Automatic interlinking of music datasets on the semantic web (original) (raw)
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This paper presents MusicWeb, a novel platform for music discovery by linking music artists within a web-based application. Mu-sicWeb provides a browsing experience using connections that are either extra-musical or tangential to music, such as the artists' political a liation or social influence, or intra-musical, such as the artists' main instrument or most favoured musical key. The platform integrates open linked semantic metadata from various Semantic Web, music recommendation and social media data sources. Artists are linked by various commonalities such as style, geographical location, instrumentation, record label as well as more obscure categories, for instance, artists who have received the same award, have shared the same fate, or belonged to the same organisation. These connections are further enhanced by thematic analysis of journal articles, blog posts and content-based similarity measures focussing on high level musical categories.
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We describe our recent achievements in interlinking several music-related data sources on the Semantic Web. In particular, we describe interlinked datasets dealing with Creative Commons content, editorial, encyclopedic, geographic and statistical data, along with queries they can answer and tools using their data. We describe our web services, providing an on-demand access to content-based features linked with such data sources and information pertaining to their creation (including processing steps, applied algorithms, inputs, parameters or associated developers). We also provide a tool allowing such music analysis services to be set up and scripted in a simple way.
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The Semantic Web is an extension of the current Web that attempts to reach a state in the future where everything on the Web will no longer be only machine-readable, but also machine-understandable. Three important technologies for developing the Semantic Web are already in place: Extensible Markup Language (XML), the Resource Description Framework (RDF), and Web Ontology Language (OWL). An ontology language is a formal language used to encode ontologies. An ontology is an explicit specification of a conceptualization. Many disciplines now develop standardized ontologies that domain experts can use to share and annotate information in their fields, and which can be used for reasoning about the objects within a particular domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them. In this work, we develop an ontology of Argentinean music. Despite being highly specific, we illustrate how such an ontology can be expanded and used in applications that carry out complex music related searches. These applications can be embedded later on in electronic devices with some form of wireless networking capability, such as mobile phones, enriching their current functionality.
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A variety of digital data sources-including institutional and formal digital libraries, crowd-sourced community resources, and data feeds provided by media organisations such as the BBC-expose information of musicological interest, describing works, composers, performers, and wider historical and cultural contexts. Aggregated access across such datasets is desirable as these sources provide complementary information on shared real-world entities. Where datasets do not share identifiers, an alignment process is required, but this process is fraught with ambiguity and difficult to automate, whereas manual alignment may be time-consuming and error-prone. We address this problem through the application of a Linked Data model and framework to assist domain experts in this process. Candidate alignment suggestions are generated automatically based on textual and on contextual similarity. The latter is determined according to user-configurable weighted graph traversals. Match decisions confirming or disputing the candidate suggestions are obtained in conjunction with user insight and expertise. These decisions are integrated into the knowledge base, enabling further iterative alignment, and simplifying the creation of unified viewing interfaces. Provenance of the musicologist's judgement is captured and published, supporting scholarly discourse and counter-proposals. We present our implementation and evaluation of this framework, conducting a user study with eight musicologists. We further demonstrate the value of our approach through a case study B David M. Weigl
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Musical data can be analysed, combined, transformed and exploited for diverse purposes. However, despite the proliferation of digital libraries and repositories for music, infrastructures and tools, such uses of musical data remain scarce. As an initial step to help fill this gap, we present a survey of the landscape of musical data on the Web, available as a Linked Open Dataset: the musoW dataset of catalogued musical resources. We present the dataset and the methodology and criteria for its creation and assessment. We map the identified dimensions and parameters to existing Linked Data vocabularies, present insights gained from SPARQL queries, and identify significant relations between resource features. We present a thematic analysis of the original research questions associated with surveyed resources and identify the extent to which the collected resources are Linked Data-ready.
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milossmi@gmail.com, jgalletly@aubg.bg 1st Abstract This paper describes the design and implementation of a Semantic Web application that allows queries and inferences to be made on a music knowledge base using Semantic Web technologies such as RDF, OWL and SPARQL. Additionally, the paper explains how these technologies were blended together to develop the application that illustrates the principles of the Semantic Web.