From Findability to Awareness: Metadata in Music and Technology Enhanced Learning.

FROM FINDABILITY TO
AWARENESS: METADATA IN
MUSIC AND TECHNOLOGY
ENHANCED LEARNING
Vinden en beseffen: Metadata
in muziek en E-learning
Sten Govaerts

Promotor: Prof. dr. ir. Erik Duval
Co-promotor: Dr. Katrien Verbert
1
Wednesday 12 September 12

http://www.britannica.com/bps/media-view/96031/1/0/0 2

http://www.ﬂickr.com/photos/markkelley/1022720488/ 4

METADATA
• title: Maiden Voyage
• main artist: Herbie Hancock
• artists: Freddie Hubbard, George
Coleman, Ron Carter, Anthony Williams
• record label: Blue Note, Capitol
Records
• instruments: trumpet, tenor
saxophone, piano, bass, drums.
• recording date: March 17, 1965
• studio: Van Gelder Studio, New Jersey
• version: remastered by Rudy Van Gelder
5

CONTEXT.

6

OVERVIEW.

7

OVERVIEW.

RQ1: How can metadata be
leveraged to provide efﬁcient and
7
effective access to content?

OVERVIEW.
RQ2: How can metadata creation
be made more scalable?

7

OVERVIEW.

RQ3: How can metadata
standards be selected for speciﬁc
functionalities of applications?
7

OVERVIEW. can attention
RQ4: How
metadata be leveraged to improve
awareness and self-reﬂection?

7

DOMAINS.

Music Technology-enhanced
Learning (TEL)

8

STEP 1 – DEFINE.

9

STEP 1 – DEFINE.

RQ3: How can metadata
standards be selected for speciﬁc
functionalities of applications?
9

METADATA SCHEMA
<rdf:RDF
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:dc="http://purl.org/dc/elements/1.1/">
<rdf:Description rdf:about="http://media.example.com/audio/guide.ra">
<dc:creator>Herbie Hancock</dc:creator>
<dc:title>Maiden Voyage</dc:title>
Dublin Core

<dc:contributor>Freddie Hubbard</dc:contributor>
<dc:contributor>George Coleman</dc:contributor>
<dc:contributor>Ron Carter</dc:contributor>
<dc:contributor>Anthony Williams</dc:contributor>
<dc:description>Maiden Voyage is the ﬁfth album led by jazz musician
Herbie Hancock, and was recorded by Rudy Van Gelder on May 17, 1965
for Blue Note Records.</dc:description>
<dc:date>1965-03-17</dc:date>
<dc:publisher>Blue Note</dc:publisher>
<dc:type>Music album</dc:type>
<dc:format>audio/mp3</dc:format>
<dc:rights>copyrighted by Capitol Records, Inc.</dc:rights>
</rdf:Description>
</rdf:RDF>
step 1 - deﬁne. 10

METADATA SCHEMA
@prefix mo: <http://purl.org/ontology/mo/> .
@prefix : <#> .
@prefix dc: <http://purl.org/dc/elements/1.1/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix event: <http://purl.org/NET/c4dm/event.owl#> .

:work
Music Ontology

a mo:MusicalWork ;
dc:title "Herbie Hancock - Maiden Voyage" .

:performance
a mo:Performance ;
dc:title "Maiden Voyage" ;
mo:performance_of :work ;
mo:performer <http://dbpedia.org/page/Herbie_Hancock> ;
dc:date "1965-03-17"^^xsd:date .
event:place <http://dbpedia.org/page/Van_Gelder_Studio> ;
mo:performance_of <http://dbpedia.org/page/
Maiden_Voyage_(Herbie_Hancock_album)> .
mo:recorded_as [
a mo:Signal ;
mo:published_as :track1 ;
dc:title "Original recording at the Van Gelder Studio" ;
].

METADATA SCHEMA
:track1

a mo:Track ;

mo:track_number 1 ;

dc:title "Maiden Voyage".

