One of the most pressing issues facing astronomy today is the growing threat of light
pollution. Light pollution affects not only astronomical observations but also sustainability in …

Through knowledge extraction from data with various methods, Data Science (DS) allows
organizations to achieve improvements in performance. The execution of these projects is …

As organizations face the challenges of processing exponentially growing data volumes,
their reliance on analytics to unlock value from this data has intensified. However, the …

In the paper at hand, a structured literature review was conducted to provide an overview of
the components of value creation from Data Science applications. For this purpose, the …

The significant increase in the amount of generated data provides potential for organizations
to improve performance. Accordingly, Data Science (DS), which encompasses the methods …

Various semantic technologies such as ontologies, machine learning, or artificial
intelligence-based are being used today with data science for the purpose of explaining the …

With the ongoing digitalization of complex systems, for example in manufacturing, domain
experts' detailed understanding of datasets is pivotal to effectively training machine learning …

The role of data as a valuable resource has caused significant transformations in various
areas of life. Data Science (DS) aims to extract knowledge from data and thus, has gained …

The effective implementation of data science projects (DSP) relies heavily on risk
management, where understanding and managing potential risks are important factors …

Data Science (DS) has gained increased relevance due to the potential to extract useful
insights from data. Quite commonly, this involves the utilization of Machine Learning (ML) …