The objective of this workpackage is to support discovery and use by improving metadata through innovative methods including semantic enrichment and crowdsourcing. It coordinates the design and implementation on mechanisms to improve the quality of existing metadata and contextual information. This will support enhanced exploration, deepen understanding of the collections, and will increase end-user engagement. Significantly increase quality of existing and new Europeana metadata for audio and audio-related items though: (a) active participation with existing audiences; (b) machine-driven tools. Specific goals • Offer tools for metadata tagging and contextualisation to the wider community. This will (1) increase quality and user satisfaction in terms of content discovery; (2) promote increased engagement between institutions and their audiences. • Apply semantic web technologies to enable enrichment of the Europeana Sounds collections. This will increase quality of the metadata and user satisfaction in terms of content discovery. • Collaborate with Wikimedia chapters in Europe to add contextual knowledge on the Europeana Sounds collection. Six edit-a-thons (campaigns that aim to create wiki pages on focussed areas) will be organised in year two and three of the project. This will (1) add a layer of in-depth knowledge to the collections presented online; (2) strengthen links between Europeana, the Europeana Network and the international Wikipedia community. • Align music scores to text, to forge a dynamic connection between currently separated collections. By allowing for new types of exploration, the value for end-users of both the multimedia and digitised paper-based resources will be increased. • Explore possibilities of music information retrieval to support innovative, language independent exploration of audio collections. • Put in place policies and (in connection with WP5) infrastructural preconditions allowing enrichments to be re-ingested in the information systems of the contributing archives, wherever relevant.

1. WP2: Enrichment & Participation
Maarten Brinkerink, WP2 Lead
Nick Stanhope, WAWWD
Simone Fonda, Net7
Johan Oomen, NISV
Sergiu Gordea, AIT
17 February 2014, London

2. Work Package 2 will support
discovery and use by improving
metadata through innovative
methods including semantic
enrichment and crowdsourcing
Lead by NISV, with EF, NTUA, AIT,
NET7, WAWWD, all content partners;
also Wikimedia chapters

3. Objectives
 Support discovery and use by improving metadata
through innovative methods including semantic
enrichment and crowdsourcing.
• Design and implement mechanisms to improve the quality of
existing metadata and contextual information. This will
support enhanced exploration, deepen understanding of the
collections, and will increase end-user engagement.
• Significantly increase quality of existing and new Europeana
metadata for audio and audio-related items though:
• (a) active participation with existing audiences;
• (b) machine-driven tools.
 Allowing enrichments to be re-ingested in the
information systems of the contributing partners.

4. Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Historypin
Historypin
(crowdsourcing)
(crowdsourcing)
Content provider 11
Content provider
Content provider nn
Content provider
enriched metadata
Wikimedia
Wikimedia
chapters
chapters
Semantic
Semantic
enrichment
enrichment
Europeana Sounds
Europeana Sounds
platform
platform
Europeana
Europeana
Channel
Channel
(crowdsourcing)
(crowdsourcing)
Third party playout
Third party playout

5. Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Historypin
Historypin
(crowdsourcing)
(crowdsourcing)
Content provider 11
Content provider
Content provider nn
Content provider
enriched metadata
Wikimedia
Wikimedia
chapters
chapters
Semantic
Semantic
enrichment
enrichment
Europeana Sounds
Europeana Sounds
platform
platform
Europeana
Europeana
Channel
Channel
(crowdsourcing)
(crowdsourcing)
Third party playout
Third party playout

6. Semantic Enrichment (1) automatic and
(2) user-contributed annotations
• uncover/highlight connections between
recordings and extract knowledge from musical
relationships.
• suggest collections based on artists'
collaborations, influences, shared members,
genres etc.
• mine into Europeana system logs and linking
with external resources (e.g. DBpedia) to identify
relationships between music related concepts
(i.e. make use of Relfinder and the Semantic
Shortcuts algorithm developed in Assets).

