Linked Digital Future for the Performing Arts:
Leveraging Synergies along the Value Chain
The objective of this research report was to identify concrete recommendations for the implementation of shared semantic technologies across the performing arts value chain with the intent of improving data systems interoperability and enhancing the discoverability of the performing arts by consumers.
LDF research lays the foundations for ensuing prototyping and development phases, providing direction for a digital literacy campaign that will roll out in the arts sector, and inform the deliberations of the Advisory Committee on potential governance structures.
LDF research catalogues various initiatives at the international level to establish a linked open data ecosystem for the performing arts. Most of these initiatives emerge from the heritage and research sectors; very few directly address the primary value chain of the performing arts, involving performing arts professionals, production companies, presenting organizations, operators of arts facilities, dissemination platforms, and concert/theatre goers. By placing primary focus on performing arts stakeholders, LDFI is breaking new ground.
Comparative analysis of the usage scenarios of different stakeholder groups has shown that the respective requirements for data overlap considerably; the core elements of the data model are consistent across sectors. This means that substantial synergies are to be expected not only with regard to data maintenance, but also in view of the development of other parts of the data infrastructure, including platforms for data entry, services for data extraction, analysis and visualization, or the provision of data and/or media repositories.
Furthermore, exchanges with LDF project members and institutions in other countries have shown that many usage scenarios related to a linked open data ecosystem for the performing arts have international relevance. There are also important usage overlaps regarding repertoire as well as artists and artists’ collectives. Given the many links between Canadian performing arts metadata and similar data from other countries, international cooperation should be strengthened.
To facilitate the implementation of the technical solutions to be developed as part of LDF initiative, an initial conceptual model and formal ontology were developed based on existing data models.
Data modelling was guided by a set of sample resources describing current performing arts productions and performance events in Canada. The data from the sample resources has been published as linked open data and serves as a basis for discussion as the model continues to develop.
Prototyping and implementation of two Canadian use cases to be pursued during the remainder of LDFI have been initiated with the proposed next steps:
Both applications contribute to and consume data from the Artsdata.ca performing arts knowledge graph.
At present, the graph database is still in its infancy, but the shared effort is on eventually assembling all relevant data about current and future performing arts events in Canada and by Canadian artists or artists’ collectives abroad. The creation of Artsdata.ca aspires to give the arts sector some control over its own data in a digital environment ruled by recommendation algorithms that help people plan their leisure time; an activity increasingly reliant on quality structured data in order to deliver pertinent results. Artsdata.ca is open to further data providers and may serve a variety of use cases beyond consumption.
To better equip itself for the digital world, members of the performing arts sector are strongly advised to embrace the linked open data approach proposed in this report. To support this process, the LDF team is planning a digital literacy campaign for the Canadian arts sector.
Based on the key insights gained through the action research, the LDF Advisory Committee has adopted five recommendations to be taken into account during this and similar initiatives:
Imagine a linked open data future for the arts.
Take a deep dive into the sample data.
Explore LDF’s linked open data model in an interactive graph. (Best viewed on desktop. Available in English only.)