Perfect Memory Media Asset Management MAM of Audiovisual Big Data @ Radio 2.0 2013

The Semantic Middleware :

Media Asset Management of the Audiovisual Big DataMedia 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

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.

• Company programs

•Competitors programs

INGEST

contentINGEST

content

•Audio analysis

•Video analysis

•Log analysis

EXTRACTinformation

EXTRACTinformation

•Categorize

•Link

•Map

STRUCTUREinformation


• Analyse

• Decide

• Learn

• Value

EXPLOITinformation

EXPLOITinformation

Be limited to the extract of information would be an error.

SourcesMeans

Goal & Need

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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,

11/11/2013 3© PERFECT MEMORY - CONFIDENTIAL

•Categorize

•Link

•Map



• Analyse

• Decide

• Learn

• Value

EXPLOITinformation

EXPLOITinformation

Being autonomous !

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

4INTRODUCING PERFECT MEMORY'S OFFER

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


Media Challenge : New needs


Media Challenge : new comers

The Media-brands


RTBF and Radio France Business Cases

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.

RTBF and Radio France Profiles

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 INTRODUCING PERFECT MEMORY'S OFFER 8


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

The expectations

5. Structure the content with a global model available upon all the MAMs



… generating deep archives issue ….

Main facts

Lost opportunities

… and management issue

Waste of time



Audit of customer’sdata model

Customize PerfectMemory’s ontology and Knowledge base

Step 1

Data model configuration

Step 1

Data model configuration List of module to

activate

List of MAM to connect

List of front-end to activate

Step 2

Platform configuration

Step 2


Deployment of the Semantic Middleware

Training and autonomization of customers team

Exploitation by the archivists and journalists

Step 3

Delivery

Step 3

Delivery

A three steps project

activate journalists


Involving the CDO*

Involving the CTO

Involving the final users

*Chief Data Officer

Business Cases Belgavox

Belgavox is a belgium archivist that:

• Archives the content,

• Sells its inventory.

Belgavox needs to:

1. Develop the traction of its inventory,

Belgavox’s global Market Place

2. Expose the entirety of its inventory,

3. Develop new monetization channels.



The customers expectations:

1. Become a media-brand

2. Set a market place and connect any potential customers on its inventory

Semantic Media Asset Management of Inventory



Audit Belgavox’s data model

Customize PerfectMemory’s ontology and Knowledge base

Step 1

Data model configuration

Step 1

Data model configuration List of module to

activate

Connection to Belgavox’s repository

List of front-end to activate

Step 2


Step 2


Deployment of the Semantic Middleware

Training and autonomization of Belgavox’s team

Step 3

Delivery

Step 3

Delivery

Belgavox Market Place

Step 4

Monetization

Step 4

Monetization

A three steps project

$$


Involving the CDO*

Involving the CTO

Involving the final users

Involving the market

*Chief Data Officer

RTBF Annotation & search interfaces

Features:

� Breakthrough user friendly interface for big data visualization

� Graphical browsing in big data content (media and metadata)


Radio France Tablet Interface

Building the contextualization of the display according to the Role and Skill of the

connected user.


► 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.)

Administration of the Semantic Middleware

User Interface

USAGE

360° Rendering

PUBLISHING

Expertise & know-how

Semantic is not a goal, but just a new tool that has to be used only where it is usefull !

Inference rules

ENRICHMENT

Semantic Data

PRODUCTION, INGEST

Ontology & knowledge base

MODELING


Media Library Linked Open Data

The semanticmiddleware

Links know-how

Linked Open Media

THE PLAYER LINKS KNOWLEDGE


Perfect Memory

… is happy to introduce its… is happy to introduce its

Semantic middleware.


The PROFILE : knowledge capitalization

YourYour Data StructureData Structure

YourYour Media LibraryMedia Library Linked Open DataLinked Open Data

YOURYOUR KNOWLEDGEKNOWLEDGE


An architecture scalable, distributedIntroducing the Semantic Middleware

SEMANTIC

PLAYER

(1) The Heart inludes the Knowledge base features, and the OAIS functionalities

(1)

(2)

YOUR

APPLICATION

(2) The BUS, 100% compliant to EBUCore, becomes the backboneof the middleware

(3) Any Bases ingested, or functionalitiesconnected via an InteOperability Windows (GIO) becomes a semantic ressource for the Middleware

(2)

(3)


Content analysis & knowledge extraction

The Semantic Middleware

FONCTIONNALITY n° IOW Name

Semantic Management 1Semantic DB, Knowledge Mapping, Inference Rules

LOD retrieval

Acquisition2 Ingest MAM

3 Ingest stream

Storage6 Storage

8 Preservation OAIS

9 Acquistion of content (audio, video, texte)

In addition to Storage and

acquisitions (ingest) capacities

the Semantic Middleware can

be connected (via IOW) with

Media indexing features

A list of actual functionalities

Media Processing

9 Acquistion of content (audio, video, texte)

10 Media Transcoding

11 Sequence generation

12 Automatic editing

Media Indexing

13 Sound Processing

14 Video Processing

19 Manuel Indexing

20 Classification

Browsing21 Semantic Player - Restitution WEB

22 IPAD Player – IOS

Value & Monetization

24 Media Shopping Basket

25 Push & Pull on alarm

28 Global Market Place

A list of actual functionalities

includes the features above.

But, any other existing external

modules with an open API can

be connected by the IOW.


The Middleware features …

• Automatic linking with external related contents,

BeforeBefore

After•

• Automatic knowledge validation,

• Cross-browsing in broadcasters’ MAMs.

After

Media Processing


From Raw Data to linked Knowledge

1. Automatic audio & video analysis

2. Automatic enhancement from flat to EBU* Core compliant models,

3. Automatic semantic enrichment of MAM contents


Media Library Linked Open Data

The semanticmiddleware

Links know-how

Linked Open Media

THE PLAYER LINKS KNOWLEDGE


Graphical Interface are 360°

360° Access – Tablets, Smart TV, Browser & Smartphonesmulti-context, multi-platform, multi-role and skills


Flexibility & scalability of the middleware

Control Enrichment

ExtractionExpressivity

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 data29INTRODUCING PERFECT MEMORY'S OFFER

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


AuditSemantic

profileConfiguration

Intégration &

Deployment

Deployment process : The 4 steps …

Needs Ontology Specific ingest Test &

Deployment in 4 steps

Needs

User scenarios

Architecture

Modeles of Data bases

Ontology

Knowledge base

Specific ingest

InterOperability windows

configuration

Test &

delivery

1 Month

2 Months

1 to 2 Months

1 Month

In situ work

Delivery within 4 to 6 months


They decided to choose Perfect Memory and are now extending their

Middleware …

They choose Perfect Memory


Perfect Memory – The Team


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


The Semantic Middleware :

Media Asset Management of the Audiovisual Big Data

New users experience, New content valorization,New users experience, New content valorization,

New business Model, New ROI

Frédéric Colomina

Business Development

[email protected]

@perfect__memory

Steny Solitude

CEO

[email protected]

@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

III Rencontres RADIO 2.0 Paris

Radio Augmentée & Publicité15 oct 2013 @ Ina Paris

250 professionnels / 50 intervenants

www.rr20.frwww.rr20.fr

Organisateurs :

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

[email protected]

Xavier Filliol

[email protected]

Technology

Perfect Memory Media Asset Management MAM of Audiovisual Big Data @ Radio 2.0 2013