nicolas.moulard@actuonda.com

1. The Semantic Middleware :
Media Asset Management of the Audiovisual Big Data
New users experience, New content valorization,
New business Model, New ROI
Semtech top 10 startup of 2013
IBC Award for « Content management » 2013
IBC Award for technology « Who caught my eye looking for blue skies » of IBC 2013
@perfect__memory http://perfect-memory.com

2. Summary of strategic needs
Content owners need to exploit the information in order to maintain and develop its leadership:
• Analyze any source of information
• Decide using the context of the information
• Learn from decisions and improve decisions
In that case, the goal is not to extract hidden data in the audiovisual content but exploit all information
available to the content owner in order to take the right decisions and learn on the result of decision.
Be limited to the extract of information would be an error.
1
INGEST
content
2
• Company
programs
•Competitors
programs
EXTRACT
information
3
•Audio analysis
•Video analysis
•Log analysis
STRUCTURE
information
Sources
4
•Categorize
•Link
•Map
EXPLOIT
information
• Analyse
• Decide
• Learn
• Value
Goal & Need
Means
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© PERFECT MEMORY - CONFIDENTIAL
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3. Summary of functional needs
During our conversations we have identified that content owners need to:
• Extract information from the audiovisual content (speech to text, video analysis, content
classification),
• Ingest & analyze various broadcast channels,
• Be autonomous in term of platform configuration, enrichment and monitoring,
STRUCTURE
information
•Categorize
•Link
•Map
EXPLOIT
information
• Analyse
• Decide
• Learn
• Value
Being autonomous !
11/11/2013
© PERFECT MEMORY - CONFIDENTIAL
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4. Summary of functional needs
During our conversations we have identified the needs to:
• Structure the content using opened and documented standards,
• Link, enrich & index the massive volumes of Contents,
• Browse inside the massive volumes of Contents,
• Manage the content all along its life cycle,
• Monetize & Value the content.
• Become autonomous in the administration of the knowledge and its infrastructure
• Being flexible in term of strategy of knowledge management
• Avoid starting from scratch
INTRODUCING PERFECT MEMORY'S OFFER
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5. Summary of our solution
The semantic middleware is :
• Natively compliant to the main media standards (EBU Core, FIMS, OAIS,…)
• Providing a media mapping manager (multiple instances of items handling),
• A non intrusive, scalable and flexible platform,
• Self learning, opened to other modules and functionalities,
• Seamless to any installed applications, and communicating with them,
• Operating inside the global and secured intranet of our client.
• Transferable platform
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6. Media Challenge : New needs
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7. Media Challenge : new comers
The Media-brands
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8. RTBF and Radio France Business Cases
RTBF and Radio France Profiles
The customers are broadcasters that:
• Produces and buy TV and/or radio programs (documentaries, shows, fictions),
• Broadcasts TV and/or radio programs and live shows and events,
• Archives the broadcasted content,
• Sells advertisement time slots.
Twenty different specialized MAMs are running to ensure each of this tasks.
The Headquarter of technologies and exploitation needs to fix the:
1.
Lack of description of their content
2.
Difficulty to access the content scattered in the different MAMs (Media Asset Management
Systems)
3.
Poor ROI on the digital exploitation of media
11/11/2013
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9. RTBF and Radio France Business Cases
The expectations
The customers expectations:
1.
Provide to its archivists and journalists an unique access point to search the content stored in
the MAMs
2.
Lower the cost of indexing the multimedia content
3.
Provide a solution for the controlled annotation of the multimedia content
4.
Enrich the content
5.
Structure the content with a global model available upon all the MAMs
11/11/2013
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10. RTBF and Radio France Business Cases
Main facts
… generating deep archives issue ….
Lost opportunities
… and management issue
Waste of time
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11. RTBF and Radio France Business Cases
A three steps project
Step 1
Data model
configuration
Step 2
Audit of customer’s
data model
Customize Perfect
Memory’s ontology and
Knowledge base
Platform
configuration
Step 3
Delivery
List of module to
activate
List of MAM to connect
List of front-end to
activate
Involving the CDO*
Deployment of the
Semantic Middleware
Training and
autonomization of
customers team
Exploitation by the
archivists and
journalists
Involving the final users
Involving the CTO
*Chief Data Officer
11/11/2013
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12. Business Cases Belgavox
Belgavox’s global Market Place
Belgavox is a belgium archivist that:
• Archives the content,
• Sells its inventory.
Belgavox needs to:
1.
Develop the traction of its inventory,
2.
Expose the entirety of its inventory,
3.
Develop new monetization channels.
11/11/2013
INTRODUCING PERFECT MEMORY'S OFFER
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13. RTBF and Radio France Business Cases
Semantic Media Asset Management of Inventory
The customers expectations:
1.
Become a media-brand
2.
Set a market place and connect any potential customers on its inventory
11/11/2013
INTRODUCING PERFECT MEMORY'S OFFER
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14. RTBF and Radio France Business Cases
A three steps project
Step 1
Data model
configuration
Step 2
Audit Belgavox’s data
model
Customize Perfect
Memory’s ontology and
Knowledge base
Platform
configuration
Step 3
List of module to
activate
Connection to
Belgavox’s repository
Delivery
Step 4
Deployment of the
Semantic Middleware
Monetization
Belgavox Market Place
Training and
autonomization of
Belgavox’s team
$
List of front-end to
activate
Involving the CDO*
Involving the final users
Involving the CTO
Involving the market
*Chief Data Officer
11/11/2013
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15. RTBF Annotation & search interfaces
Features:
Breakthrough user friendly interface for big data visualization
Graphical browsing in big data content (media and metadata)
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16. Radio France Tablet Interface
Building the contextualization of the display according to the Role and Skill of the
connected user.

