• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.99-109
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• 2021

In recent machine learning studies, in order to consider the quality and completeness of data, derivation of non-functional requirements for data has been proposed from the viewpoint of requirements engineering. In particular, requirements engineers have defined data requirements in machine learning. In this study, data requirements were derived at the data acquisition (DAQ) stage, where data is collected and stored before data preprocessing. Through this, it is possible to express the requirements of all data required in the existing DAQ system, the presence of tasks (functions) satisfying them, and the relationship between the requirements and functions. In addition, it is possible to elicit requirements and to define the relationship, so that a software design document can be produced, and a systematic approach and direction can be established in terms of software design and maintenance. This research using existing DAQ system cases, scenarios and use cases for requirements engineering approach are created, and data requirements for each case are extracted based on them, and the relationship between requirements, functions, and goals is illustrated through goal modeling. Through the research results, it was possible to extract the non-functional requirements of the system, especially the data requirements, from the DAQ system using requirements engineering.

• Journal of Information Processing Systems
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• v.6 no.3
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• pp.385-402
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• 2010

Most of the data warehouse (DW) requirements engineering approaches have not distinguished the early requirements engineering phase from the late requirements engineering phase. There are very few approaches seen in the literature that explicitly model the early & late requirements for a DW. In this paper, we propose an AGDI (Agent-Goal-Decision-Information) model to support the early and late requirements for the development of DWs. Here, the notion of agent refers to the stakeholders of the organization and the dependency among agents refers to the dependencies among stakeholders for fulfilling their organizational goals. The proposed AGDI model also supports three interrelated modeling activities namely, organization modeling, decision modeling and information modeling. Here, early requirements are modeled by performing organization modeling and decision modeling activities, whereas late requirements are modeled by performing information modeling activities. The proposed approach has been illustrated to capture the early and late requirements for the development of a university data warehouse exemplifying our model's ability of supporting its decisional goals by providing decisional information.

• International Journal of Knowledge Content Development & Technology
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• v.10 no.1
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• pp.7-20
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• 2020

For research data to be shared without legal, financial and technical barriers in the Open Science era, data repositories must have the functional requirements asked by DMP and CoreTrustSeal. In order to derive functional requirements for the data repository, this study analyzed the Data Management Plan (DMP) and CoreTrustSeal, the criteria for certification of research data repositories. Deposit, Ethics, License, Discovery, Identification, Reuse, Security, Preservation, Accessibility, Availability, and (Meta) Data Quality, commonly required by DMP and CoreTrustSeal, were derived as functional requirements that should be implemented first in implementing data repositories. Confidentiality, Integrity, Reliability, Archiving, Technical Infrastructure, Documented Storage Procedure, Organizational Infrastructure, (Meta) Data Evaluation, and Policy functions were further derived from CoreTrustSeal. The functional requirements of the data repository derived from this study may be required as a key function when developing the repository. It is also believed that it could be used as a key item to introduce repository functions to researchers for depositing data.

• International Journal of Knowledge Content Development & Technology
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• v.13 no.1
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• pp.75-100
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• 2023

With research data generation on the rise, Institutional Repositories (IR) are one of the tools to manage it. However, the variety of data practices across institutions, domains, communities, etc., often requires dedicated studies in order to identify the research data management (RDM) require- ments and mapping them to IR features to support them. In this study, we investigated the data practices for a few national universities in North Macedonia, including 110 participants from different departments. The methodology we adopted to this end enabled us to derive some of the key RDM requirements for a variety of data-related activities. Finally, we mapped these requirements to 6 features that our participants asked for in an IR solution: (1) create (meta)data and documentation, (2) distribute, share, and promote data, (3) provide access control, (4) store, (5) backup, and (6) archive. This list of IR features could prove useful for any university that has not yet established an IR solution.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.27-37
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• 2020

In this paper, we propose the methodology based on data-driven approach using Natural Language Processing and Machine Learning for classifying requirements into functional requirements and non-functional requirements. Through the analysis of the results of the requirements classification, we have learned that the trained models derived from requirements classification with data-preprocessing and classification algorithm based on the characteristics and information of existing requirements that used term weights based on TF and IDF outperformed the results that used stemming and stop words to classify the requirements into functional and non-functional requirements. This observation also shows that the term weight calculated without removal of the stemming and stop words influenced the results positively. Furthermore, we investigate an optimized method for the study of classifying software requirements into functional and non-functional requirements.