:signal mo:time [
tl:duration "PT2M14S"^^xsd:duration;
Music Ontology

tl:timeline :tl;
].

:chorus1 a ps:Chorus;
rdfs:label "First chorus";
event:time [
tl:timeline :tl;
tl:start "PT0S"^^xsd:duration;
tl:duration "PT9S"^^xsd:duration;
].

:verse1 a ps:Verse;
rdfs:label "First verse";
event:time [
tl:timeline :tl;
tl:start "PT9S"^^xsd:duration;
tl:duration "PT33S"^^xsd:duration;
step 1 - deﬁne. ]. 11

FINDING AN APPROPRIATE
METADATA SCHEMA...

Corthaut, Nik; Govaerts, Sten; Verbert, Katrien; Duval,
Erik. Connecting the dots: music metadata generation,
schemas and applications. ISMIR 2008.

...FOR THE RIGHT
APPLICATION.

Corthaut, Nik; Govaerts, Sten; Verbert, Katrien; Duval,
Erik. Connecting the dots: music metadata
generation, schemas and applications. ISMIR 2008.

STEP 2 – CREATE.

14

STEP 2 – CREATE.

RQ2: How can metadata creation
be made more scalable?
14

country of origin of an artist.
http://www.ﬂickr.com/photos/twicepix/4437851857/
15

COUNTRY & CONTINENT
• useful for:

• subgenres
• popularity
• recommendations

step 2 - create. 16

COUNTRY & CONTINENT
• useful for:

• subgenres
• popularity
• recommendations

• expensive to annotate

step 2 - create. 16

COUNTRY & CONTINENT
• useful for:

• subgenres
• popularity
• recommendations

• expensive to annotate

• very little existing research

step 2 - create. 16

MASHUP.
google maps

freebase
last.fm google app
engine
twitter last.fm

last.fm yahoo! pipes last on am/fm

website
dapper youtube

step 2 - create. 17

Three data sources last.fm 91%
• last.fm freebase 90%
• freebase biography 71%
• biographies combination 77%
0% 25% 50% 75% 100%
Accuracy

last.fm 7%
Evaluation: freebase 26%
ground truth data biography 55%
set of 11275 artists combination 59%
Govaerts, Sten; Duval, Erik. A Web-based approach to
determine the origin of an artist. ISMIR 2009. 0% 15% 30% 45% 60%
Coverage
step 2 - create. 18

Three data sources last.fm 91%
Ennio Morricone (born 10 November 1928 in Rome) is an Italian
• last.fm freebase
composer especially noted for his film scores. He has composed the 90%
scores of more than 500 films and TV series. Although only 30 of
• freebase biography 71%
these are for Western films, it is for this work which he is best known.
Morricone’s sparse style of composition for the genre is particularly
• biographies combination 77%
exemplified by the soundtracks of the classic spaghetti westerns The
Good, the Bad and the Ugly (Sergio Leone, 1966) and Once Upon A
Time In The West (Sergio Leone, 1968). 0% 25% 50% 75% 100%
[...] Accuracy
In 2003 he scored the Japanese Taiga drama about Miyamoto
Musashi, Japan’s legendary warrior. In 2005 he was on a world tour
last.fm 7%
with the Roma Sinfonietta Orchestra, touring from cities like New

Evaluation:York, Bilbao, Bratislava and Tokyo. In 2006, Morricone collaborated
with Morrissey by composing the string part for 26%
freebase
his song “Dear God
ground truth data
Please Help Me”, recorded in Rome’s Forum Music Village Studios.
In recognition of his vast body of work and dedication, Morricone 55%
biography
set of 11275 artists
received an honorary Academy Award in 2007; Morricone had
received nominations for Best Original Score in the past, but had 59%
combination
failed Erik. A Web-based approach to
Govaerts, Sten; Duval, to win.
0% 15% 30% 45% 60%
determine the origin of an artist. ISMIR 2009.
Coverage
step 2 - create. 18

