Institutional Services and Tools for Content, Metadata and IPR Management
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Institutional Services and Tools for Content, Metadata and IPR Management

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Ingest a large range metadata formats (XML based or Dublin Core, METS, MPEG-21, etc.) coming from different channels (http, ftp, oai-pmh, etc.) and content files >500 ff. ...

Ingest a large range metadata formats (XML based or Dublin Core, METS, MPEG-21, etc.) coming from different channels (http, ftp, oai-pmh, etc.) and content files >500 ff.
Perform human content enrichment, translations, validation; comments; social media, rating; promoting; publication; corrections; assessment, etc.
Perform automated activities, technical parameters (duration, size, etc.), descriptors, indexing, translations, VIP names, geonames, LOD, assessment, IPR , verification
IPR modelling, assignment and verification.
Harmonising the activities of human and automated processing
Scale up of the back office architecture to cope with a large number of transactions
Support and model one or more workflows

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    Institutional Services and Tools for Content, Metadata and IPR Management Institutional Services and Tools for Content, Metadata and IPR Management Presentation Transcript

    • Institutional Services and Tools for Content, Metadata and IPR Management P. Bellini, I. Bruno, P. Nesi, M. Paolucci Departmento di Ingegneria dell’Informazione University of Florence Via S. Marta 3, 50139, Firenze, Italy tel: +39-055-4796523, fax: +39-055-4796363, cell: +39-335-5668674 Paolo.nesi@unifi.it http://www.disit.dinfo.unifi.it/ 1DMS 2013, UK, Paolo Nesi, 2013
    • Automated Back office ANY content -PC, MACos, linux, … -iPhone, iPod, Windows Mobile, ….… Library Library partner Library partner Content archive Content archiveContent archive 2 DMS 2013, UK, Paolo Nesi, 2013 Content Agg. Content Services ANY content
    •  Ingest a large range metadata formats (XML based or Dublin Core, METS, MPEG-21, etc.) coming from different channels (http, ftp, oai-pmh, etc.) and content files >500 ff.  Perform human content enrichment, translations, validation; comments; social media, rating; promoting; publication; corrections; assessment, etc.  Perform automated activities, technical parameters (duration, size, etc.), descriptors, indexing, translations, VIP names, geonames, LOD, assessment, IPR , verification  IPR modelling, assignment and verification.  Harmonising the activities of human and automated processing  Scale up of the back office architecture to cope with a large number of transactions  Support and model one or more workflows DMS 2013, UK, Paolo Nesi, 2013 4
    •  Informative Content  Video, audio, images, documents  3D, animations, Braille  Slide, Video-Slide, courses  eBook, ePub, Mpeg21, intelligent  Aggregated Content:  Playlist, Collections  Annotations, Synchronization  Support and networking content:  Blog, WebPage, Events, comments, forum, votes, messages, … 5DMS 2013, UK, Paolo Nesi, 2013 comments rating relationships technical Dynamic recommend …………… • Performance • Master classes • Scene Sketches • Scenography • Scenes • Private lives of artists • Scores • Braille • BackStage Stills • Choreography • Morals • Poster • Booklets • Magazines Music • Audio ballets
    • Ingestion and Harvesting ECLAP Metadata Ingestion Server O A I P M H Resource Injection Content Retrieval Database + semantic database Library Library partnerLibrary partner Archive partnerArchive partnerArchive partner ECLAP Social Service Portal 6 IPR Wizard/CAS AXCP back office services Content Analysis Content Indexing and Search Metadata Editor Content Aggregation and Play Content Processing Metadata Export Semantic Computing and Sugg. Content Upload Management Content Upload Networking Social Network connections Metadata E-Learning Support DMS 2013, UK, Paolo Nesi, 2013
