FIAT/IFTA MAM Survey 2017Highlights from the results analysis

FIAT/IFTA MMC Seminar, Lugano 2017 – Brecht Declercq (VIAA), Gerhard Stanz (ORF) – 08.06.2017

Why the MMC MAM Surveys?

Archive world is changing fast

You find cutting edge archive knowledge almost only in

the archives

FIAT/IFTA members are in search of answers

MMC collects, processes and distributes know-how

2nd Survey since the one in 2015

disclaimer:

lies,damn lies,

and statistics[Benjamin Disraeli]

Broadcaster’s archives 40 71%

Regional / national AVarchives 14 25%

Others 2 4%

MAM SURVEY 2017 RESPONDENTS

Number of responses 56Number of unique archives 53

YOUR METADATACREATION STRATEGY

Metadata creation methodsclassification

• manually: manual annotation in the archive

• harvesting: importing existing data from production

• mining: algorithms generate new meaning from input data

96%

78%

67%

54%

48%

31%

24%

15%

9%

60%

39%

50%

23%

39%

36%

21%

25%

32%

Manual, internal

Import from production: other systems

Import from production: planning system

Copy and paste from online sources

Import from production: closed captioning

Manual, external commercial service

Automatic feature extraction: speech-to-text

Manual, external non-commercial

Automatic feature extraction: othertechnologies

how many respondents use this method at all? for which share of your items on average? (non-users excl.)

Metadata creation methods

HARVESTINGFROM PRODUCTION

Harvesting potential

average

The amount of metadata that can be harvested in your case? 36%

How much could it be if the integration would be perfect? 58%

Harvesting internal sources

Harvesting external sources

63%

31%

31%

19%

6%

0% 20% 40% 60% 80% 100%

Others

IMDB

Geonames

DBPedia

ISANOther:

MusicbrainzBaidu

SoccerwayOgol

WikipediaSharedogUFC site

Tribune (TMS)

Harvesting ‘Edit Decisions’ (EDL)

69% 31%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

no yes

JOURNALISTS/EDITORSAS CATALOGERS?

Production staff fill in metadata themselves?

57%

44%

11%

2%

43%

26%

15%

2%

total

broadcaster

regional / national archive

other

yes no

0

1

2

3

4

5

6

7

8

9

10

Happy with the quality?

ENTIRELY HAPPY

NOT HAPPY AT ALL

0

1

2

3

4

5

6

7

8

9

10

Happy with the delay?

ENTIRELY HAPPY

NOT HAPPY AT ALL

MININGAKA AUTOMATIC FEATURE EXTRACTION

Mining experience and expectation

1. v

ide

o-O

CR

2. l

ogo

det

ecti

on

3. i

mag

e/co

nce

pt-

reco

gnit

ion

4. o

bje

ct

reco

gnit

ion

5. s

em

anti

cso

un

d

clas

sifi

cati

on

6. t

ech

nic

also

un

d

clas

sifi

cati

on

7. s

pe

aker

id

en

tifi

cati

on

8. m

usi

cre

cogn

itio

n

9. a

spe

ct r

atio

q

ual

ific

atio

n

10

. su

bje

ct

he

adin

gs

11

. sp

eec

h-t

o-t

ext

A. in daily work 2% 2% 2% 0% 4% 9% 6% 4% 20% 9% 10%

B. Tested, we will implement it

6% 4% 6% 4% 2% 2% 6% 9% 6% 7% 12%

C. no experience, but useful

67% 46% 69% 63% 56% 50% 61% 63% 46% 69% 46%

D. no experience, not

relevant9% 43% 15% 19% 28% 35% 15% 19% 26% 7% 10%

E. tested, but not good enough

17% 6% 9% 15% 11% 4% 13% 6% 2% 7% 22%

MAX

MIN

17%

17%

67%

spoken word audio / radio only

video / TV / moving image only

both

Speech-to-text: for which kind of media?

0%

0%

0%

0%

0%

0%

17%

33%

50%

100%

0% 50% 100%

Other

Publicity

Feature films

Cartoons / animation

Children's programs

Fiction / drama

Shows / quiz

Current affairs / factual

Sports

News

Speech-to-text: for which genres?

0

1

2

3

4

5

6

7

8

9

10

Speech-to-text: happy with the quality?

ENTIRELY HAPPY

NOT HAPPY AT ALL

0

1

2

3

4

5

6

7

8

9

10

Speech-to-text: happy with names recognition?

ENTIRELY HAPPY

NOT HAPPY AT ALL

Why don’t you use speech-to-text (yet)?

23%

13%

13%

11%

9%

13%

9%

4%

5%

11%

Not good enough for our main languages

How to integrate it in MAM architecture?

Costs will outweigh benefits

Our MAM doesn't allow it

Implementation is busy

Others: in some stage of preparation

Others: no MAM yet / too early

Others: we use subtitling, so low priority

Others

(We have it already)

METADATA CREATIONIN THE FUTURE

Remaining manual annotation

4%

11%

7%

23%

14%

9%7%

5%

0%2%

0%

14%

0%

5%

10%

15%

20%

25%

30%0

%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

no

dec

reas

e

Nu

mb

ero

f re

spo

nd

ents

Decrease of manual annotation until…

COMBINEDSEARCH

Combined search possible?

47.3% 34.5% 18.2%

0% 20% 40% 60% 80% 100%

yes no n/a

Combined search details

Database Sources: Ano

nym

ous

1

Ano

nym

ous

2

Ano

nym

ous

3

Ano

nym

ous

4

Ano

nym

ous

5

Ano

nym

ous

6

Ano

nym

ous

7

Ano

nym

ous

8

Ano

nym

ous

9

Ano

nym

ous

10

Ano

nym

ous

11

Ano

nym

ous

12

Ano

nym

ous

13

Ano

nym

ous

14

4 w

ith

3 So

urce

s

7 w

ith

2 So

urce

s

Television / Video Archive 14 x x x x x x x x x x x x x x

Radio / Audio Archive 13 x x x x x x x x x x x x x

Photo, image, graphics database 9 x x x x x x x x x

Document Management System 5 x x x x x

Newspapers 7 x x x x x x x

Television License Database 5 x x x x x

Television Planning System 5 x x x x x

Radio License Database 5 x x x x x

Radio Planning System 4 x x x x

MAM 1 x

Newswires, Agency Information 2 x x

other 2 x x

Administrative Data 1 x

Books and Manuscripts 1 x

Web-Archive 1 x

Number of Databases: 9 7 7 7 5 5 5 5 5 4 4 4 4 4 3 2

happy with the search possibilities as they are now*

DISCOVERABILITYFINDABILITY

91% 9%

0% 20% 40% 60% 80% 100%

no yes

Use of external registries

ISAN, ISBN, GUID, …

Archival clips on Youtube?

17% 22% 61%

0% 20% 40% 60% 80% 100%

yes, incl. internal metadata yes, excl. internal metadata no

Metadata for target groups other than production?

45%

36%

50%

43%

16%

36%

50%

22%

34%

14%

28%

5%

14%

7%

broadcaster'sarchives

national/regionalAvarchives

others

total

no we don't yes, from the beginning yes, from later on other

Adaptations on metadata for other target groups?

35%

19%

19%

11%

43%

we adapt the vocabulary used

we adapt the metadata categories

we decrease the level of detail

other

no we don't adapt our metadata

THANK YOU!FIAT/IFTA MMC & PMC Members

Eléonore Alquier (INA)Elena Brodie-Kusa (EBK)

Anne Couteux (INA)Brecht Declercq (VIAA)

Gerhard Stanz (ORF)

More and deeper results in de publication after this conference!