Data protection compliance is critical from a requirements engineering (RE) perspective,
both from a software development lifecycle (SDLC) perspective and regulatory compliance …

Process mining helps infer valuable insights about business processes using event logs,
whereas goal modeling focuses on the representation and analysis of competing goals of …

This paper focuses on the challenges of modeling cyber–physical systems (CPSs) that arise
from the intrinsic heterogeneity, concurrency, and sensitivity to timing of such systems. It …

Machine Learning (ML) provides approaches which use big data to enable algorithms to"
learn", producing outputs which would be difficult to obtain otherwise. Despite the advances …

Both conceptual modeling and machine learning have long been recognized as important
areas of research. With the increasing emphasis on digitizing and processing large amounts …

Business intelligence (BI) offers tremendous potential for business organizations to gain
insights into their day-to-day operations, as well as longer term opportunities and threats …

The User Requirements Notation (URN), standardized by the International
Telecommunication Union in 2008, is used to model and analyze requirements with goals …

We present a model to implement digital twins in sustainable agriculture. Our two-year
research project follows the design science research paradigm, aiming at the joint creation …

In goal-oriented requirements engineering, goal models have been advocated to express
stakeholder objectives and to capture and choose among system requirement candidates. A …

Goal-oriented requirements engineering (GORE) has been introduced as a means of
modeling and understanding the motivations for system requirements. Using models to …