IngridKG: A FAIR Knowledge Graph of Graffiti
Abstract Graffiti is an urban phenomenon that is increasingly attracting the interest of the sciences. To the best of our knowledge, no suitable data corpora are available for systematic research until now. The Information System Graffiti in Germany project (Ingrid) closes this gap by dealing with g...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-05-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02199-8 |
| _version_ | 1797818211629006848 |
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| author | Mohamed Ahmed Sherif Ana Alexandra Morim da Silva Svetlana Pestryakova Abdullah Fathi Ahmed Sven Niemann Axel-Cyrille Ngonga Ngomo |
| author_facet | Mohamed Ahmed Sherif Ana Alexandra Morim da Silva Svetlana Pestryakova Abdullah Fathi Ahmed Sven Niemann Axel-Cyrille Ngonga Ngomo |
| author_sort | Mohamed Ahmed Sherif |
| collection | DOAJ |
| description | Abstract Graffiti is an urban phenomenon that is increasingly attracting the interest of the sciences. To the best of our knowledge, no suitable data corpora are available for systematic research until now. The Information System Graffiti in Germany project (Ingrid) closes this gap by dealing with graffiti image collections that have been made available to the project for public use. Within Ingrid, the graffiti images are collected, digitized and annotated. With this work, we aim to support the rapid access to a comprehensive data source on Ingrid targeted especially by researchers. In particular, we present IngridKG, an RDF knowledge graph of annotated graffiti, abides by the Linked Data and FAIR principles. We weekly update IngridKG by augmenting the new annotated graffiti to our knowledge graph. Our generation pipeline applies RDF data conversion, link discovery and data fusion approaches to the original data. The current version of IngridKG contains 460,640,154 triples and is linked to 3 other knowledge graphs by over 200,000 links. In our use case studies, we demonstrate the usefulness of our knowledge graph for different applications. |
| first_indexed | 2024-03-13T09:04:47Z |
| format | Article |
| id | doaj.art-6dcba9188dd948f586f80d59ad781468 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-03-13T09:04:47Z |
| publishDate | 2023-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-6dcba9188dd948f586f80d59ad7814682023-05-28T11:08:04ZengNature PortfolioScientific Data2052-44632023-05-0110111210.1038/s41597-023-02199-8IngridKG: A FAIR Knowledge Graph of GraffitiMohamed Ahmed Sherif0Ana Alexandra Morim da Silva1Svetlana Pestryakova2Abdullah Fathi Ahmed3Sven Niemann4Axel-Cyrille Ngonga Ngomo5DICE Research Group, Department of Computer Science, Paderborn UniversityDICE Research Group, Department of Computer Science, Paderborn UniversityDICE Research Group, Department of Computer Science, Paderborn UniversityDICE Research Group, Department of Computer Science, Paderborn UniversityInstitute for German Language and Comparative Literature, Paderborn UniversityDICE Research Group, Department of Computer Science, Paderborn UniversityAbstract Graffiti is an urban phenomenon that is increasingly attracting the interest of the sciences. To the best of our knowledge, no suitable data corpora are available for systematic research until now. The Information System Graffiti in Germany project (Ingrid) closes this gap by dealing with graffiti image collections that have been made available to the project for public use. Within Ingrid, the graffiti images are collected, digitized and annotated. With this work, we aim to support the rapid access to a comprehensive data source on Ingrid targeted especially by researchers. In particular, we present IngridKG, an RDF knowledge graph of annotated graffiti, abides by the Linked Data and FAIR principles. We weekly update IngridKG by augmenting the new annotated graffiti to our knowledge graph. Our generation pipeline applies RDF data conversion, link discovery and data fusion approaches to the original data. The current version of IngridKG contains 460,640,154 triples and is linked to 3 other knowledge graphs by over 200,000 links. In our use case studies, we demonstrate the usefulness of our knowledge graph for different applications.https://doi.org/10.1038/s41597-023-02199-8 |
| spellingShingle | Mohamed Ahmed Sherif Ana Alexandra Morim da Silva Svetlana Pestryakova Abdullah Fathi Ahmed Sven Niemann Axel-Cyrille Ngonga Ngomo IngridKG: A FAIR Knowledge Graph of Graffiti Scientific Data |
| title | IngridKG: A FAIR Knowledge Graph of Graffiti |
| title_full | IngridKG: A FAIR Knowledge Graph of Graffiti |
| title_fullStr | IngridKG: A FAIR Knowledge Graph of Graffiti |
| title_full_unstemmed | IngridKG: A FAIR Knowledge Graph of Graffiti |
| title_short | IngridKG: A FAIR Knowledge Graph of Graffiti |
| title_sort | ingridkg a fair knowledge graph of graffiti |
| url | https://doi.org/10.1038/s41597-023-02199-8 |
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