17. RTBF and Radio France Business Cases
Administration of the Semantic Middleware
► Monitoring the process on the semantic middleware (ex: master and proxies creation via semantic rules, semantic
enrichment on STT, publication on the semantic player, etc.)

18. Expertise & know-how
Semantic is not a goal, but just a new tool that has to be used only where it is usefull !
User Interface
USAGE
360° Rendering
PUBLISHING
Inference rules
ENRICHMENT
Semantic Data
PRODUCTION, INGEST
Ontology & knowledge base
MODELING
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19. Linked Open Media
Media Library
Linked Open Data
The semantic
middleware
Links know-how
LINKS KNOWLEDGE
THE PLAYER
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20. Perfect Memory
… is happy to introduce its
Semantic middleware.
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21. The PROFILE : knowledge capitalization
Your Data Structure
Your Media Library
Linked Open Data
YOUR KNOWLEDGE
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22. An architecture scalable, distributed
Introducing the Semantic Middleware
(1)
(1) The Heart inludes the
Knowledge base
features, and the OAIS
functionalities
SEMANTIC
PLAYER
(2)
(2) The BUS, 100%
compliant to EBUCore,
becomes the backbone
of the middleware
(3) Any Bases ingested,
or functionalities
connected via an
InteOperability Windows
(GIO) becomes a
semantic ressource for
the Middleware
YOUR
APPLICATION
(3)
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23. Content analysis & knowledge extraction
In addition to Storage and
acquisitions (ingest) capacities
the Semantic Middleware can
be connected (via IOW) with
Media indexing features
The Semantic Middleware
n°
IOW Name
1
Semantic DB, Knowledge Mapping, Inference Rules
LOD retrieval
2
Ingest MAM
3
Ingest stream
6
Storage
8
Preservation OAIS
9
Acquistion of content (audio, video, texte)
10
Media Transcoding
11
Sequence generation
12
Automatic editing
13
Sound Processing
14
Video Processing
19
Manuel Indexing
20
Classification
21
Semantic Player - Restitution WEB
22
IPAD Player – IOS
24
Media Shopping Basket
25
Push & Pull on alarm
28
FONCTIONNALITY
Global Market Place
Semantic Management
Acquisition
Storage
A list of actual functionalities
includes the features above.
Media Processing
Media Indexing
But, any other existing external
modules with an open API can
be connected by the IOW.
Browsing
Value & Monetization
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24. The Middleware features …
Before
• Automatic linking with external related contents,
• Automatic knowledge validation,
• Cross-browsing in broadcasters’ MAMs.
After
Media Processing
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25. From Raw Data to linked Knowledge
1.
2.
3.
Automatic audio & video analysis
Automatic enhancement from flat to EBU* Core compliant models,
Automatic semantic enrichment of MAM contents
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26. Linked Open Media
Media Library
Linked Open Data
The semantic
middleware
Links know-how
LINKS KNOWLEDGE
THE PLAYER
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27. Graphical Interface are 360°
360° Access – Tablets, Smart TV, Browser & Smartphones
multi-context, multi-platform, multi-role and skills
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28. Flexibility & scalability of the middleware
Control
Expressivity
Enrichment
Extraction

