- The guide explains media ontologies in simple terms, provides a useful discussion of mapping data across different information systems, and offers practical examples of how media organizations are using semantic web technologies to bring greater efficiency to real-world workflows.
- Understanding and managing the complex relationships between all elements in the content life cycle — from scripts to assets to the tasks being performed across media workflows — requires richer metadata.
READ MORE: SMPTE, MovieLabs, and EBU Publish ‘Media in the Cloud: Ontology and Semantic Web Technology Navigation Guide (SMPTE)
SMPTE, MovieLabs and the European Broadcasting Union have published a guide to working with cloud technology as part of the overall industry effort to standardize production and distribution in the cloud.
The “Media in the Cloud: Ontology and Semantic Web Technology Navigation Guide” is available for free on the SMPTE website. It is described as a primer on the use of ontologies and other semantic web technologies characterized by the movement of workflows into the cloud.
World Wide Web co-founder Tim Berners-Lee first proposed the semantic web in 2001. This was the concept of moving from the mere presentation of content on the web to actionable human and machine-readable data.
Movement towards such a web has been slow, SMPTE details in the guide, but may now be regarded as accelerating thanks to a convergence of mechanisms and specifications that make it more practical and more desirable. These include the cloud itself, which is not a requirement for the use of semantic web technologies but is certainly a catalyst; microservices and application programming interfaces (APIs); artificial intelligence (AI) and machine learning (ML); and media-specific ontology specifications.
As the guide outlines, the movement into the cloud comes with attendant expectations around automation, agility, and scalability and challenges in areas such as interoperability, portability, discovery, and orchestration.
“It is an ever more data-driven eco-system with an increased need for consistent, interoperable metadata and semantics to drive and manage distributed processes and workflows. Fortunately, semantic web technologies — which may be regarded as internet-native — have great potential to address some of these challenges, supporting the combination of standards-based machine-readability with the representation of human subject matter expertise.”
Unfortunately, there is a lack of awareness about what semantic technologies are, what ontologies are, where they are applicable, and how to deploy them.
“The shift of media workflows to the cloud — an ever more data-driven ecosystem — yields many benefits, including greater automation, agility, and scalability. But to realize these, organizations must successfully address challenges related to workflow interoperability, data portability, and the management of complex sets of assets,” said MovieLabs CTO Jim Helman. “Media ontologies provide the essential knowledge framework to address those challenges.”
What is an Ontology?
For the purposes of this paper, an ontology is a formal model that represents a given “knowledge domain” — meaning the entities that are meaningful within that space and the relationships between them — using a set of specifications developed by the World Wide Web Consortium (W3C): primarily RDF; RDFS; OWL; SKOS and SPARQL.
“In practical terms an ontology represents explicit business knowledge and provides the scaffolding for the core data infrastructure of an enterprise or a broader field,” says the Guide.
It goes on: Understanding and managing the complex relationships between all elements in the content life cycle — from scripts to assets to the tasks being performed across media workflows — requires richer metadata. An ontology provides a framework needed to support application and service integration, asset and content management, and search and discovery, among other functions.
The utilization of RDF in particular provides a mechanism for information exchange between applications without a loss of meaning and for creating linked data, meaning data that is interlinked with, and enriched by, data from heterogenous and distributed sources.
The paper warns that semantic technology is not a magic bullet. It does not necessarily replace other technologies and is not a good fit for every use case. It is not as mature as the relational database/SQL eco-system, which may be more appropriate for predictable and consistent data that is not characterized by many or complex relations, and for which there is a greater pool of expert human resources.
However, we learn that semantic technology can be smartly stacked with other tools and is in broad terms a good fit for cloud-based eco-systems, having its genesis as a web-based approach to knowledge management.
“Where there is likely room for development in the near future is in the media factory — the production and distribution supply chain and in media asset management and media processing workflows,” the guide states.
“As these migrate to the cloud or hybrid cloud/on-premises and microservice-based deployments, it will become easier to integrate semantic technologies into day-to-day operations, and more vendors will integrate them into their offerings.”
The paper concludes with a thumbnail view of all the various technologies discussed in this paper from APIs to Wikidata via Data Lake and Node.
“Consistent and interoperable metadata and semantics are key for connecting data sets along the value chain, managing distributed workflows, and integrating applications. They are also crucial for content management and search and discovery,” said Hans Hoffmann, head of Media Fundamentals and Production Technology at EBU Technology and Innovation. “This navigation guide is the result of a great collaboration between EBU, SMPTE, and MovieLabs, three key actors in this field, and it will greatly help the media industry in its transformation into a data-driven ecosystem.”
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