Tag: SPARQL

wikipedia_id:2574343:en;wikidata_id:Q54871:en

SPARQL for music: when melodies meet ontology

SPARQL for music: when melodies meet ontology

Introduction: Developed in the context of the EU H2020 Polifonia project, the investigation deals with the potentialities of SPARQL Anything to
to extract musical features, both at metadata and symbolic levels, from MusicXML files. The paper captures the procedure that has applied by starting from an overview about the application of ontologies to music, as well as of the so- called ‘façade-based’ approach to knowledge graphs, which is at the core of the SPARQL Anything software. Then, it moves to an illustration of the passages involved (i.e., melody extraction, N-grams extraction, N-grams analysis and exploitation
of the Music Notation Ontology). Finally, it provides some considerations regarding the result of the experiment in terms of effectiveness of the queries’ performance. In conclusion, the authors highlight how further studies in the field may cast an increasingly brighter light on the application of semantic-oriented methods and techniques to computational musicology.
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Programmable Corpora: Introducing DraCor, an Infrastructure for the Research on European Drama

Programmable Corpora: Introducing DraCor, an Infrastructure for the Research on European Drama

Introduction: The DraCor ecosystem encourages various approaches to the browsing and consultation of the data collected in the corpora, like those detailed in the Tools section: the Shiny DraCor app (https://shiny.dracor.org/), along with the SPARQL queries and the Easy Linavis interfaces (https://dracor.org/sparql and https://ezlinavis.dracor.org/ respectively). The project, thus, aims at creating a suitable digital environment for the development of an innovative way to approach literary corpora, potentially open to collaborations and interactions with other initiatives thanks to its ontology and Linked Open data-based nature.
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Europeana and the FAIR principles for research data | Europeana Pro

Europeana and the FAIR principles for research data | Europeana Pro

Introduction: The FAIR Data Principles (Findable, Accesible, Interoperable, Reusable) aim to make clear the need to improve the infrastructure for reuse of scholarly data. The FAIR Data Principles emphasize the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals, key activities for Digital Humanities research. The post below summarizes how Europeana’s principles (Usable, Mutual, Reliable) align with the FAIR Data ones, enhancing the findability, accessibility, interoperability, and reuse of digitised cultural heritage.

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