The Evolution of

MAM Systems

May 2015

Jonas Engström, V1.3

High Dynamic Range Hybrid Cloud

Automated Multi Device Watch-Ready 8K

Robotic Auto-Cataloguing Scale-Out DAM

PAM Super-MAM

Proudly Presenting:

Fresh from NAB!!!

Awake yet?

Let’s start over

Essence… and metadata

TV?

Roope and S/360

Nineties: From Text-Only to Highres Video

Industry standard text and search solutions

Internet and the web

Non-linear video editing is evolving

Video servers

Digital newsrooms - NRCSs

Large scale digital video storage is becoming feasible

First of a kind systems to manage video

First broadcast MAM companies formed

Systems at the Turn of the Century:

Customised

New features

Networked

DAM systems entering the broadcast world

First large broadcast digital video libraries

The META Project at Swedish Television

(yes, it actually looked like that)

The META Project at Swedish Television

Noughties: MAM / Archive Roll-Out

• Critical mass of installations

• News/sports and programme content

• Early broadcast adopters:

• ATRES, B&G, CNN, DR, Fox Sports, SVT, TRT, VRT, …

• Characteristics

• First generation feature sets

• Browse video and keyframes / desktop edit

• High degree of bespoke functionality

• Limited but growing API and connectivity options

• Projects were often lead by big IT or SIs

• Many MAM companies also grew significantly

• These are the ”first generation MAM systems”

Lessons Learned

• Many projects took significant time to implement

• A race to keep up with evolving requirements

• Many first of a kind system interfaces and features where

challenging to build

• Lots of deeply embedded bespoke functions

• Built with best intentions using available tools

• But proved difficult and expensive to upgrade

• With that said, operational benefits did materialise

• Main areas of improvement:

• Productisation, QA, project processes

• Making use of new and improved IT platforms and systems

• Platform and eco system thinking

• Matured in terms of scope

Comparable with the evolution of NRCSs

Matured in terms of deployment

Multiple networked systems instead of one behemoth

Using recent advances in search technology

Some systems have more production functions

Others have more interfaces to other systems

The bleeding edge has moved to HTML5 video functions,

feature extraction and linguistic functions

Modular with better APIs

SOA friendly (yes, for real)

Workflow engine

Second Generation MAM Systems

• Matured in terms of scope

Comparable with the evolution of NRCSs

Matured in terms of deployment

Multiple networked systems instead of one behemoth

Using recent advances in search technology

Some systems have more production functions

Others have more interfaces to other systems

The bleeding edge has moved to HTML5 video functions,

feature extraction and linguistic functions

Modular with better APIs

SOA friendly (yes, for real)

Workflow engine

Second Generation MAM Systems

Before: Most Functionality inside the MAM

Now: More Modular and Open

Now: More Modular and Open

A Workflow Engine in Pictures

A Workflow Engine in Pictures

Next Steps?

Data Capture Challenges - News, Sports & CA

1. Harvest production data

2. Improve the usefulness of production data

Good examples:

SVT - integration with NRCS, automation, planning,

publishing and subtitling systems for news

BBC Scotland and Sky News - integration with editing

platforms to harvest key metadata including rights

straight from the timeline

Sports logging - TV2 No, DFL and many more

• DPP - a very good step forward

Now how to scale the concept?

How to get more data on the

programmes we own?

Capture existing production data

Extract additional data from essence

How about being able to search for

subjects / talent and filtering on status /

situations / moods etc?

Data Capture Challenges - Programmes

• Making use of the publishing equivalents to air dates and

channels?

Preparing for the diminishing importance of linear TV vs other

channels?

Social: A lot of posts are produced by many broadcasters

Users do generate loads of data, some useful, some not. Do we

have a policy here?

Data related to web publishing and social media activities is easy

to reach from the archive. Or?

Maybe not even as pointers to the respective system?

Can we get help from the archive to tell the story of TV

programmes on on young social media?

More Challenges - Web & Social Checklist

• Classification / search - semantic, phonetic

Cloud resources for content analysis

Interesting Technology Developments

• Newspapers betting on video

In large parts of the new media landscape,

content production cost is the problem

What if buying stock footage including rights

was as easy as e-shopping?

On the social side, posting videos instead of

pictures is growing in numbers

Some Notes From the Worlds of Old and New Media

Thank You

Spotify playlist link:

https://open.spotify.com/user/jonasexx/playlist/2FMGUkmHHIDqA34xmfL4xx