{"article_number":"318","citation":{"apa":"Sherif, M. A., da Silva, A. A. M., Pestryakova, S., Ahmed, A. F., Niemann, S., &#38; Ngomo, A.-C. N. (2023). IngridKG: A FAIR Knowledge Graph of Graffiti. <i>Scientific Data</i>, <i>10</i>(1), Article 318. <a href=\"https://doi.org/10.1038/s41597-023-02199-8\">https://doi.org/10.1038/s41597-023-02199-8</a>","mla":"Sherif, Mohamed Ahmed, et al. “IngridKG: A FAIR Knowledge Graph of Graffiti.” <i>Scientific Data</i>, vol. 10, no. 1, 318, Springer Science and Business Media LLC, 2023, doi:<a href=\"https://doi.org/10.1038/s41597-023-02199-8\">10.1038/s41597-023-02199-8</a>.","chicago":"Sherif, Mohamed Ahmed, Ana Alexandra Morim da Silva, Svetlana Pestryakova, Abdullah Fathi Ahmed, Sven Niemann, and Axel-Cyrille Ngonga Ngomo. “IngridKG: A FAIR Knowledge Graph of Graffiti.” <i>Scientific Data</i> 10, no. 1 (2023). <a href=\"https://doi.org/10.1038/s41597-023-02199-8\">https://doi.org/10.1038/s41597-023-02199-8</a>.","ama":"Sherif MA, da Silva AAM, Pestryakova S, Ahmed AF, Niemann S, Ngomo A-CN. IngridKG: A FAIR Knowledge Graph of Graffiti. <i>Scientific Data</i>. 2023;10(1). doi:<a href=\"https://doi.org/10.1038/s41597-023-02199-8\">10.1038/s41597-023-02199-8</a>","bibtex":"@article{Sherif_da Silva_Pestryakova_Ahmed_Niemann_Ngomo_2023, title={IngridKG: A FAIR Knowledge Graph of Graffiti}, volume={10}, DOI={<a href=\"https://doi.org/10.1038/s41597-023-02199-8\">10.1038/s41597-023-02199-8</a>}, number={1318}, journal={Scientific Data}, publisher={Springer Science and Business Media LLC}, author={Sherif, Mohamed Ahmed and da Silva, Ana Alexandra Morim and Pestryakova, Svetlana and Ahmed, Abdullah Fathi and Niemann, Sven and Ngomo, Axel-Cyrille Ngonga}, year={2023} }","ieee":"M. A. Sherif, A. A. M. da Silva, S. Pestryakova, A. F. Ahmed, S. Niemann, and A.-C. N. Ngomo, “IngridKG: A FAIR Knowledge Graph of Graffiti,” <i>Scientific Data</i>, vol. 10, no. 1, Art. no. 318, 2023, doi: <a href=\"https://doi.org/10.1038/s41597-023-02199-8\">10.1038/s41597-023-02199-8</a>.","short":"M.A. Sherif, A.A.M. da Silva, S. Pestryakova, A.F. Ahmed, S. Niemann, A.-C.N. Ngomo, Scientific Data 10 (2023)."},"publisher":"Springer Science and Business Media LLC","type":"journal_article","keyword":["Library and Information Sciences","Statistics","Probability and Uncertainty","Computer Science Applications","Education","Information Systems","Statistics and Probability"],"year":"2023","user_id":"6593","_id":"45484","status":"public","publication":"Scientific Data","language":[{"iso":"eng"}],"department":[{"_id":"574"},{"_id":"115"}],"project":[{"_id":"104","name":"INGRID: INGRID: Informationssystem Graffiti in Deutschland","grant_number":"289287267"}],"volume":10,"author":[{"last_name":"Sherif","full_name":"Sherif, Mohamed Ahmed","first_name":"Mohamed Ahmed"},{"full_name":"da Silva, Ana Alexandra Morim","last_name":"da Silva","first_name":"Ana Alexandra Morim"},{"last_name":"Pestryakova","full_name":"Pestryakova, Svetlana","first_name":"Svetlana"},{"full_name":"Ahmed, Abdullah Fathi","last_name":"Ahmed","first_name":"Abdullah Fathi"},{"first_name":"Sven","full_name":"Niemann, Sven","last_name":"Niemann"},{"full_name":"Ngomo, Axel-Cyrille Ngonga","last_name":"Ngomo","first_name":"Axel-Cyrille Ngonga"}],"publication_identifier":{"issn":["2052-4463"]},"doi":"10.1038/s41597-023-02199-8","date_created":"2023-06-06T09:12:39Z","publication_status":"published","abstract":[{"text":"<jats:title>Abstract</jats:title><jats:p>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 (<jats:sc>Ingrid</jats:sc>) closes this gap by dealing with graffiti image collections that have been made available to the project for public use. Within <jats:sc>Ingrid</jats:sc>, the graffiti images are collected, digitized and annotated. With this work, we aim to support the rapid access to a comprehensive data source on <jats:sc>Ingrid</jats:sc> targeted especially by researchers. In particular, we present <jats:sc>Ingrid</jats:sc>KG, an RDF knowledge graph of annotated graffiti, abides by the Linked Data and FAIR principles. We weekly update <jats:sc>Ingrid</jats:sc>KG 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 <jats:sc>Ingrid</jats:sc>KG 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.</jats:p>","lang":"eng"}],"title":"IngridKG: A FAIR Knowledge Graph of Graffiti","date_updated":"2023-06-06T09:17:10Z","intvolume":"        10","issue":"1"}