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8. Typed relations among different kind of
objects and entities

9. Define new knowledge

10. Link to the Web of Data, and
access its data

11. Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Historypin
Historypin
(crowdsourcing)
(crowdsourcing)
Content provider 11
Content provider
Content provider nn
Content provider
enriched metadata
Wikimedia
Wikimedia
chapters
chapters
Semantic
Semantic
enrichment
enrichment
Europeana Sounds
Europeana Sounds
platform
platform
Europeana
Europeana
Channel
Channel
(crowdsourcing)
(crowdsourcing)
Third party playout
Third party playout

12. Collaborating with Wikimedia Chapters
Photo of the Wiki Loves Sound Edit-a-Thon in the Netherlands

13. Example (Cat’s meow)

14. Reuse in Wikipedia

15. Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Historypin
Historypin
(crowdsourcing)
(crowdsourcing)
Content provider 11
Content provider
Content provider nn
Content provider
enriched metadata
Wikimedia
Wikimedia
chapters
chapters
Semantic
Semantic
enrichment
enrichment
Europeana Sounds
Europeana Sounds
platform
platform
Europeana
Europeana
Channel
Channel
(crowdsourcing)
(crowdsourcing)
Third party playout
Third party playout

16. Crowdsourcing (enrichment)
• ‘happens’ on multiple sites, where users are!
• two user groups (general public and experts)
-
Historypin
-
Institutional Portals
-
Europeana Channel (see also WP4 presentation)

17. Crowdsourcing: approach
Crowdsourcing: requirements and policy Definition (T2.1.1)
The requirements will differentiate between two target
groups: the general public and experts
Crowdsourcing: operationalisation and Evaluation (T2.1.2)
This subtask oversees the successful deployment and
end-user evaluation of the crowdsourcing infrastructure: on the
Europeana portal, the individual partner sites and on Historypin.
Activities include creating training materials and one hands-on
workshop.

20. Web-based game for the general public
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YUMA (now Annotorious) from AIT

21. Enrichment on institutional portals
ple
ple
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am
exx
e
Europeana search widget by EF

22. Enrichment on Europeana Sounds
Channel
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ple
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Example of the SoundCloud player, with social tagging functionality

23. Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
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enContent provider n
Content provider 11
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Content provider
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Historypin
Historypin
(crowdsourcing)
(crowdsourcing)
enriched metadata
Wikimedia
Wikimedia
chapters
chapters
Semantic
Semantic
enrichment
enrichment
Europeana Sounds
Europeana Sounds
platform
platform
Europeana
Europeana
Channel
Channel
(crowdsourcing)
(crowdsourcing)
Third party playout
Third party playout

24. Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Corporate portal
Corporate portal
(crowdsourcing)
(crowdsourcing)
Historypin
Historypin
(crowdsourcing)
(crowdsourcing)
Content provider 11
Content provider
Content provider nn
Content provider
enriched metadata
Wikimedia
Wikimedia
chapters
chapters
Semantic
Semantic
enrichment
enrichment
Europeana Sounds
Europeana Sounds
platform
platform
Europeana
Europeana
Channel
Channel
(crowdsourcing)
(crowdsourcing)
Third party playout
Third party playout

25. Innovative exploration pilots: audio
information retrieval and dynamic
linking

26. Linking music to scores
Identify related resources (audio, video, music scores,
vocabularies)
Link audio segments to music scores
 Automated: midi content to sheet music (digital)
 Semi automatic: convert content and music scores to
Midi/MusicXML
 Manual: markup audio and digitized music scores
Typical applications:
 Learning to play an instrument (hear, follow, play)
 Compositions (compose, follow, hear )
27
17.02.14

27. Music information retrieval
Index and retrieve music content
 Extract audio features: timbre, chords, harmonies, melody, main pitch,
beats per minute or rhythm




Index features and retrieve similar content
Music categorization
Evaluation using Europeana Sounds content
Sound recognition (birds)
Typical applications:
 Search/explore music repositories
 Music classification and recommendation
 Intellectual property protection
28
17.02.14

28. Existing tools (open source)
 OMR: Audiveris, OpenOMR
 Midi and scores synchronization: midisheetmusic,
musicscore
 Feature extraction: JMir, MirToolbox(Mathlab), RP-Extract
 Indexing and retrieval: Clubmixer, Marysas

29. WP2: deliverables
No
Title
Delivery month
D2.1
Crowdsourcing infrastructure & exchange
policy
6
D2.2
Functional design of semantic enrichment
7
D2.3
Linking pilot delivery report (software,
documentation)
14
D2.4
Crowdsourcing infrastructure v1 assessment
17
D2.5, 8
GLAM-wiki collaboration progress reports
21, 34
D2.6
MIR pilot report
22
D2.7
Crowdsourcing evaluation & impact
assessment
30
D2.9
Evaluation report on semantic enrichment
implementation
36

30. Thank you