Realizing Additional Value From Linear Content Using Metadata and Automation

Metadata

Publisher: SMPTE — White Plains, NY, USA
Doc Type: Journal Article
Content Type: Original Research
Abbreviated Title: SMPTE Mot. Imag. J
Volume: 131, No. 3, pp. 8–16
Abstract: This article describes the collaboration between BBC News and BBC Research & Development, who are exploring ways to use the BBC’s linear program output and associated production metadata, along with artificial intelligence and machine learning techniques, to segment the programs into individual stories. These segments can then be used to provide chapterized versions of the linear output, make individual stories findable by search and available as items on web pages. Ultimately, by using object-based media (OBM) techniques, these stories can be recombined to provide personalized and/or interactive experiences. We hypothesize that access to individual stories and items instead of entire, undifferentiated programs will be of greater value to audiences and we provide the user testing results that support this. In this article, we explain the approach being taken to recover program metadata and how that can help achieve content segmentation at scale. The article then describes how OBM techniques are being used to automatically combine segmented content to make new interactive and personalized experiences, including the prototype code base and the workflows developed so far. The article concludes with a summary of the key findings from the work to date, including audience benefits, data consistency, and the role of editorial oversight.
Publication Date: 2022-04-01
DOI: 10.5594/JMI.2022.3153662
ISSN: Print: 1545-0279 | Electronic: 2160-2492
Link: https://doi.org/10.5594/JMI.2022.3153662
Author(s): Michael Armstrong
bio
Michael Armstrong works at the interaction between people, stories, media and technology. Their work spans topics from access services, speech audibility, video quality to human perception and the originator of Object-Based Media, an idea formed whilst pioneering computer-based playout in the 1990s at BBC Radio Bristol, Bristol, U.K. Their current research is examining the way media experiences can be built using data-driven techniques enabling media personalisation and natural feeling responsive interaction. This work combines the issues of storytelling and narrative structures, natural forms of agency for the user, the problems of personalisation and the roles that the user can play in an experience along with a healthy dose of data science and python code.
Miles Bernie
bio
Miles Bernie is the head of product at BBC News Labs, London, U.K. He is a news incubator at the intersection of journalism, tech, and data, responsible for strategy, architecture, agile delivery, and innovation transfer.
Dave Bevan
bio
Dave Bevan joined BBC News, U.K., in 1995. A serial innovator, he has a long list of internal tools to his name that have delivered significant new ways of working and bridging internal production tools to provide significant workflow improvements. He also led the migration from traditional broadcast graphics hardware to desktop software-based graphics production. An early adopter of web technologies, he led the development of a BBC-wide web-based image library system in 1998 and later focused on delivering new and innovative audio and video tools. For the past five years, Bevan has been a member of the BBC’s News Labs innovation hub—a team that brings together software innovators, media production and broadcast engineering specialists, data analysts, and user experience innovators. Together, they deliver new and innovative audience experiences and drive forward the adoption of new ways of working, tools, ideas, and concepts for staff.
Andy Brown
bio
Andy Brown is a research scientist and software engineer at BBC Research & Development, Salford, U.K. He has a background in computer science, having gained a PhD and worked as post-doctoral research associate at the University of Manchester, Manchester, U.K., in the fields of human–computer interaction and accessibility. His work is currently focused on object-based media where he is helping to develop the tools for creating and playing content. He has a particular interest in exploring how audience analytics can be used to provide insights into how the experiences bring value to users.
Keyword(s): Interactive Media, Metadata, Object-based Media (OBM), Repurposing, Segmentation
Copyright: © 2022 SMPTE

Bibliographic Reference(s)

Source Data (JSON)

Full registry record with provenance metadata. Open directly: /api/doc/10.5594-JMI.2022.3153662.json

Reference Tree

Explore all references and references to this document, as a navigable tree.

Open Reference Tree

Reference this Doc

Plain text (ISO 690 compliant)

Preview:

Michael Armstrong, Miles Bernie, Dave Bevan, and Andy Brown; Realizing Additional Value From Linear Content Using Metadata and Automation, SMPTE Motion Imaging Journal ( Volume: 131, Issue: 3, April 2022); SMPTE, 2022. Available at https://doi.org/10.5594/JMI.2022.3153662

Snippet:

Michael Armstrong, Miles Bernie, Dave Bevan, and Andy Brown; Realizing Additional Value From Linear Content Using Metadata and Automation, SMPTE Motion Imaging Journal ( Volume: 131, Issue: 3, April 2022); SMPTE, 2022. Available at https://doi.org/10.5594/JMI.2022.3153662

HTML (ISO 690 compliant)

Preview:

Snippet:

<span class="citation">Michael Armstrong, Miles Bernie, Dave Bevan, and Andy Brown; <cite>Realizing Additional Value From Linear Content Using Metadata and Automation</cite>, SMPTE Motion Imaging Journal ( Volume: 131, Issue: 3, April 2022); SMPTE, 2022. Available at <a href="https://doi.org/10.5594/JMI.2022.3153662" target="_blank" rel="noopener">https://doi.org/10.5594/JMI.2022.3153662</a></span>

SMPTE's HTML Pub

Preview:

Michael Armstrong, Miles Bernie, Dave Bevan, and Andy Brown; Realizing Additional Value From Linear Content Using Metadata and Automation, SMPTE Motion Imaging Journal ( Volume: 131, Issue: 3, April 2022); SMPTE, 2022
doi: 10.5594/JMI.2022.3153662
url: https://doi.org/10.5594/JMI.2022.3153662

Snippet:

<li>
Michael Armstrong, Miles Bernie, Dave Bevan, and Andy Brown; <cite id="bib-10-5594-jmi-2022-3153662">Realizing Additional Value From Linear Content Using Metadata and Automation</cite>, SMPTE Motion Imaging Journal ( Volume: 131, Issue: 3, April 2022); SMPTE, 2022
<span class="doi">10.5594/JMI.2022.3153662</span>
</li>