Connections

By Chris Tribbey

Before coming over to Universal Music Group last year as its new VP of advanced media planning and management, JR Yasgur spent more than a decade with Sony Pictures Entertainment. And whether it’s the film or the music side of the entertainment business, one thing’s the same: justifying a return on investment when it comes to adopting new ways to tackle data isn’t easy.

“We can talk about what type of data we need to capture from an operational perspective, to ingest our content, to preserve it, archive it, store it, remonetize it, that’s different data than what we’re talking about when it comes to enriching the consumer experience, monetizing it and the social data that accompanies it,” Yasgur said, speaking at the second annual Smart Content Summit. “On the studio and music side, there is a bit of a challenge for us to justify the ROI, because each of these initiatives, they certainly are costly, require structure, resources … initially it’s often driven by the marketing group, with how we’re going to re-exploit the content.”

She was speaking during a panel on how entertainment companies today are going about managing their huge libraries of content, and doing it beyond simple text-based search by creating taxonomies and ontologies to help find the relationships between assets. And the more content you’re dealing with, the more complex the job of mapping those relationships, panelists agreed.

Aaron Edell, VP of operations and professional services for GrayMeta, said media and entertainment companies must strive for normalization when dealing with multiple data sets, to make sure data is searchable across multiple data aggregators and multiple data providers. He and others continued to use an analogy offered up by Eric Iverson, SVP and divisional CIO for Sony Pictures Television, that your data can’t just be thrown haphazardly into a garage, but must be organized neatly in the garage. The cleaner that garage becomes, the easier it is to find — and monetize — content.

“We can now look into the boxes, and see what everything is, programmatically, and we don’t have to tag everything manually,” Edell said. “I think we approach it backwards some times: we start with the organization and the taxonomy, and then use that to attack the data, rather than use the data to attack the organization.

“The big upside to semantic metadata is that before it was a very manual process, and now you can get a much greater economy of scale through automation, and the point of having all this data — big data — is you’re starting to make the connections, that you’re finances have relevance to what kind of money you’re spending on storage, or what kind of cameras you’re renting, what kind of data is coming in from other locations, and you have to be able to sit in a place where you can logically see all of that.”

Matt Turner, CTO of media and publishing for MarkLogic, extended the analogy further: the intelligence in the data — and your taxonomies, ontologies and semantics —are the bins, the shelves you put in place before you put your data in. And to Yasgur’s point, he does see a shift happening in the ways companies are investing in how they tackle their data.

“Instead of just throwing everything into the garage, it’s not just organizing it neatly, it’s organizing it for a specific purpose,” he said. “Semantic data is flexible. If you use these [more recent] approaches, you’re building a base of information that isn’t thrown away, it isn’t just for one purpose. And that’s a big difference in how you make an investment in the data. It’s going to pay off in other areas later.”

For Matthew Wildrick, senior manager of product management for Rovi Corp., he believes it’s all well and good that companies are thinking about how to organize their garages of data, but maybe they should also spend some time looking at how that data got there in the first place, and learning from that. “If you don’t have the data in the first place, if you can’t think about all of this stuff in the context of billions of files — because really, we’re not talking about a few boxes in the garage, we’re talking about billions of them — you need to be able to account for them, and that whatever semantics you do come up with, it’s going to be reliant on humans entering metadata,” he said.

Yasgur said getting your garage in order is worth the headaches: finding new ways to identify and retrieve data opens up all sorts of new avenues of monetization, data areas you may not have previously thought about capturing around content. “How do you we go about identifying it? How do we implement a workflow for capturing it going forward? And how do we go back to the existing library of content and capture that information in an efficient, cost effective, operationally viable manner?” she said.

The Feb. 4 Smart Content Summit, presented by the Media & Entertainment Services Alliance (MESA) brought together more than 300 top data, operations and research executives from TV, film and home entertainment.