The Semantic Web MIDI Tape

2018

Over recent decades, the natural sciences have moved from formulating hypotheses through the observation of phenomena to generating them automatically through the analysis of large cross-disciplinary datasets, collected and maintained within large collaborative projects. Recently, it was suggested that musicology should embrace the same paradigm shift, and move to a more collaborative and data-oriented culture. In this paper, we describe the MIDI Linked Data Cloud, an RDF graph of 10 billion MIDI statements linked to contextual metadata. We show examples of its potential application for digital libraries for musicology, and we argue that the use of Linked Data for integrating symbolic music notations and contextual metadata constitutes technical foundations for Web-scale musicology projects.

Lecture Notes in Computer Science, 2017

The study of music is highly interdisciplinary, and thus requires the combination of datasets from multiple musical domains, such as catalog metadata (authors, song titles, dates), industrial records (labels, producers, sales), and music notation (scores). While today an abundance of music metadata exists on the Linked Open Data cloud, linked datasets containing interoperable symbolic descriptions of music itself, i.e. music notation with note and instrument level information, are scarce. In this paper, we describe the MIDI Linked Data Cloud dataset, which represents multiple collections of digital music in the MIDI standard format as Linked Data using the novel midi2rdf algorithm. At the time of writing, our proposed dataset comprises 10,215,557,355 triples of 308,443 interconnected MIDI files, and provides Web-compatible descriptions of their MIDI events. We provide a comprehensive description of the dataset, and reflect on its applications for research in the Semantic Web and Music Information Retrieval communities.

Journal of New Music Research, 2010

The promise of the Semantic Web is to democratise access to data, allowing anyone to make use of and contribute back to the global store of knowledge. Within the scope of the OMRAS2 Music Information Retrieval project, we have made use of and contributed to Semantic Web technologies for purposes ranging from the publication of music recording metadata to the online dissemination of results from audio analysis algorithms. In this paper, we assess the extent to which our tools and frameworks can assist in research and facilitate distributed work among audio and music researchers, and enumerate and motivate further steps to improve collaborative efforts in music informatics using the Semantic Web. To this end, we review some of the tools developed by the OMRAS2 project, examine the extent to which our work reflects the Semantic Web paradigm, and discuss some of the remaining work needed to fulfil the promise of online music informatics research.

We describe the process of collecting, organising and publishing a large set of music similarity features produced by the SoundBite [10] playlist generator tool. These data can be a valuable asset in the development and evaluation of new Music Information Retrieval algorithms. They can also be used in Web-based music search and retrieval applications. For this reason, we make a database of features available on the Semantic Web via a SPARQL end-point, which can be used in Linked Data services. We provide examples of using the data in a research tool, as well as in a simple web application which responds to audio queries and finds a set of similar tracks in our database.

Semantic Web technologies such as RDF, OWL, and SPARQL can be successfully used to bridge complementary musicological information. In this paper, we describe, compare, and evaluate the datasets and workflows used to create two such aggregator projects: In Collaboration with In Concert, and JazzCats, both of which bring together a cluster of smaller projects containing concert and performance metadata.

2015

[email protected], [email protected] 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.

2008

In this paper, we describe current efforts towards interlinking music-related datasets on the Web. We first explain some initial interlinking experiences, and the poor results obtained by taking a naïve approach. We then detail a particular interlinking algorithm, taking into account both the similarities of web resources and of their neighbours. We detail the application of this algorithm in two contexts: to link a Creative Commons music dataset to an editorial one, and to link a personal music collection to corresponding web identifiers. The latter provides a user with personally meaningful entry points for exploring the web of data, and we conclude by describing some concrete tools built to generate and use such links.

2008

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.

2017

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.

Communications in computer and information science, 2016

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.