The HaMSE Ontology: Using Semantic Technologies to support Music Representation Interoperability and Musicological Analysis
Poltronieri, Andrea, Gangemi, Aldo
–arXiv.org Artificial Intelligence
The use of Semantic Technologies - in particular the Semantic Web - has revealed to be a great tool for describing the cultural heritage domain and artistic practices. However, the panorama of ontologies for musicological applications seems to be limited and restricted to specific applications. In this research, we propose HaMSE, an ontology capable of describing musical features that can assist musicological research. More specifically, HaMSE proposes to address issues that have been affecting musicological research for decades: the representation of music and the relationship between quantitative and qualitative data. To do this, HaMSE allows the alignment between different music representation systems and describes a set of musicological features that can allow the music analysis at different granularity levels.
arXiv.org Artificial Intelligence
Feb-11-2022
- Country:
- Europe
- Austria > Vienna (0.14)
- Germany (0.04)
- Italy > Emilia-Romagna
- Metropolitan City of Bologna > Bologna (0.04)
- Portugal > Braga
- Braga (0.04)
- Spain > Andalusia
- Málaga Province > Málaga (0.04)
- United Kingdom > England
- Greater London > London (0.04)
- North America
- Puerto Rico > Peñuelas
- Peñuelas (0.04)
- United States > New York
- New York County > New York City (0.04)
- Puerto Rico > Peñuelas
- Europe
- Genre:
- Research Report (0.64)
- Industry:
- Leisure & Entertainment (1.00)
- Media > Music (1.00)
- Technology: