Pasquale Lisena

DOREMUS: A graph of linked musical works

Three major French cultural institutions—the French National Library (BnF), Radio France and the Philharmonie de Paris—have come together in order to develop shared methods to describe semantically their catalogs of music works and events. This process comprises the construction of knowledge graphs representing the data contained in these catalogs following a novel agreed upon ontology that extends CIDOC-CRM and FRBRoo, the linking of these graphs and their open publication on the web. A number of specialized tools that allow for the reproduction of this process are developed, as well as web applications for easy access and navigation through the data. The paper presents one of the main outcomes of this project—the DOREMUS knowledge graph, consisting of three linked datasets describing classical music works and their associated events (e.g., performances in concerts). This resource fills an important gap between library content description and music metadata. We present the DOREMUS pipeline for lifting and linking the data, the tools developed for these purposes, as well as a search application allowing to explore the data.

Transforming the JSON Output of SPARQL Queries for Linked Data Clients.

SPARQL endpoints are one possible access method to linked data. The results of SPARQL queries serialized in JSON are, however, not suitable to be directly used by web developers in end-user applications who often need to merge the values resulting from variable bindings. In this work, we propose a generic approach implemented in a JavaScript module that takes as input a JSON file describing both the SPARQL query and the shape of the expected output at the same time.

Improving (Re-) Usability of Musical Datasets: An Overview of the DOREMUS Project

Abstract DOREMUS works on a better description of music by building new tools to link and explore the data of three French institutions. This paper gives an overview of the data model based on FRBRoo explaining the conversion and linking processes using linked data technologies and presenting the prototypes created to consume the data according to the web users’ needs.

K-CAP2017 Satellites: Workshops and Tutorials

ACM Reference Format: Carlos Badenes, Ronald Denaux, Martine De Vos, Daniel Garijo, Jose Manuel Gomez-Perez, Agnieszka Lawrynowicz, Pasquale Lisena, Raul Palma, Raphaël Troncy, and Daniel Vila. 2017. K-CAP2017 Satellites Workshops and Tutorials. In K-CAP 2017: K-CAP 2017: Knowledge Capture Conference CD-ROM, December 4–6, 2017, Austin, TX, USA. ACM, New York, NY, USA, 6 pages. https://doi.org/10.1145/3148011.3188410

Modeling the Complexity of Music Metadata in Semantic Graphs for Exploration and Discovery

Representing and retrieving fine-grained information related to something as complex as music composition, recording and performance is a challenging activity. This complexity requires that the data model enables to describe different outcomes of the creative process, from the writing of the score, to its performance and publishing. In this paper, we show how we design the DOREMUS ontology as an extension of the FRBRoo model in order to represent music metadata coming from different libraries and cultural institutions and how we publish this data as RDF graphs. We designed and re-used several controlled vocabularies that provide common identifiers that overcome the differences in language and alternative forms of needed concepts. These graphs are interlinked to each other and to external resources on the Web of Data. We show how these graphs can be walked through for designing a web-based application providing an exploratory search engine for presenting complex music metadata to the end-user. Finally, we demonstrate how this model and this exploratory application is suitable for answering non-trivial questions collected from experts and is a first step towards a fully fledged recommendation engine.

DOREMUS to Schema.org: Mapping a complex vocabulary to a simpler one

Librarians and music professionals often us complex models and ontologies such as FRBRoo to represent music metadata. As a consequence, this metadata is not easily consumable by general search engines or external web applications. This paper presents a methodology, composed of a set of recipes, for mapping a complex ontology to a simpler model, namely Schema.org.

Modeling, Exploring and Recommending Music in Its Complexity

Knowledge models that are currently in-use for describing music metadata are insufficient to express the wealth of complex information about creative works, performances, publications, authors and performers. In this thesis, we aim to propose a method for structuring the music information coming from heterogeneous librarian repositories. In particular, we research and design an appropriate music ontology based on existing models and controlled vocabularies and we implement tools for converting and visualizing the metadata. Moreover, we research how this data can be consumed by end-users, through the development of a web application for exploring the data. We ultimately aim to develop a recommendation system that takes advantage of the richness of the data.