Publikation: Sailor Shift and the Spread of Oceanus Folk : A Visual Analysis
Dateien
Datum
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
DOI (zitierfähiger Link)
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
This paper presents a visual analytics system developed for the VAST Challenge 2025 Mini-Challenge 1 (MC1). Leveraging a comprehensive knowledge graph, our interactive system analyzes musical influences, collaborations, and genre evolution through the career of artist Sailor Shift and the Oceanus Folk genre. The system integrates network graphs, timelines, and sankey diagrams to facilitate exploration of artist relationships, the temporal spread of Oceanus Folk, and identification of emerging talent. Architecturally, it combines a Neo4j graph database, FastAPI backend, and React frontend, providing a robust platform for data-driven insights tailored to assist journalist Silas Reed.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
LU, Makena, Hafiza Rabail MUSHTAQ, Zeyuan YU, Daniel A. KEIM, Lucas JOOS, Julius RAUSCHER, 2025. Sailor Shift and the Spread of Oceanus Folk : A Visual Analysis. 2025 IEEE Visual Analytics Science and Technology Challenge (VAST Challenge). Vienna, Austria, 3. Nov. 2025. In: 2025 IEEE Visual Analytics Science and Technology Challenge (VAST Challenge). Piscataway, NJ: IEEE, 2025, S. 5-6. ISBN 979-8-3315-9090-1. Verfügbar unter: doi: 10.1109/vast-challenge69463.2025.00007BibTex
@inproceedings{Lu2025-11-03Sailo-76267,
title={Sailor Shift and the Spread of Oceanus Folk : A Visual Analysis},
year={2025},
doi={10.1109/vast-challenge69463.2025.00007},
isbn={979-8-3315-9090-1},
address={Piscataway, NJ},
publisher={IEEE},
booktitle={2025 IEEE Visual Analytics Science and Technology Challenge (VAST Challenge)},
pages={5--6},
author={Lu, Makena and Mushtaq, Hafiza Rabail and Yu, Zeyuan and Keim, Daniel A. and Joos, Lucas and Rauscher, Julius}
}RDF
<rdf:RDF
xmlns:dcterms="http://purl.org/dc/terms/"
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:bibo="http://purl.org/ontology/bibo/"
xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
xmlns:foaf="http://xmlns.com/foaf/0.1/"
xmlns:void="http://rdfs.org/ns/void#"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#" >
<rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/76267">
<dc:contributor>Yu, Zeyuan</dc:contributor>
<foaf:homepage rdf:resource="http://localhost:8080/"/>
<dc:contributor>Keim, Daniel A.</dc:contributor>
<dcterms:title>Sailor Shift and the Spread of Oceanus Folk : A Visual Analysis</dcterms:title>
<dc:creator>Keim, Daniel A.</dc:creator>
<dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2026-02-20T10:10:39Z</dcterms:available>
<dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2026-02-20T10:10:39Z</dc:date>
<dc:language>eng</dc:language>
<dcterms:issued>2025-11-03</dcterms:issued>
<dc:creator>Joos, Lucas</dc:creator>
<dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dc:contributor>Rauscher, Julius</dc:contributor>
<dc:contributor>Lu, Makena</dc:contributor>
<dc:contributor>Joos, Lucas</dc:contributor>
<dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
<dc:creator>Yu, Zeyuan</dc:creator>
<dc:creator>Lu, Makena</dc:creator>
<void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
<dc:contributor>Mushtaq, Hafiza Rabail</dc:contributor>
<dc:creator>Mushtaq, Hafiza Rabail</dc:creator>
<dc:creator>Rauscher, Julius</dc:creator>
<bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/76267"/>
<dcterms:abstract>This paper presents a visual analytics system developed for the VAST Challenge 2025 Mini-Challenge 1 (MC1). Leveraging a comprehensive knowledge graph, our interactive system analyzes musical influences, collaborations, and genre evolution through the career of artist Sailor Shift and the Oceanus Folk genre. The system integrates network graphs, timelines, and sankey diagrams to facilitate exploration of artist relationships, the temporal spread of Oceanus Folk, and identification of emerging talent. Architecturally, it combines a Neo4j graph database, FastAPI backend, and React frontend, providing a robust platform for data-driven insights tailored to assist journalist Silas Reed.</dcterms:abstract>
</rdf:Description>
</rdf:RDF>