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Category: Communication

Description: Presented at JTS2019 by Jon W. Dunn and Bertram Lyons at the Netherlands Institute for Sound and Vision, Hilversum (NL) on Saturday, October 5, 2019. Collaborative notes available at: https://doi.org/10.5281/zenodo.3835666 ABSTRACT: In recent years, concern over the longevity of physical AV formats due to media degradation and obsolescence, combined with decreasing cost of digital storage, have led libraries and archives to embark on projects to digitize recordings for purposes of long-term preservation and improved access. Beyond digitization, in order to facilitate discovery, AV materials must also be described, but many items and collections lack sufficient metadata. In 2014 Indiana University (IU) began an effort to digitize hundreds of thousands of hours of audiovisual materials from across campus through its Media Digitization and Preservation Initiative (MDPI). In 2015, with the support of consulting firm AVP, the IU Libraries conducted a planning project to research, analyze, and report on technologies, workflows, staffing, timeline and budgets to address the challenge of quickly and efficiently creating metadata for these materials. One of the outcomes of this planning project was identifying a need for a technology platform to support the incremental application of both automated and human-based processes to create and augment metadata. While there have been several open source and commercial efforts to date that demonstrate the possibilities for computationally assisted metadata generation and improved discovery, they have generally been narrow in focus and developed as standalone solutions. In truth, access to audiovisual objects at scale will require a variety of these analysis mechanisms, and these will need to be linked together with human tasks in a recursive and reflexive workflow engine that is compiling, refining, synthesizing, and delivering metadata to be used by any number of target systems. Recognizing that the need for such a platform extends well beyond any single institution, Indiana partnered with the University of Texas at Austin and AVP, with funding from the Andrew W. Mellon Foundation, to bring together a group of experts in the fall of 2017 to provide input into the technical design of a system to meet these needs, which we refer to as Audiovisual Metadata Platform, or AMP. This planning effort, outcomes of which are documented in a public white paper (https://go.iu.edu/ampreport), has led to a subsequent grant from the Mellon Foundation to support initial implementation and testing of the AMP platform beginning in 2019. In this new phase of AMP, known as AMP Pilot Development, or AMPPD, IU and AVP are working to develop an initial version of AMP as an open source system that will enable the creation and execution of workflows that link together both automated and human analysis activities to generate metadata for AV resources. The AMP system will then be pilot-tested against representative samples from collections both at Indiana University and at the New York Public Library to assess its feasibility for further development. In this session, we will describe the architecture of AMP, discuss the use cases and technical considerations that informed its design, and discuss the results so far from its implementation and testing.