Three data sources
• last.fm
• freebase
• biographies
last.fm

freebase

biography

combination
71%
77%
91%
90%
}
0% 25% 50% 75% 100%
Accuracy

last.fm 7%
Evaluation: freebase 26%
ground truth data biography 55%
set of 11275 artists combination 59%
Coverage
step 2 - create. 18

Three data sources
• last.fm
• freebase
• biographies
last.fm

freebase

biography

combination
71%
77%
91%
90%
}
0% 25% 50% 75% 100%
Accuracy

Evaluation:
ground truth data
set of 11275 artists
last.fm

freebase

biography

combination
7%
26%
55%
}
59%
Coverage
step 2 - create. 18

LAST.FM MASHUP

http://www.cs.kuleuven.be/~sten/lastonamfm
step 2 - create. 19

musical genre.
http://www.ﬂickr.com/photos/7593077@N03/5076100406/in/photostream/ 20

USING SEARCH ENGINES

step 2 - create. 21

CLASSIFICATION WITH
SEARCH ENGINES
using co-occurrence

M. Schedl, T. Pohle, P. Knees, G. Widmer, “Assigning and Visualizing
Music Genres by Web-based Co-occurrence Analysis”,
Proceedings of the 7th International Conference on Music
Information Retrieval, 2006, pp. 260-265.
step 2 - create. 22

step 2 - create. 23

Rock: Jazz:

Blues: Pop:

Country: Metal:

step 2 - create. 23

Rock: Jazz:

0,013 0,013
Blues: Pop:

0,009 0,015
Country: Metal:

0,009 0,005
step 2 - create. 23

RESULTS
• 1st results were much worse

• what happened?

• re-run the original experiment

• evaluate on the same data set: 1995 artists and 9 genres.

• different search engines: Google,Yahoo! and Microsoft.

• over time: 8 times over a period of 36 days.
step 2 - create. 24

step 2 - create. 25

step 2 - create. 26

WHAT TO USE?
• use Google when it’s stable else rely on Yahoo!

• when is it stable? test with a small set

• some artists get classiﬁed incorrectly on bad days

• compare the accuracy achieved with the test set to the
average.

step 2 - create. 27

WHAT TO USE?
• use Google when it’s stable else rely on Yahoo!

• when is it stable? test with a small set

• some artists get classiﬁed incorrectly on bad days

• compare the accuracy achieved with the test set to the
average.

Govaerts, Sten; Corthaut, Nik; Duval, Erik. Using search engine for
classiﬁcation: does it still work? adMIRe WS, ISM2009.

step 2 - create. 27

STEP 4 – UTILISE.

28

STEP 4 – UTILISE.
Ch 5 & 6

28

FEDERATED SEARCH.

Govaerts, Sten; El Helou, Sandy; Duval, Erik; Gillet, Denis. A federated
search and social recommendation widget. SRS WS, CSCW 2011.
Govaerts, Sten; Verbert, Katrien; et al. Towards Responsive Open Learning
Environments: the ROLE Interoperability framework. EC-TEL 2011.
step 4 - utilise. 29

CONTEXT
• Personal Learning Environment:
• customizable
• re-use, creation & mashup of tools, resources
• enable users to access content
• in different contexts


WHAT’S A WIDGET ?!?


STEP 5 & 6 – CAPTURE &
PERSONALISE.

32

STEP 5 & 6 – CAPTURE &
PERSONALISE.
Ch 5 & 6

32

ATTENTION METADATA

Attention metadata does not describe
the content itself, but what people do
with the content.

step 5 & 6 - capture/personalise. 33

ATTENTION METADATA

Attention metadata does not describe
the content itself, but what people do
with the content.

copyright by Warner Bros. Pictures


UI.


SOCIAL RECOMMENDATIONS.

