Asset Manager Metadata Transformation via Workflow Engine
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Solution Overview
Problem
The increasing demand for media delivery across various devices and platforms poses challenges in efficiently processing and distributing multimedia content, including formatting, transcoding, and inserting advertisements, due to the complexity and variability of content formats and metadata.
Innovation Solution
A digital data clearinghouse (DDC) system that allows users to define work units, compose workflows, and dynamically manage asset distribution by performing tasks such as reformatting and inserting advertisements, utilizing a graphical user interface and automated processes to streamline content processing and distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processing of content formats and metadata is used, then processing accuracy can be maintained, but processing time and labor costs increase significantly
Solution Approach 1:
The system segments content processing into distinct work units (transcoding, formatting, ad insertion, etc.), each handled by specialized modules. This allows parallel processing of different content types while maintaining organization through modular architecture, resolving the contradiction between processing speed and system complexity.
Solution Approach 2:
The patent introduces a workflow engine as an intermediary that automatically coordinates between content sources, processing modules, and distribution channels. This mediator handles the complexity of format conversion and metadata transformation automatically, enabling high-speed processing without requiring complex manual coordination.
2Productivity
If automated workflows are implemented, then processing efficiency improves, but flexibility to handle unique content requirements decreases
Solution Approach 1:
The workflow engine provides dynamic configuration capabilities, allowing automated workflows to be adjusted in real-time based on content requirements. Users can dynamically add, remove, or modify processing steps without disrupting the entire system, maintaining both efficiency and flexibility through adaptive automation.
Solution Approach 2:
The system implements universal processing modules that can handle multiple content types and formats through a single integrated platform. The same workflow engine manages diverse tasks (transcoding, subtitles, ads) across different media types, providing flexibility through standardized multi-functional components rather than dedicated specialized systems.
3Adaptability or versatility
If content is processed for multiple devices and platforms simultaneously, then distribution coverage increases, but processing complexity and resource requirements increase
Solution Approach 1:
The system segments device-specific processing requirements into separate work units that can be executed in parallel. Different device formats (mobile, tablet, desktop) are processed simultaneously through dedicated modules, increasing distribution coverage while managing resource usage through parallelization rather than sequential processing.
Solution Approach 2:
The workflow engine performs preliminary analysis of content and target devices before processing begins, optimizing resource allocation in advance. By pre-determining the best processing paths and resource requirements for different device types, the system reduces real-time resource consumption while maintaining comprehensive device compatibility.
Data Source
AI summary
A method may include automatically receiving content and metadata; automatically identifying a source metadata format of the metadata; automatically identifying a target metadata format; automatically selecting a data map to perform validation of the metadata and at least one of transforming or translating of the metadata based on the identifying of the source metadata format and the identifying of the target metadata format, wherein the transforming includes converting the metadata to the target metadata format and the translating includes converting a file type of the metadata to a target metadata file type; and automatically attempting to validate the metadata based on the data map; automatically performing the at least one of the transforming or the translating of a validated metadata when the metadata is validated based on the data map, wherein the transforming includes converting the validated metadata to the target metadata format including one or more extendible fields.