• Journal of the Korea Safety Management & Science
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• v.13 no.4
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• pp.9-16
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• 2011

Modern systems become more complex and the demand for systems safety goes up sharply. Thus, the proper handling of the safety requirements in the systems design is getting greatly increased attention these days. Hazard analysis has been one of the active areas of research in connection with systems safety. In this paper, we study a subject on how the hazard analysis results can be incorporated in the systems design. To this end we set up a goal on how to systematically generate safety requirements that should reflect hazard analysis results and be implemented in the systems design and development. To do so, we first review the process for systems design and suggest the associated Model. Then the process and results of hazard analysis are analyzed and Modeled particularly with emphasis on the safety data. The resulting data Model incorporating both the hazard analysis and system life cycle is used in the generation of safety requirements. Based on the developed data Model, the generation of the requirements, the construction of requirements DB, and the change management later on is demonstrated through the use of a computer-aided software tool.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.112-121
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• 2020

Recently, as the internet usage is increasing, accordingly generated text data is also increasing. Because this text data on the internet includes users' comments, the text data on the Internet can help you get users' opinion more efficiently and effectively. The topic of text mining has been actively studied recently, but it primarily focuses on either the content analysis or various improving techniques mostly for the performance of target mining algorithms. The objective of this study is to propose a novel method of analyzing the user's requirements by utilizing the text-mining technique. To complement the existing survey techniques, this study seeks to present priorities together with efficient extraction of customer requirements from the text data. This study seeks to identify users' requirements, derive the priorities of requirements, and identify the detailed causes of high-priority requirements. The implications of this study are as follows. First, this study tried to overcome the limitations of traditional investigations such as surveys and VOCs through text mining of online text data. Second, decision makers can derive users' requirements and prioritize without having to analyze numerous text data manually. Third, user priorities can be derived on a quantitative basis.

• Journal of Information Science Theory and Practice
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• v.11 no.3
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• pp.79-91
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• 2023

The storage of data documentation for Myanmar pagodas has various issues, and its retrieval method causes problems for users and libraries. This study utilized a mixed-methods approach, combining qualitative and quantitative methods to investigate pagoda data management in Myanmar libraries. The study aims to achieve the following objectives: to study the library collection management of pagodas in Myanmar, to investigate the management of pagoda data in Myanmar libraries, and to identify the pagoda data requirements for metadata development from the library professional perspective. The study findings revealed several challenges facing librarians and library users in accessing and managing Myanmar pagoda data, including limited stocks and retrieval tools, difficulty in accessing all available data online, and a lack of a centralized database or repository for storing and retrieving pagoda data. The study recommends the establishment of metadata criteria for managing a set of pagoda data and improving access to technology to address these challenges.

• Journal of Information Technology Applications and Management
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• v.16 no.4
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• pp.263-283
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• 2009

Although some CASE tools supported conceptual data design, they required for users too much preliminary knowledge to learn how to use and handle them. In addition, in a number of studies on conceptual data design with natural language, they claimed passive participation for users with conforming to messages predefined by CASE tools. As an alternative to these traditional CASE tools, we proposed an ERD formulator for automated data design tool, called ERDF, so that even ordinary users, not necessarily data modeler, are capable of formulating ERD on business requirements by use of ERDF. We, first of all, introduced NSM as the standard methodology. We also designed the structure of ERDF including main controller, input controller, operation controller, regulation controller, schema controller, and output controller. We then defined conceptual domains and basic operations to lay down schema operations as well as sentence rules to handle input sentence in natural language. To get an ERD that is faithful to business requirements, we laid out supplementary design for dialogue and confirmation of soundness and completion.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.163-172
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• 2020

Flight data recorder (FDR) for accident investigation is required to comply with EUROCAE(ED-112) standard so that flight data can be restored when exposed to extreme conditions due to aircraft crash. Since the ED-112 standard defines the general requirements for all aircraft, it is essential to analyze detailed requirements for FDR software to apply appropriate requirements selectively according to the configuration and operation concept of a specific aircraft. In this paper, the software requirements applicable to unmanned aircraft will be analyzed and the FDR software design will be proposed. Also, a software verification method for each requirement will be presented to verify that the implemented software is designed to satisfy all requirements.