29. Added values
Cost reduction of information collection
• Semantic Enrichment and enhancement (Linked Open Data)
• Data base alignment – Structuration of unstructured data
• Assisted and collaborative indexing (Validated Tagging)
• Auto-indexing along selected Types
• Fine named entities recognition thanks from semantic contextualisation
• Self learning process (Inference)
Distributed process management
• Traceability & monitoring of the process (Open Semantic Bus)
• Linking & Interoperability of independent process (Interoperability Wicket)
Mapping of assets
• Explicit characterization and self generation of the links between assets
(predicat management)
• Listing & preservation of critical data (Knowledge base)
Multi-axial exploitation of the media
• Multi-platform publication
• Contextualized rendering of data
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30. Value generation & Cost reduction
Flat information is enhanced as a Knowledge
The contents are now automatically indexed and self enriched
The cost of processing is reduced by 20 today
The automatic event trigger enhances revenue from the automatic extraction and
communication of pertinent information
Native advertising is possible possible at any levels of the content
Unique Identifier is resolved according to the OAIS and EBU Core Standards
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31. Deployment in 4 steps
Deployment process : The 4 steps …
Semantic
profile
Audit
Needs
Ontology
User scenarios
Knowledge base
Architecture
Modeles of Data bases
Configuration
Specific ingest
InterOperability windows
configuration
Intégration &
Deployment
Test &
delivery
Delivery within 4 to 6 months
1 Month
1 to 2 Months
2 Months
In situ work
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32. They choose Perfect Memory
They decided to choose Perfect Memory and are now extending their
Middleware …
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33. Perfect Memory – The Team
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34. Perfect Memory – The eco-system
Registered in 2008, a Ltd with 245 K€ capital
Funded by SOFIMAC Partner a major investor in France
Deploying for Media, Media-Trade, Archivers and Big Companies
Expert in management, indexation, and of monetization of mass volumes of Multi Media
Owning a unique Middleware process transforming raw data into Knowledge
INTRODUCING PERFECT MEMORY'S OFFER
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35. The Semantic Middleware :
Media Asset Management of the Audiovisual Big Data
New users experience, New content valorization,
New business Model, New ROI
Steny Solitude
CEO
Steny.solitude@perfect-memory.com
@perfect__memory
Frédéric Colomina
Business Development
Frederic.colomina@perfect-memory.com
@perfect__memory
Semtech top 10 startup of 2013
IBC Award for « Content management » 2013
IBC Award for technology « Who caught my eye looking for blue skies » of IBC 2013
@perfect__memory http://perfect-memory.com

36. III Rencontres RADIO 2.0 Paris
Radio Augmentée & Publicité
www.rr20.fr
15 oct 2013 @ Ina Paris
250 professionnels / 50 intervenants
10 keynotes / 3 tables rondes / 12 workshops
Grands Prix Radio 2.0 / La Radio des Rencontres
Partenaires Platinum :
Organisateurs :
Nicolas Moulard
moulard@actuonda.com
Xavier Filliol
xavier@octet.com