Govaerts, Sten; El Helou, Sandy; Duval, Erik; Gillet, Denis. A federated
search and social recommendation widget. SRS WS, CSCW 2011.
Govaerts, Sten; Verbert, Katrien; et al. Towards Responsive Open Learning
Environments: the ROLE Interoperability framework. EC-TEL 2011.

PAGE RANK
HYPERLINK
WEB
SITE
Rank of node i:

A node is important if and only if many other
important nodes point to it


OUR CASE
hare
d R1
d /s
save
saved/shared
d
en tion
Erik R2
fr i e c dis
n like
c on d
lik
ed
R3
d n
Sandy
ien ctio
fr e
c on
n lik
ed
R4

Sten R5


THREE CASE STUDIES
1 2 3


KU LEUVEN & EPFL

• 15 PhD students.


KU LEUVEN & EPFL

• usability, satisfaction,
usefulness


KU LEUVEN & EPFL

usefulness
• usefulness of recommendations: 11/14 pro.


KU LEUVEN & EPFL

usefulness
• user satisfaction: System Usability Scale (SUS) & MS
Desirability Toolkit


KU LEUVEN & EPFL

usefulness
• SUS score: 66,25%


KU LEUVEN & EPFL

usefulness
KU Leuven: high (75%)
• SUS score: 66,25%
EPFL + one KU Leuven: low (50%)

WHY THE DIFFERENT SUS?

• 1st phase by 2 interviewers


WHY THE DIFFERENT SUS?
• issues:

• distraction from unrelated widgets

• layout too dense

• height of widgets too small

• not evaluating the widget but the
whole experience...


DESIRABILITY...


FESTO

• LMS (CLIX) extended with widgets

• 25 heterogeneous participants

• evaluation setup:
1. video introduction to the new system
2. period of experimentation
3. questionnaire

FESTO RESULTS


FESTO RESULTS

88% would recommend it to their colleagues
81% agreed that it helps them to be more effective


JIAO TONG UNIVERSITY

• offers higher education for adults with a full-time job

• early prototype with

• evaluation setup:

1. task list (ETA 15 mins)

2. questionnaire (in Chinese) (partially from ResQUE)


RESULTS
• ran over 3 weeks, 13 respondents

• results for federated search widget:
• 69% used the federated search widget
• 56% found the recommendations relevant to the course
• 38% wanted to continue using the federated search widget
• Personal learning environment results
• 23% found it useful for the course
• 39% found it easy to use, 15% found it navigationally consistent
• 46% were satisﬁed with the personal learning environment

WHY?

• an established LMS augmented with PLE features
brand new system
• cultural differences?
• slow internet connection
(long loading and querying times)

• lesson learned: the choice of evaluation environment is very
important

WHY?

brand new system
users perceive federated search as useful and
• slow internet connection
effective IF the content in the repositories relates
(long loading and querying times)
to their tasks.
[Belliston et al., 2007], [Korah et al., 2010], [Gore, 2008]

important

WHY?

brand new system
our evaluation indicates that users beneﬁt from
users perceive federated search as useful and
• slow internet connection recommendations.
the social
effective IF the content in the repositories relates
recommendations from friends are preferred over
(long loading and querying times) to their tasks.
system recommendations. [Shinha et al., 2001]
[Belliston et al., 2007], [Korah et al., 2010], [Gore, 2008]

important

STEP 7 – CREATE AWARENESS.

48

Ch 7

48

Ch 7

RQ4: How can attention
metadata be leveraged to improve
awareness and self-reﬂection?
48

PROBLEM

http://www.ypfp.org/classroom

step 5 & 7 - capture/create awareness. 49

STUDENT ACTIVITY METER
• visualisations of attention metadata
evaluation
• self-monitoring for learners

design

implementation


evaluation

• awareness for teachers
design

implementation


evaluation

design
• time tracking
implementation


evaluation

design
• time tracking
implementation
• learning resource use and recommendations


evaluation

design
• time tracking
implementation
• learning resource use and recommendations

• part of Learning Analytics research [ACM LAK conf., Siemens 2011, Duval 2011]

Govaerts, Sten; Verbert, Katrien, Duval, Erik; Pardo, Abelardo. The
Student Activity Meter for Awareness and Self-reﬂection. CHI 2012.

demo...