    • 7 DMS 2013, UK, Paolo Nesi, 2013
    • 8 DMS 2013, UK, Paolo Nesi, 2013
    • DMS 2013, UK, Paolo Nesi, 2013 9  Back-office Ingestion Architecture IngestionECLAP Metadata Ingestion O A I P M H Harvesting Resource Injection Content Retrieval Ingestion Database AXCP Uploader Library Library partnerLibrary partner Archive partnerArchive partnerArchive partner local ECLAP Social Service Portal
    • DMS 2013, UK, Paolo Nesi, 2013 10 UNDER-AXCP UPLOADED UNDER-IPR UNDER- ENRICH UNDER- VALIDATION UNDER- APPROVAL PUBLISHED WFIPR By IPR wizard IPR edit IPR done Upload rule Metadata edit Automated enrich rule Assessment rule Final publication rule WFENRICHER By Metadata Editor Translations, Content update/adaptation, Metadata analysis & validation By AXCP Backoffice WFVALIDATOR By Metadata Editor WFPUBLISHER Manually or by AXCP Backoffice Validation request PROPOSED Validation done not approved Upload via form Ingestion rule Administrative database Publishing database Publish to Europeana Enrichment done Enrichment done By AXCP Backoffice Moderated Upload Professional & Institutions Upload
    • 11DMS 2013, UK, Paolo Nesi, 2013
    • DMS 2013, UK, Paolo Nesi, 2013 12
    • 13DMS 2013, UK, Paolo Nesi, 2013
    •  Formalize the right per content access  Stream / progressive download  Download  Embed  user device: PC, mobile, iPad, etc.  resolution per Video: low, med, HD  content kind: audio, video, images, document, etc.  metadata license (Creative Commons, etc.);  publisher ECLAP page  Europeana.Rights  IPR ingestion identifier 14DMS 2013, UK, Paolo Nesi, 2013
    • VIDEO permission (FINAL) EX 1 EX 2 EX 3 EX 4 Video download PC HD Yes Video play PC HD  Video download-PC- LD and MD   Video play-PC- LD and MD  Yes Yes  Video download-mobile-Browser  Yes Video play-mobile-Browser     Video download-mobile-Apps Content Organizer  Yes  Video play-mobile-Apps Content Organizer     VALUECONTROL 15DMS 2013, UK, Paolo Nesi, 2013
    •  Workflow Roles:  24 enrichers (WFENRICHER), 6 validators (WFVALIDATOR), 23 IPR users (WFIPR) and 9 publishers (WFPUBLISHER).  Data flow in last 20 months  706,052 workflow transitions for 117,861 content items  Average of: 6 transitions per content  Max: 104 transitions per content.  performed in 653 days, avg 1,014 transitions per day  maximum of 13,162 transitions in one day,  maximum of 14 different virtual nodes on AXCP grid, DMS 2013, UK, Paolo Nesi, 2013 17
    •  172300 objects  23755 Identified Names  0,6% of user names into ECLAP  9,95% of VIP names into dbPedia (2151 names)  4294 names associated with dbPedia DMS 2013, UK, Paolo Nesi, 2013 18
    •  >170000 objects  35 different models  970.000 dates classified to several different semantics DMS 2013, UK, Paolo Nesi, 2013 19
    • 20 DMS 2013, UK, Paolo Nesi, 2013
    •  67 Differente IPR models  40 non public model with some restriction  27 are public models, different CC profiles  68% of content is associatetd with Public IPR Model DMS 2013, UK, Paolo Nesi, 2013 21 0 10000 20000 30000 40000 50000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 2 Public Not Public
    • Permission User type public group educ./research only play/access 11 13 19 download & play 3 8 11 no permission 19 12 4 DMS 2013, UK, Paolo Nesi, 2013 22  Permission based on user profile  Mainly Education and Research
    •  Typically workflows and CMS for aggregator are manually managed and do not address enrichment  The proposed solution to automate the content workflow for multipartner institutions has:  Processed over than 170.000 elements in 750 days, ingesting, enriching 35 collections from 15 countries in 13 languages  Reduced the number of manual interventions for: enrichment, assessment, validation and publication  Proposed an integration with a flexible IPR model and IPR Wizard tool for Conditional Access profiling and distribution  Only 1 IPR problem has been detected claimed. DMS 2013, UK, Paolo Nesi, 2013 23