TY - GEN
T1 - Towards a Comprehensive Ontology for Requirements Engineering for AI-Powered Systems
AU - Sadovski, Eran
AU - Aviv, Itzhak
AU - Hadar, Irit
N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Context and motivation: Artificial intelligence (AI) provides computer systems problem-solving and decision-making features mimicking human behavior. As AI becomes widely adopted, AI-powered systems become increasingly ubiquitous. Requirements engineering (RE) is fundamental to system development, including AI-powered systems, which provide novel RE challenges. Question/problem: Developing means for addressing these challenges, which include increased need and importance of specifying and addressing social requirements, (e.g., responsibility, ethics, and trustworthiness); achieving a comprehensive understanding of all RE aspects, given the substantial growth in the diversity and complexity of requirements and the emergence of new and often contradictory ones; and, employing relevant methods and techniques that are suited for addressing these challenges. Principal ideas/results: We propose an RE4AI ontology as a first step toward addressing the above challenges. The development of the ontology was based on a meta-synthesis of relevant publications for identifying recurring themes and patterns, resulting in a set of themes categorized into RE stages, topics, stakeholders’ roles, and constraints that formed the developed ontology. Contribution: The ontology provides a systematic and unambiguous representation of the accumulated RE knowledge about the system, including requirement themes, relationships between requirements, constraints, and stakeholders needed in the RE process. This ontology provides the basis for a complete AI RE methodology (AI-REM) framework that will incorporate methods to develop and manage AI-powered system requirements.
AB - Context and motivation: Artificial intelligence (AI) provides computer systems problem-solving and decision-making features mimicking human behavior. As AI becomes widely adopted, AI-powered systems become increasingly ubiquitous. Requirements engineering (RE) is fundamental to system development, including AI-powered systems, which provide novel RE challenges. Question/problem: Developing means for addressing these challenges, which include increased need and importance of specifying and addressing social requirements, (e.g., responsibility, ethics, and trustworthiness); achieving a comprehensive understanding of all RE aspects, given the substantial growth in the diversity and complexity of requirements and the emergence of new and often contradictory ones; and, employing relevant methods and techniques that are suited for addressing these challenges. Principal ideas/results: We propose an RE4AI ontology as a first step toward addressing the above challenges. The development of the ontology was based on a meta-synthesis of relevant publications for identifying recurring themes and patterns, resulting in a set of themes categorized into RE stages, topics, stakeholders’ roles, and constraints that formed the developed ontology. Contribution: The ontology provides a systematic and unambiguous representation of the accumulated RE knowledge about the system, including requirement themes, relationships between requirements, constraints, and stakeholders needed in the RE process. This ontology provides the basis for a complete AI RE methodology (AI-REM) framework that will incorporate methods to develop and manage AI-powered system requirements.
KW - Artificial Intelligence
KW - FR
KW - Machine Learning
KW - NFR
KW - Ontology
KW - RE4AI
KW - Requirement Engineering
UR - http://www.scopus.com/inward/record.url?scp=85190714342&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-031-57327-9_14
DO - https://doi.org/10.1007/978-3-031-57327-9_14
M3 - Conference contribution
SN - 9783031573262
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 219
EP - 230
BT - Requirements Engineering
A2 - Mendez, Daniel
A2 - Moreira, Ana
PB - Springer Science and Business Media Deutschland GmbH
T2 - 30th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2024
Y2 - 8 April 2024 through 12 April 2024
ER -