Controlled Vocabularies for Music Metadata (original) (raw)
Related papers
Publishing Music Similarity Features on the Semantic Web
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.
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.
Linked Data and You: Bringing Music Research Software into the Semantic Web
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.
Local and global Semantic Networks for the representation of music information
2016
In the field of music informatics, multilayer representation formats are becoming increasingly important, since they enable an integrated and synchronized representation of the various entities that describe a piece of music, from the digital encoding of score symbols to its typographic aspects and audio recordings. Often these formats are based on the eXtensible Markup Language (XML), that allows information embedding, hierarchical structuring and interconnection within a single document. Simultaneously, the advent of the so-called Semantic Web is leading to the transformation of the World Wide Web into an environment where documents are associated with data and metadata. XML is extensively used also in the Semantic Web, since this format supports not only human- but also machine-readable tags. On the one side the Semantic Web aims to create a set of automatically-detectable relationships among data, thus providing users with a number of non-trivial paths to navigate information in...
SEMU: A Semantic Knowledge Management System of Musical Information
Entertainment Computing, 2015
The diverse data types of musical information domain including binary and text-based structures create semantic gaps between the entities of different data formats. This leads to difficulties in analyzing, capturing and managing entities of the domain. In this paper, we present a semantic knowledge management system, called SEMU, to efficiently managing musical information. We propose SEMU ontology to capture information extracted from various data types and sources. In order to extract information from raw data, we use Musical Information Retrieval techniques for audio files and Natural Language Processing techniques for text-based formats. We develop a rule-based solution to enrich the system knowledge base. Later, we provide a web application with seamless integration between SEMU knowledge base and user interface to enable users to benefit from the advantages of the SEMU system.
Zenodo (CERN European Organization for Nuclear Research), 2022
The use of Semantic Technologies-in particular the Semantic Web-has revealed to be a great tool for describing the cultural heritage domain and artistic practices. However, the panorama of ontologies for musicological applications seems to be limited and restricted to specific applications. In this research, we propose HaMSE, an ontology capable of describing musical features that can assist musicological research. More specifically, HaMSE proposes to address issues that have been affecting musicological research for decades: the representation of music and the relationship between quantitative and qualitative data. To do this, HaMSE allows the alignment between different music representation systems and describes a set of musicological features that can allow the music analysis at different granularity levels.
DOREMUS: Doing reusable musical data
2017
This paper introduces DOREMUS-a semantic web project aiming to provide common knowledge models and shared multilingual vocabularies to cultural institutions, publishers, distributors and users in the musical domain. The project develops methods to describe, publish, connect and contextualize music catalogs on the web of data. Our focus is on the description of classical and traditional musical works as well as their interpretations (events).
Orchestrating Music Queries via the Semantic Web
2015
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.