2025/11/26 by Elisa Quintarelli, Fabio A. Schreiber, Quintarelli, Elisa +7
Business, Management and Accounting · Decision Sciences · Social Sciences · #Big Data and Business Intelligence #Data Quality and Management #Databases (cs.DB) #E.0 #Ethics and Social Impacts of AI #FOS: Computer and information sciences #H.2
paper · pdf · doi:10.48550/arxiv.2511.21942
openalex publication_date 2025/11/26 · openalex created_date 2025/12/03 · openalex updated_date 2026/07/28
Ethics has become a major concern to the information management community, as both algorithms and data should satisfy ethical rules that guarantee not to generate dishonourable behaviours when they are used. However, these ethical rules may vary according to the situation-the context-in which the application programs must work. In this paper, after reviewing the basic ethical concepts and their possible influence on data management, we propose a bipartite conceptual model, composed of the Context Dimensions Tree (CDT), which describes the possible contexts, and the Ethical Requirements Tree (ERT), representing the ethical rules necessary to tailor and preprocess the datasets that should be fed to Data Analysis and Learning Systems in each possible context. We provide some examples and suggestions on how these conceptual tools can be used.