Miguel Ceriani , Fabio Viola , Saša Rudan , Francesco Antoniazzi , Mathieu Barthet , György Fazekas
{"title":"通过音频共享本体实现音频内容提供者的语义集成","authors":"Miguel Ceriani , Fabio Viola , Saša Rudan , Francesco Antoniazzi , Mathieu Barthet , György Fazekas","doi":"10.1016/j.websem.2023.100787","DOIUrl":null,"url":null,"abstract":"<div><p>A broad variety of audio content is available online through an increasing number of repositories and platforms. Resources such as music tracks, recorded sounds or instrument samples may be accessed by users for tasks ranging from customised music listening and exploration, to music making and sound design using existing sounds and samples. However, each online repository offers its own API and represents information through its own data model, making it difficult for applications to exploit the plurality of online audio and music content on the web. A crucial step toward integrating audio repositories in a flexible manner is a shared basis for modelling the data therein. This paper describes and extends the Audio Commons Ontology, a common data model designed to integrate existing repositories in the audio media domain. The ontology is designed with the involvement of users through surveys and requirements analyses, and evaluated in-use, by demonstrating how it supports the integration of four relevant repositories with heterogeneous APIs and data models. While this work proves the concept in the audio domain, our proposed methodology may transfer across a broad range of media integration tasks.</p></div>","PeriodicalId":49951,"journal":{"name":"Journal of Web Semantics","volume":"77 ","pages":"Article 100787"},"PeriodicalIF":2.1000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Semantic integration of audio content providers through the Audio Commons Ontology\",\"authors\":\"Miguel Ceriani , Fabio Viola , Saša Rudan , Francesco Antoniazzi , Mathieu Barthet , György Fazekas\",\"doi\":\"10.1016/j.websem.2023.100787\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A broad variety of audio content is available online through an increasing number of repositories and platforms. Resources such as music tracks, recorded sounds or instrument samples may be accessed by users for tasks ranging from customised music listening and exploration, to music making and sound design using existing sounds and samples. However, each online repository offers its own API and represents information through its own data model, making it difficult for applications to exploit the plurality of online audio and music content on the web. A crucial step toward integrating audio repositories in a flexible manner is a shared basis for modelling the data therein. This paper describes and extends the Audio Commons Ontology, a common data model designed to integrate existing repositories in the audio media domain. The ontology is designed with the involvement of users through surveys and requirements analyses, and evaluated in-use, by demonstrating how it supports the integration of four relevant repositories with heterogeneous APIs and data models. While this work proves the concept in the audio domain, our proposed methodology may transfer across a broad range of media integration tasks.</p></div>\",\"PeriodicalId\":49951,\"journal\":{\"name\":\"Journal of Web Semantics\",\"volume\":\"77 \",\"pages\":\"Article 100787\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Web Semantics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1570826823000161\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Web Semantics","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1570826823000161","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Semantic integration of audio content providers through the Audio Commons Ontology
A broad variety of audio content is available online through an increasing number of repositories and platforms. Resources such as music tracks, recorded sounds or instrument samples may be accessed by users for tasks ranging from customised music listening and exploration, to music making and sound design using existing sounds and samples. However, each online repository offers its own API and represents information through its own data model, making it difficult for applications to exploit the plurality of online audio and music content on the web. A crucial step toward integrating audio repositories in a flexible manner is a shared basis for modelling the data therein. This paper describes and extends the Audio Commons Ontology, a common data model designed to integrate existing repositories in the audio media domain. The ontology is designed with the involvement of users through surveys and requirements analyses, and evaluated in-use, by demonstrating how it supports the integration of four relevant repositories with heterogeneous APIs and data models. While this work proves the concept in the audio domain, our proposed methodology may transfer across a broad range of media integration tasks.
期刊介绍:
The Journal of Web Semantics is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web. These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer interaction and knowledge discovery are of major relevance as well. All aspects of the Semantic Web development are covered. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services. The journal emphasizes the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications.