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Big Data Big Media the new paradigm of multimedia content management with Perfect Memory at Big Media by Actuonda

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Big Data Big Media the new paradigm of multimedia content management with Perfect Memory …

Big Data Big Media the new paradigm of multimedia content management with Perfect Memory

Primer encuentro BIG MEDIA
Conectando Media, Audiencia y Publicidad con Datos
24 de junio 2014, Madrid
• Sponsor Platinum : Perfect Memory
• Sponsor Gold : Stratio, Paradigma
• Con el apoyo de : Big Data Spain, Medios On
• Socio tecnológico : Agora News
• Organizadores : Actuonda y Cátedra Big Data UAM-IBM
• Contacto : Nicolas Moulard (Actuonda) moulard@actuonda.com @Radio_20
www.bigmediaconnect.es

Published in Technology , Education
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  • 1. Big Data, Big Media THE NEW PARADIGM OF THE MULTIMEDIA CONTENT MANAGEMENT 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. Perfect Memory – The Team 2BIG DATA - BIG MEDIA
  • 3. 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 3BIG DATA - BIG MEDIA
  • 4. The context of Big Data Big Data is a buzz word that hide different realties : - Volume issue (data volume, media volume), - Interoperability that serves the ubiquity of the content (anywhere, anytime, anybody), - Diversity of sources (MAM, DB, internal, external, structured, unstructured). Deals with volume, ubiquity and diversity Le 09/10/2013 BIG DATA - BIG MEDIA 4
  • 5. The context of Big Data Volume is an old issue : - Upstream: Require to solve the administration, the exploitation and the indexing of the content, - Downstream: provide mapping and representation of the content. A posteriori, analytics, Data mining Health, Oil, Retail (see the the diaper & beer case) Interoperability is a consequence of the raising of the Internet: - Cooperation, communities, coworking, - It requires standards (XML Schema, MPEG 4,7,21, MXF, OAIS, RDF. Deals with volume, ubiquity and diversity - It requires standards (XML Schema, MPEG 4,7,21, MXF, OAIS, RDF. A priori, structuration of the content Media New movie workflow (production to distribution) Diversity of sources: - Structuration, meaning, - Linked data. A priori, knowledge processing Media, industrie, Education Web 3.0 paradigm (Semantic, LOD, Open Data) Le 09/10/2013 BIG DATA - BIG MEDIA 5
  • 6. Facts… 1. Multi media contents are growing massively 2. Media inventories are managed by heterogeneous systems 3. Indexation, if done, is mainly done manually - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Media 2000 2005 ∞∞ Media Asset Management Systems time 6BIG DATA - BIG MEDIA
  • 7. Facts… … generating deep archives issue …. Main facts Lost opportunities … and management issue Waste of time 7BIG DATA - BIG MEDIA
  • 8. Media Challenge : New needs 8BIG DATA - BIG MEDIA
  • 9. Media Challenge : new comers The Media-brands 9BIG DATA - BIG MEDIA
  • 10. 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 10BIG DATA - BIG MEDIA
  • 11. 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, • Transferable platform 11BIG DATA - BIG MEDIA
  • 12. Semantic layer cake From modeling to exploitation User Interface USAGE 360° Rendering PUBLISHING Inference rules ENRICHMENT Semantic Data PRODUCTION, INGEST Ontology & knowledge base MODELING 12BIG DATA - BIG MEDIA
  • 13. Semantic valorization Why? • From DATA to information • Understand information and build the knowledgeknowledge • Provide solutions to value the content. 13BIG DATA - BIG MEDIA
  • 14. Semantic valorization Bring semantic to the media Data Info Knowledge 2 persons, face to face, smiling and laughing Semantic system Data Info Knowledge 2 persons, face to face, smiling and laughing • Samuel L. Jackson (Person) • Leonardo DiCaprio (Person) • Thumbnail from “Django unchained” • Quentin Tarantino behind the camera 14BIG DATA - BIG MEDIA
  • 15. Enhancement & Enrichment From flat to rich content ENTITY « Organisation » URI: MMC#RTBF#6756593 Name : RTBF ENTITY « Person » URI: MMC#RTBF#67554778 Name : Barthe First name: François ENTITY « Person » URI: MMC#RTBF#6753 Name : Zidane First name: Zinedine « Works for » « Talk about » Enrichment3 Enhancement semantic 2Table « Person » Id : #67554778 Name : Barthe First name: François Employer : RTBF Description : > Worked on Zidane’s bio. 1 ENTITY « Person » URI: MMC#RTBF#67554778 Name : Barthe First name : François Description : > Worked on Zidane’s bio. ENTITY « Organisation » URI: MMC#RTBF#6756593 Name : RTBF « Work for » for » semantic Enrichment semantic 3 Le 09/10/2013 15BIG DATA - BIG MEDIA
  • 16. Inference Perfect Memory’s data bases : • Increasing of amount of information in time, • Increasing of quality of links in time. Preserve, enrich and sharing of knowledge. Capitalisation of knowledge Semantic Inference 4 Semantic negentropic DB News facts Inference rules 16BIG DATA - BIG MEDIA
  • 17. Exploiting the knowledgeExploiting the knowledge From Pr. Bachimont – University of Technology of Compiègne Le 09/10/2013 17BIG DATA - BIG MEDIA
  • 18. Linked Open Data Consolidating the distributed knowledge RTBF 18BIG DATA - BIG MEDIA
  • 19. Process management OSB workers InterOp-Window A service on the OSB 1. Manager: Identification of request 2. Manager: Main process instantation 3. Manager: Sub process instantiation 4. Manager :Tasks instantiation 5. Manager: IOW calls 6. Guichets#1 : Execution of tasks and works 7. … 8. Guichets#n : Execution of tasks and works Treatment request 8. Guichets#n : Execution of tasks and works 19BIG DATA - BIG MEDIA
  • 20. Semantic Player Rendering the semantic links InterOp-Guichet Player SémantiqueNetworkNetwork OSB OSB OSB OSB Enhancement, Repurposing & Exploitation of audiovisual contents. 20BIG DATA - BIG MEDIA
  • 21. An architecture scalable, distributed Introducing the Semantic Middleware approach 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 backbone of the middleware (3) Any Bases ingested, or functionalities connected via an InteOperability Windows (GIO) becomes a semantic ressource for the Middleware (2) (3) 21BIG DATA - BIG MEDIA
  • 22. Flexibility & scalability of the middleware Control Enrichment Extraction Expressivity Le 09/10/2013 22BIG DATA - BIG MEDIA
  • 23. RTBF Annotation & search interfaces Features: Breakthrough user friendly interface for big data visualization Graphical browsing in big data content (media and metadata) 23BIG DATA - BIG MEDIA
  • 24. Radio France Tablet Interface Connection: Building the contextualization of the display according to the Role and Skill of the connected user. 24Big Data - Big Media
  • 25. The PROFILE : knowledge capitalization YourYour Data StructureData Structure YourYour Media LibraryMedia Library Linked Open DataLinked Open Data YOURYOUR KNOWLEDGEKNOWLEDGE 25BIG DATA - BIG MEDIA
  • 26. The Middleware features … • Automatic linking with external related contents, BeforeBefore After • • Automatic knowledge validation, • Cross-browsing in broadcasters’ MAMs. After Media Processing 26BIG DATA - BIG MEDIA
  • 27. The semantic middleware approach Le 09/10/2013 BIG DATA - BIG MEDIA 27
  • 28. BIG DATA – BIG MEDIA THE NEW PARADIGM OF THE MULTIMEDIA CONTENT MANAGEMENT Frédéric Colomina Business Development Frederic.colomina@perfect-memory.com @perfect__memory Steny Solitude CEO Steny.solitude@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
  • 29. Organizadores Sponsor platinum Sponsor Gold Con el apoyo de Socio tecnológico Nicolas Moulard, Director de Actuonda moulard@actuonda.com Tel : +34 699 248 200 @Radio_20 www.bigmediaconnect.es