51 http://www.leveraas.com/


demogra evaluation design
negative positive
phics goal changes
•↑learnability
usability,
•↓errors
12 CS satisfaction, small usability
I. 1st iteration •good satisfaction
students preliminary issues
•usefulness
usefulness
positive


ITERATION TWO &
THREE

• CGIAR: 19 teachers - LAK: 12

• An online survey about usefulness, teacher issues and how
the tool can resolve these.


CGIAR LAK
1 2 3 4 issue for2 add- issue for add-
5 1 3 4 5
teacher ressed teacher ressed
Provide feedback to the
Provide feedback to the students
students ✔ ? ✔ ✔
Being aware of what
Being aware of whatdoing
students are students are doing ✔ ✔ ✔ ?
✗ ✗
Knowing about collaboration
Knowing and communication * and communication
about collaboration ✔ ✔
?
Knowing which documents
Knowing are used and how much used and how much
which documents are ✔ ✔ ✔
? ✗ ?
Knowing how and when
Knowing online and whenbeen used have been used
how tools have online tools ✔
Finding the students who
are not doing well
Finding the students who are not doing well ✔ ? ✔ ?
Finding the best students
Finding the best students
Knowing how much time
? ? ? ✗
? ✔ ?
students spent
Knowing Knowing if externalstudents
how much time learning spent ✔
? ? ?
resources are used
Knowing if external learning resources areIssues
used ✔Addressed by SAM


CGIAR LAK
issue for add- issue for add-
teacher ressed teacher ressed
Provide feedback to the students ✔ ? ✔ ✔
Being aware of what students are doing ✔ ✔ ✔ ?
Knowing about collaboration and communication ✔ ✗ ✔ ✗
Knowing which documents are used and how much ✔ ✔ ✔ ?
Knowing how and when online tools have been used ? ✔ ✗ ?
Finding the students who are not doing well ✔ ? ✔ ?
Finding the best students ? ? ? ✗
Knowing how much time students spent ? ✔ ? ✔
Knowing if external learning resources are used ✔ ? ? ?

CGIAR CASE STUDY


CGIAR CASE STUDY
want to search detect outliers
for students
more details on
good indicator for effort student
understand the workload
progress evolution
compare students
obtain course overview
increase awareness
want better 1 to 1 use for course
comparison tool design optimization more metrics
wanted

LAK CASE STUDY

http://maranash.blogspot.com/2011/01/conference-shout-out.html


LAK CASE STUDY
ﬁnd students experiencing
problems and low
verify the status of the engagement
classroom activity
more
chronological course dwell time metrics
self-reﬂection to measure
progress and increase
motivation more data

http://maranash.blogspot.com/2011/01/conference-shout-out.html


demogra evaluation design
negative positive
phics goal changes

usability, •↑learnability
12 CS satisfaction, small usability •↓errors
I. 1st iteration
students preliminary issues •good satisfaction
usefulness •usefulness positive

assessing •provides awareness
19 resource
teacher •all vis. useful
II. teachers help function recomm. not
needs, use & •many uses
& TA’s useful
usefulness •90% want it

•provides awareness
assessing re-orderable
most and feedback
12 teacher parallel
addressed •many uses
III. participan needs, expert coordinates
needs are •66% want it
ts feedback, use with
indecisive •recomm. can be
& usefulness histograms
useful
57

ITERATION FOUR

•a CS course on C++ programming

• 11 people: 7 teachers, 2 TA’s & 1 course planner

• richer data set: tracking from programming environment

• qualitative study using a structured face-2-face interview
with 25 open questions.


