essence, algebraic topology provides a transformative lens for uncovering stowed-away topological structures in complex data, offering solutions to perplexing problems in science, engineering, and society, with vast potential for future exploration and innovation.

Application of Complex Polytopic Fuzzy Information Systems in Knowledge Engineering: Decision Support for COVID-19 Vaccine Selection

Application of Complex Polytopic Fuzzy Information Systems in Knowledge Engineering: Decision Support for COVID-19 Vaccine Selection

Perancangan E-Commerce Pada Victory Collection Berbasis Web

Along with developments in technology, companies are increasingly required to use advanced technology as a tool or media to survive and win the competition. The impact on the aspect of competition is the formation of an increasingly strong competition. The purpose of this research is to know how to design sales system at Victory Collection using web system; And to know how to optimize the sales system more effectively and efficiently at Victory Collection; As well as to find out how the solution to increase sales using a manual into a web-based system at Victory Collection. By using Waterfall Process Model method, all the system details that have been running and the system that will be proposed will be arranged and implemented to optimize the promotion and sales of existing products at Victory Collection. The Waterfall Process approach or method is a systematic and sequential systematic development model that starts at the level and progress of the system in all stages such as analysis, design, code, testing, and maintenance. This model covers activities such as engineering and modeling of information systems, needs analysis, design, coding, maintenance, and testing. The design of this information system is limited only to the food and beverage sales system. The results of this system is expected to minimize damage and loss of sales data and ordering goods at Victory Collection; And this system is expected to help facilitate the search and presentation of goods data at Victory Collection; And this system is expected to increase the sales ratio at Victory Collection.

Hernia registry as the first stage of the development of a ‘learning healthcare system'

This paper aims to assess the effectiveness of current approaches to information exchange among key actors in the healthcare system and their impact on healthcare delivery. Specifically, it compares existing approaches to collecting medical data in herniology and explores their potential use in ‘learning healthcare systems'. However, current nosological registries do not fully meet the needs of these systems. One solution is to modify medical information systems to serve as a source of medical data of sufficient quality to supplement existing medical data lakes. Achieving this requires collaboration among clinicians, researchers, medical information system engineers, and data scientists. Establishing legal regulations for the transfer of medical data to scientific and educational organizations is necessary to fully realize the potential of this new type of nosological registry for advancing science and medicine.

A multivocal literature review of decentralized finance: Current knowledge and future research avenues

While decentralized finance (DeFi) has the potential to emulate and, indeed, outperform existing financial systems, it remains a complex phenomenon yet to be extensively researched. To make the most of this potential, its practitioners must gain a rigorous understanding of its intricacies, as must information systems (IS) researchers. Against this background, this study uses a multivocal literature review to capture the state of research in DeFi. Thereby, we (1) present a consolidating definition of DeFi as we (2) analyze, synthesize, and discuss the current state of knowledge in the field of DeFi. We do so while adapting the blockchain research framework proposed by (Risius and Spohrer, Business & Information Systems Engineering 59:385–409, 2017). Furthermore, we (3) identify gaps in the literature and indicate future research directions in DeFi. Even though our findings highlight several shortcomings in DeFi that have prevented its widespread adoption, our literature review shows a large consensus on DeFi’s many promising features and potential to complement the traditional financial system. To that end, this paper is presented to encourage further research to mitigate the current risks of DeFi, the payoff of which will be an enriched financial ecosystem.

Specificities of Engineering of Training Information Systems With Virtual Electronic Tutoring Devices

In the study of engineering disciplines, special attention is paid to students’ participation in conducting scientific experiments. But not all experiments can be implemented in physical laboratories due to the high cost and great complexity. In such cases, information technologies provide an opportunity to create virtual learning systems, a kind of which is cognitive training information systems, including virtual tutoring devices. The methodological basis for researching the components of virtual tutoring devices and training informational system as a whole was the complex application of mutually complementary approaches and methods, the main of which were methods of decomposition, aggregation, structural and cognitive analysis. One of the most significant shortcomings of existing training information systems is their low didactic efficiency, therefore, the purpose of this article is to create virtual electronic training devices as part of cognitive learning systems which functioning algorithms take into account the education process participant’s personal qualities and thereby provide the opportunity of using a student-oriented approach in education. The article presents schematic solutions for the engineering of training information systems, which include virtual models of precision power systems and precision amplification systems. By building powerful power supply systems, it was possible to fully compensate the instability of the output voltage when the load current changes up to 50 A. Solutions were also proposed to create broadband amplifiers with a harmonic coefficient of 0.003%. The work proposes schematic solutions for virtual electronic training devices that can provide students with nodes of various complexities in engineering. The work presents methods for increasing the didactic efficacy of the use of training information systems.

