Once upon a time, long, long ago in a media facility far, far away, the world of media transformation was a simple place. Today, things are very different; we are manufacturing a specific version for a specific business need against a specific delivery profile. The old paradigm of "use this profile to transcode" has been replaced with "here is the workflow that encapsulates our business rules for this deliverable.”
Once upon a time, long, long ago in a media facility far, far away, the world of media transformation was a simple place. You could take an SDI stream and put it into a box with knobs on it and by twiddling the knobs a different representation of the original signal would come out. You could capture an SDI stream to a file and do the same function with a piece of software, but essentially the workflow was the same. The output was just a different encoding or frame rate or resolution of the input.
Today, things are very different. The input to a transformation workflow is often a bunch of components; a version of a media file, some dubbed audio, a caption file, an EDL, some ancillary graphics, some metadata and a loudness control track. We are no longer simply creating a new representation of an existing asset, today we are manufacturing a specific version for a specific business need against a specific delivery profile. The old paradigm of "use this profile to transcode" has been replaced with "here is the workflow that encapsulates our business rules for this deliverable.” The new levels of automation that this can bring allows media rights holders and facilities acting on their behalf to tailor a title for a specific platform and a specific market at a cost that was just not possible five years ago.
As you might already know for some time (we first talked about IMF in 2013 and organized a webinar last year), SMPTE has created a new, standardized mastering format called IMF – the Interoperable Mastering Format (SMPTE ST 2067). This format is designed to power the world of multi-platform, multi-lingual, multi-resolution delivery. It has a wealth of facilities for identification, auditing and tracking of media, titles and metadata. Although based on human-readable XML, it is fundamentally optimized for machine processing.
To get the best from an IMF workflow, machine processing of metadata is required. Ensuring consistency of metadata across many assets and many references to those assets is an easily optimizable task for software, but a tedious mind-melt for a human being. Dalet Workflow Engine has been enriched with a number of dedicated tasks that decompose the process of making an IMF bundle so that they can be optimized for a particular environment. Different facilities may have different starting points. For example, facility A may have to transcode a ProRes asset at the start of a workflow whereas facility B may already have AS02 assets that can be used without essence modification to create the IMF bundle. Facility A may require a user interface to transfer business metadata into the IMF bundle whereas facility B may already have that data in a MAM and can synthesize the right XML at the start of the workflow.
With the huge variation of starting points for IMF creation, it is imperative that a workflow engine is versatile and able to use the right tools at the right time to form a valid and verifiable IMF bundle at reasonable speed and for reasonable cost. Dalet Workflow Engine has been optimized for these kinds of workflows where the number of input files is not known until the job starts, and the workflow proceeds without losing or changing vital information. The cherry on the cake is the ability to see the performance of the jobs in a data analytics engine that is able to spot trends in operation so that continual optimization of the tools can be performed.
As the industry trends from software purchased with capital budget to solutions that run as a service (SaaS), it is imperative that applications performing media workflows deliver ROI. This can only be done with control AND visibility. Fortunately, Dalet AmberFin together with the Dalet Workflow Engine delivery both, and that’s just one of the reasons why it was awarded a StudioDaily Prime Award at the last NAB Show!
Moving from a "use a profile to transcode" approach to a complex multi-inputs/outputs workflow requires some education. Even though Dalet AmberFin and its workflow engine ship with a user-friendly, web-based interface to design, manage and monitor your workflows, we created a number of tutorial videos to introduce the concepts of the user interface and explain step-by-step how to leverage all the functionalities of the engine. Click here to access the videos!