ACHIEVABLE TASKS
conﬂicting visions on get a time
identify students doing
students doing well summary well and at risk
and at risk
better course monitor tool and
overview resource use
understand time
spent better

detect students course planning
for assistance
step 5 & 7 - capture/create awareness. http://www.tdpri.com/forum/telecaster-discussion-
59
forum/48431-ic503z-cap-52-ri-blackguard-book.html


ACHIEVABLE TASKS
conﬂicting visions on get a time
identify students doing
students doing well summary well and at risk
and at risk
all: want tocourse using it
better continue monitor tool and
9/11: give it to students
overview resource use
understand time
spent better

detect students course planning
for assistance
step 5 & 7 - capture/create awareness. http://www.tdpri.com/forum/telecaster-discussion-
59
forum/48431-ic503z-cap-52-ri-blackguard-book.html


demo- evaluation design
negative positive
graphics goal changes
usability, •↑learnability
12 CS satisfaction, small usability •↓errors
I. 1st iteration
students preliminary issues •good satisfaction
usefulness •usefulness positive
•provides awareness
19 assessing teacher resource
•all vis. useful
II. teachers needs, use & help function recomm. not
•many uses
& TA’s usefulness useful
•90% want it
•provides awareness and
assessing teacher most
12 re-orderable feedback
needs, expert addressed
III. participan PC with •many uses
feedback, use & needs are
ts histograms •66% want it
usefulness indecisive
•recomm. can be useful

ﬁlter & •provides time overview
search, conﬂicting •provides course
11 icons, visions of overview
use, usefulness
IV. teacher zooming in students •PC assist with detecting
& satisfaction
s & TA’s line chart, doing well problems
editing PC or at risk •many uses & insights
axes •100% want it
60

CONCLUSION
• SAM is perceived useful and contributes to better
awareness.


CONCLUSION
awareness.

• SAM enables:


CONCLUSION
awareness.

• SAM enables:
• to detect potential students doing well and at risk


CONCLUSION
awareness.

• SAM enables:
• a better course overview


CONCLUSION
awareness.

• SAM enables:
• understanding student time spending


CONCLUSION
awareness.

• SAM enables:
• to ﬁnd a wide variety of new insights


CONCLUSION
awareness.

• SAM enables:
• to ﬁnd a wide variety of new insights

• almost all want to continue using SAM

CONTRIBUTIONS.
1. A structured method for selecting an appropriate metadata schema

2. The design & evaluation of a metadata generator for the origin of an artist

3. The re-evaluation of a general metadata generation approach

4. The design & evaluation of federated search tool with social
recommendations

5. The design & evaluation of visualisations of attention metadata to support
awareness and self-reﬂection.

62

Ch 8
CONTRIBUTIONS.



recommendations


62

Ch 8
CONTRIBUTIONS.
RQ 3



recommendations


62

Ch 8
CONTRIBUTIONS.
RQ 3


62

Ch 8
CONTRIBUTIONS.
RQ 3



62

Ch 8
CONTRIBUTIONS.
RQ 3


3. The re-evaluation of a general metadata generation approach RQ 2

62

Ch 8
CONTRIBUTIONS.
RQ 3


recommendations

62

Ch 8
CONTRIBUTIONS.
RQ 3


recommendations RQ 1

62

Ch 8
CONTRIBUTIONS.
RQ 3



62

Ch 8
CONTRIBUTIONS.
RQ 3


RQ 4

62

publications.

http://dailypracticeblog.com/how-paper-claims-will-be-impacted-by-5010/ 63

domain steps RQ conf. publication
define, Govaerts, Sten; Corthaut, Nik; Duval, Erik. Moody tunes: the
(RQ1, RQ3) ISMIR’06 rockanango project
create, utilise
create (RQ2) ISMIR’07 Govaerts, Sten; Corthaut, Nik; Duval, Erik. Mood-ex-machina:
towards automation of moody tunes
Corthaut, Nik; Govaerts, Sten; Verbert, Katrien; Duval, Erik.
music RQ3 ISMIR’08 Connecting the dots: music metadata generation,
define schemas and applications