Methodical approaches to standardization of data acquisition, storage and analysis in management of geotechnical systems

The authors review the existing data logging sources in management of geotechnical systems in different functioning periods and point at the relevance of new tools for safe and efficient solid mineral mining based on the methods of predictive analytics. In modern conditions, the introduction of data acquisition and processing facilities toward advancement of the predictive analytics techniques is meant for the on-going commercial operations after approval of their economic efficiency. As a consequence, companies operate for many years without collecting and storing valuable data on geotechnical systems. Moreover, the versatility of data acquisition/processing program suppliers makes integration of the programs impossible. Considering the existing instructional approaches to the behavior assessment of a geotechnical system, prediction of its stable functioning scenarios, analysis of its malfunction causes and to the introduction of corrective effects, it is required to enhance accuracy of predictive modeling by means of improving quality of data on the geotechnical system and allied facilities. The article offers the review of international data acquisition standards and open interfaces for introduction and control of information accumulation and storage systems in the mining industry. The classification of geotechnical system information sources is proposed and used as the framework for the methods of aggregation, processing and conversion of information in data banks of a mining company, as well as for the quantitative assessment of influence exerted by every physical object of a geotechnical system, personnel and environmental parameters on the process flow efficiency. The introduction of the proposed classification enables foreseeing sequences of introduction of the equipment and tools to acquire and process the required volume of data at the mine project stage, and allows machine learningbased study into causes of incidents, accidents and induced disasters at the stage of mine operation, alongside with development of preventive measures at hazardous production facilities in mineral mining. The routes of developing standards for the science-based and adjusted approach to engineering information systems for the mining industry are identified.The study was supported by the Russian Science Foundation, Grant No. 22-17-00142.

Guest Editorial: WWWJ Special Issue of the 22th International Conference on Web Information Systems Engineering (WISE 2021)

Guest Editorial: WWWJ Special Issue of the 22th International Conference on Web Information Systems Engineering (WISE 2021)

Pengembangan Sistem Informasi E-Recruitment Untuk Seleksi Penerimaan Karyawan Baru Berbasis Web

Technological developments are increasingly rapid, companies need skilled workers so that they can bring companies to develop and compete with technological developments, aspects of employee recruitment are very influential on the progress of the company, recruitment processes that are not in accordance with company needs can hinder company development as in the process of recruiting prospective employees who have to go directly to the company address or send via post and email, this takes a lot of time, lots of piles of unused job applications and creates spam and takes a long time to sort through. Based on this, the researcher proposes an e-Recruitment Information system innovation to assist the recruitment process, including the process of inputting and searching for new employee recruitment data. The research design resulted in a software engineering of Employee E-Recruitment Information systems at PT. XYZ which makes it easier for the human resources department to accept new employees. In addition, the Employee E-Recruitment Information System at PT. The new XYZ can speed up the time in the process of recruiting, inputting and searching for new employee candidate data.

JCISE Editorial – August 2022

JCISE Editorial – August 2022

We need a broader debate on the sustainability of blockchain

Alexander Rieger is a postdoctoral researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg. His research interests include innovative digital technologies such as blockchain, decentralized digital identities, and artificial intelligence. Alex leads the scientific advisory team for the FLORA blockchain project of Germany's Federal Office for Migration and Refugees and acts as advisor to the European Blockchain Partnership and various public and private sector partners in Germany and Luxembourg. Tamara Roth is a postdoctoral researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg. Her research interests include the interplay of innovative technologies such as blockchain and decentralized digital identities with sociocultural and socioethical constructs in public administration and healthcare. Moreover, she investigates technology adoption and implications of technologies for sustainable development from a psychological and neurobiological perspective. Johannes Sedlmeir is a researcher on information systems at the FIM Research Center, University of Bayreuth. In his research, he focuses on the energy consumption and performance benchmarking of different blockchains, the application of cryptographic methods such as zero-knowledge proofs for scalable and privacy-oriented blockchain solutions in different sectors, and decentralized digital identities. He received his M.Sc. in theoretical and mathematical physics. Gilbert Fridgen is professor and PayPal-FNR PEARL chair in digital financial services at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg. In his research, he analyzes the transformative effects of digital technologies on individual organizations and on the relationship between organizations. He addresses potentially disruptive technologies like blockchain, decentralized digital identities, artificial intelligence, or the Internet of Things. His research involves information systems engineering and IT strategy and (risk) management, as well as regulatory compliance. In his projects and partnerships, he collaborates with partners in financial services, energy, mobility, manufacturing, and consulting, as well as with public bodies and governments.

Conceptual model visual simulation and the inductive learning of missing domain constraints

Conceptual modeling plays a fundamental role in information systems engineering, and in data and systems interoperability. To play their role as instruments for domain modeling, conceptual models must contain the exact set of constraints that represent the worldview of the relevant domain stakeholders. However, as empirical results show, conceptual modelers are subject to cognitive limitations and biases and, hence, in practice, they systematically produce models that fall short in that respect. Moreover, automating the process of formally assessing conceptual models in this sense (i.e., model validation) is notoriously hard, mainly because the intended worldview at hand lies in the mind of these stakeholders. In this paper, we provide a novel approach to model validation and automated constraint learning that combines, on one hand, Model Finding via the visual simulation of that model’s valid instances and, on the other hand, Inductive Logic Programming techniques. In our approach, we properly channel the results produced by the application of a visual model finding technique as input to a learning process. We then show how the approach is able to support the modeler in identifying missing constraints from the original model. The approach is validated against a catalog of empirically-elicited conceptual modeling anti-patterns. As we show here, the approach is able to support the automated learning of constraints that are needed to rectify a number of relevant anti-patterns in this catalog.