Has anyone tried ontologies for supply chain management?5 answersOntologies have been used in supply chain management to improve efficiency and knowledge integration. Researchers have conducted surveys to identify existing ontologies in the field and create new ontologies that unify the structural elements of the supply chain. These ontologies aim to model the concepts and semantic relationships between them in supply chain networks. The use of ontologies can enable digital transformation and enhance supply chain resilience. Ontologies have also been applied in product lifecycle management (PLM) to integrate knowledge from different stages and teams, improving data sharing and integration. In the context of food supply chains, ontologies have been proposed to manage traceability and connect products to different stages of the transformation process. Overall, ontologies have been utilized in various aspects of supply chain management to address challenges and improve performance.
How to develop a research discipline classification?4 answersDeveloping a research discipline classification involves several steps. First, researchers can use text-mining approaches to automatically classify research papers based on their similarities in research areas or keywords. Support vector machine training algorithms can be implemented for fast and accurate classification. Additionally, a classification system can be devised to identify research publications in a specific field, allowing for the determination of trends and differences between publication venues. This classification work can lead to further examination of research approaches and methods used in computing education publications. In the field of music research, classification relies on the knowledge of observable or deduced features and an adequate similarity or distance measure. Finally, interactive visualization and classification tools can be developed to explore communities of research in a scientific discipline, providing a holistic view of the field and facilitating the identification of relevant publications.
How are ontologies utilised in requirement engineering?5 answersOntologies are used in requirement engineering to represent and model knowledge in various disciplines, such as computer science and electrical engineering. They provide a formal means of representing system requirements and sensor knowledge in the Internet of Things (IoT). By designing comprehensive ontologies, knowledge can be structured within a domain and used for multiple purposes, from system requirements specifications to modeling knowledge based on data from IoT sensors. Ontologies help in capturing requirements in a formal way, enabling stakeholders to produce more effective and higher quality requirement specifications. They also facilitate knowledge sharing and reuse, as well as reflect multiple viewpoints of stakeholders, by providing a clear, complete, and consistent hierarchical ontology concept and association. Additionally, ontologies can be used to detect incomplete and conflicted requirements, ensure consistency between requirements specifications, and improve communication between stakeholders.
What are the differente types of requirement categorization?5 answersRequirement categorization can be done based on different perspectives and aspects. One approach is to categorize requirements according to their design needs or attributes, which is known as a designer perspective. Another approach is to categorize requirements based on procurement or acquisition needs, which is known as a contractual perspective. Additionally, requirements can be categorized based on stakeholder intent and aspects of concern, such as functional, performance, and safety requirements. In large systems engineering projects, requirements may need to be categorized for various aspects beyond software, including hardware and activities in other disciplines. Furthermore, orthogonal, system-centric categorization methods have been proposed as a potential solution to mitigate problems associated with traditional categorization approaches.
What is the meaning of classification in the context of library?5 answersClassification in the context of library refers to the process of organizing and categorizing information or materials in a systematic manner for easy retrieval and access. It involves creating a structure or system that allows for the efficient organization and management of library resources. Classification helps in the selection, arrangement, and description of library materials, enabling users to locate and browse through relevant resources. It also aids in the identification and differentiation of different types of libraries based on their characteristics and functions. Classification is essential in both physical and digital library environments, ensuring that information is organized, trustworthy, and conforms to standards and regulations. Overall, classification plays a crucial role in library science by facilitating the effective organization, retrieval, and management of information resources.
What is relation between requirements and domain modeling?5 answersRequirements and domain modeling are closely related in software development. Domain modeling involves identifying and representing the entities and relationships within a specific domain. Requirements, on the other hand, define the functionality and behavior expected from a system. Domain modeling helps in understanding the domain-specific concepts and constraints, which in turn helps in eliciting and analyzing requirements effectively. By using domain models, domain experts can identify and specify the requirements more accurately, ensuring that the system meets the stakeholders' needs. Additionally, domain models can be used to validate and verify the requirements, ensuring their consistency and correctness. Therefore, domain modeling plays a crucial role in requirement engineering, providing a foundation for the development of high-quality software systems.