RQ2 ISMIR’09 Govaerts, Sten; Duval, Erik. A Web-based approach to
determine the origin of an artist
create ISM’09- Govaerts, Sten; Corthaut, Nik; Duval, Erik. Using search engine
RQ2 for classification: does it still work?
WS
Govaerts, Sten; Verbert, Katrien; Klerkx, Joris; Duval, Erik.
RQ4 ICWL’10 Visualizing activities for self-reflection and
awareness
capture, Evaluating the
create RQ4 ICWL’11 Govaerts, Sten; Verbert, Katrien; Duval, Erik.studies
student activity meter: two case
awareness Govaerts, Sten; Verbert, Katrien, Duval, Erik; Pardo, Abelardo. The
TEL RQ4 CHI’12 Student Activity Meter for Awareness and Self-
reflection
CSCW’11 Govaerts, Sten; El Helou, Sandy; Duval, Erik; Gillet, Denis. A
utilise, RQ1 federated search and social recommendation widget
-WS
personalise, Govaerts, Sten; Verbert, Katrien; et al. Towards Responsive
capture RQ1 EC-TEL’11 Open Learning Environments: the ROLE
Interoperability framework
64

period project domain RQ steps pubs.

2005 - Aristo IWT RQ2, deﬁne, create, ISMIR’06,
music ISMIR’07,
2007 project 1 RQ3 (utilise)
ISMIR’08,
ISMIR’09,
2007 - Aristo IWT RQ2, ISM’09-
music deﬁne, create
2009 project 2 RQ3 WS
ICWL’10,
utilise, personalise,
2009 - RQ1, ICWL’11,
ROLE TEL capture, create
ECTEL’11,
now RQ4 awareness CHI’12

10/2010- Research RQ1, utilise, personalise, CSCW’11-
TEL WS
12/2010 stay at EPFL RQ4 capture

65

some
metrics...

66

CITATIONS PER YEAR.
total citations: 72
external citations: 49 30
self citations
h-index: 6
external citations
23
number of citations

15

8

0
2007 2008 2009 2010 2011 2012
year
67

CITATIONS PER YEAR.
total citations: 72
external citations: 49 30
self citations
h-index: 6 6 external citations
23
number of citations

15

8 23

8
11 6
2 7
1
2 3 3
0
2007 2008 2009 2010 2011 2012
year
67

number of citations

0
4
8
11
15

ISMIR 2006

ISMIR 2007

ISMIR 2008

ISMIR 2009 (1)

ISMIR 2009 (2)

adMIRe 2009

68
IJETEL 2010

papers
ICWL 2010

SRS 2011

ECTEL 2011

EFEPLE 2011
CITATIONS PER PAPER.

ICWL 2011
self citations

CHI 2012
external citations

number of citations

0
4
8
11
15

9
5
ISMIR 2006

2
4
ISMIR 2007

9
ISMIR 2008

6
2
ISMIR 2009 (1)

1
ISMIR 2009 (2)

1
adMIRe 2009

68
6
1

IJETEL 2010

papers
7
4

ICWL 2010
3
2

SRS 2011
2
2

ECTEL 2011
2
1

EFEPLE 2011
CITATIONS PER PAPER.

2

ICWL 2011
self citations

1

CHI 2012
external citations

TIME SPENT.

1: schemas 2: origin 2: search 4,5&6: search & recomm. 5&7: awareness

time

time per RQ

0% 25% 50% 75% 100%
RQ1 RQ2 RQ3 RQ4

69

TIME SPENT.

1: schemas 2: origin 2: search 4,5&6: search & recomm. 5&7: awareness

time 15% 20% 10% 18% 37%

time per RQ 18% 30% 15% 37%

0% 25% 50% 75% 100%
RQ1 RQ2 RQ3 RQ4

69

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Questions?
70

From Findability to Awareness: Metadata in Music and Technology Enhanced Learning.

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