Rhizomer: Interactive semantic knowledge graphs exploration
Rhizomer helps researchers and practitioners explore knowledge graphs available as Semantic Web data by performing the three data analysis tasks: overview, zoom and filter, and details-on-demand. This approach makes it easier for users to get an idea about the overall structure and intricacies of a...
| Autores: | , , |
|---|---|
| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10459.1/84188 |
| Acesso em linha: | https://doi.org/10.1016/j.softx.2022.101235 http://hdl.handle.net/10459.1/84188 |
| Access Level: | acceso abierto |
| Palavra-chave: | Knowledge graph Semantic data Visualization User interface |
| Resumo: | Rhizomer helps researchers and practitioners explore knowledge graphs available as Semantic Web data by performing the three data analysis tasks: overview, zoom and filter, and details-on-demand. This approach makes it easier for users to get an idea about the overall structure and intricacies of a dataset, when compared to existing approaches and even without prior knowledge. Rhizomer is helpful for data reusers, who want to know about the reuse opportunities of a given dataset, and for knowledge graph creators, who can check if the generated data follow their expectations. Rhizomer has been applied in many scenarios, from research and commercial projects to teaching. |
|---|