6 citations · 7 across the 6 of their papers we have counts for
6 papers
Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation -- Internal Processes Perspective
Eduardo Vyhmeister, Bastien Pietropaoli, Alejando Martinez Molina +4
Data valuation and monetisation are emerging as central challenges in data-driven economies, yet no unified framework exists to measure or manage data value across organisational c…
A Framework for Data Valuation and Monetisation
Eduardo Vyhmeister, Bastien Pietropaoli, UdoBub +2
As organisations increasingly recognise data as a strategic resource, they face the challenge of translating informational assets into measurable business value. Existing valuation…
Data Quality Taxonomy for Data Monetization
Eduardo Vyhmeister, Bastien Pietropoli, Andrea Visentin
This chapter presents a comprehensive taxonomy for assessing data quality in the context of data monetisation, developed through a systematic literature review. Organising over one…
Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation -- A Systematic Literature Review
Eduardo Vyhmeister, Bastien Pietropaoli, Alejando Martinez Molina +4
Data valuation and data monetisation are complex subjects but essential to most organisations today. Unfortunately, they still lack standard procedures and frameworks for organisat…
When Industry meets Trustworthy AI: A Systematic Review of AI for Industry 5.0
Eduardo Vyhmeister, Gabriel G. Castane
Industry is at the forefront of adopting new technologies, and the process followed by the adoption has a significant impact on the economy and society. In this work, we focus on a…
Deep Neural Network for Constraint Acquisition through Tailored Loss Function
Eduardo Vyhmeister, Rocio Paez, Gabriel Gonzalez
The significance of learning constraints from data is underscored by its potential applications in real-world problem-solving. While constraints are popular for modeling and solvin…