The Big Data landscape poses challenges in managing diverse data formats, requiring efficient storage and processing for high-quality analysis. Effective metadata management is crucial for organizing, accessing, and reusing data within these data ecosystems. Existing metadata vocabularies and standard, however, do not adequately accommodate aggregated or summary data. This paper introduces a metadata model to support semantic annotation and profiling of multidimensional data. Defined as an RDF vocabulary, the model provides a flexible and extensible graph representation for metadata at source and attribute levels, aligning dimensions and measures to a reference Knowledge Graph and summarizing value distributions in profiles. An evaluation of the execution time for profile generation is also proposed, across data sources with different cardinalities.
@article{arxiv.2503.15951,
title = {A metadata model for profiling multidimensional sources in data ecosystems},
author = {Claudia Diamantini and Alessandro Mele and Domenico Potena and Cristina Rossetti and Emanuele Storti},
journal= {arXiv preprint arXiv:2503.15951},
year = {2025}
}