Presentation about using IPTC to code photographs for scientific research. Presented during the 'AV in Digital Humanities' workshop during th Digital Humanities 2014 Conference, Tuesday 8 July 2014, Lausanne.

1. Tracing the afterlife of iconic
photographs using IPTC
Martijn Kleppe
Slides on Slideshare: bit.ly/iconicphoto
@martijnkleppe

2. Charlie Cole, Newsweek – World Press Photo of the Year 1989

3. Nick Ut, AP – World Press Photo of the Year 1972

5. Icons
Composition
Archetype
Unique &
Generique
Often
Published
Variations
Emotions
Meaning
clear
Symbolic
Meaning
Meaning
changes

6. Outline
6
1. Find images that are often published
2. Find images which meaning has changed over time
3. Lessons learned
4. Hopes for the future

7. 1. Often published
7
• Which identical photos are published most often?
• 400 Dutch History textbooks
• Dataset of ~ 5.000 photographs
• Analyzed on 41 variables (f.e. name person & topic)
• IPTC to structure dataset

8. 1. Often published - IPTC
8
International Press Telecommunications Council

10. 1. Often published - IPTC
10
International Press Telecommunications Council

11. 1. Often published - IPTC
11
Advantages for photographers:
- Code multiple images
at once
- All information in 1 file
- All software can read
information in the file
- Easy to transfer
Advantages for academics:
- Code multiple images
at once
- All information in 1 file
- All software can read
information in the file
- Easy to transfer (& share)
- Find images easier
- Export all data

12. 1. Often published – My case
12
• Which photos are published most often in 400 Dutch
History textbooks?
• Locate photos in History textbooks
• Digitize them & add them to Fotostation Pro
• Code all images & add values in IPTC fields

13. Fotostation Pro

15. 1. Often published – My case
15
• Export data variables (f.e. topics) to SPSS
• Create frequency lists topics
• Which topics are most frequent?
• Manually go over most frequent topics to find most
published photographs

17. Icons
Composition
Archetype
Unique &
Generique
Often
Published
Variations
Emotions
Meaning
clear
Symbolic
Meaning
Meaning
changes

18. 2. Changing Meaning
18
• Back to Fotostation Pro to easily find photographs of
Troelstra:

19. 2. Changing Meaning
19
• Go over the captions provided in the history textbooks
1912?
or
1918?

20. 3. Lessons Learned
20
• IPTC was useful & efficient
• Manual labor remained necessary & typos will happen
• Does the most frequent topic also contain the
most published identical photo?
(Spoiler alert: NO! )
• How to describe photographs?
Do we all see the same thing in images?
Do we all use the same words to describe images?

21. “Universal suffrage, Portrait”

22. “Political parties, social-
democracy the Netherlands”

23. “Protestphoto”

24. 3. Lessons Learned
24
• IPTC was useful & efficient
• Manual labor remained necessary & typos will happen
• But does the most frequent topic also contain the
most published identical photo?
(Spoiler alert: NO! )
• How to describe photographs?
Do we all see the same thing in images?
Do we all use the same words to describe images?
• Semantic Gap

25. 3. Lessons learned
25
“The semantic gap characterizes the
difference between two descriptions of an
object by different linguistic
representations, for instance languages or
symbols.”
Smeulders, 2000

26. 4. Hopes for the future
26
• How to overcome or avoid the semantic gap?
• Image recognition
https://itunes.apple.com/us/app/lexalizer/id374904872?mt=8

27. 4. Hopes for the future
27

28. 4. Hopes for the future
28

29. 4. Hopes for the future
http://mw2013.museumsandtheweb.com/paper/where-do-images-of-art-go-once-they-go-online-a-
reverse-image-lookup-study-to-assess-the-dissemination-of-digitized-cultural-heritage/

30. 4. Hopes for the future
 Let me create my dataset of photos (with IPTC)
 Apply image recognition to:
 Show me similar photos in 1 dataset
RQ: which photos are used most often?
+ No more manual checking
 Let me upload 1 photo and find all similar photos
RQ: how did the meaning of the photo change over time?
+ No dependency of words
 Applicable for other research questions:
Show me all newspapers that contain the photo of Troelstra

31. Questions?
Martijn Kleppe
kleppe@eshcc.eur.nl
www.martijnkleppe.nl
@martijnkleppe

32. Literature
Finnegan, C.A.: “What is this a picture of? Some Thoughts on Images and
Archives”, In:Rethoric & Public Affairs 9, 116 – 123 (2006).
Grijsen, C.: “In perspectief: behoud en beheer van born-digital fotoarchieven” (In
perspective: conservation and management of born-digital photo archives). In: Fotografisch
Geheugen 75, 24 – 26. (2012).
Kleppe, M.: Canonieke Icoonfoto’s. De rol van (pers)foto’s in de Nederlandse
geschiedschrijving (Canonical Iconic Photographs: The role of (press) photos in Dutch
Historiography). Eburon, Delft (2013a).
Kleppe, M.: Foto’s in Nederlandse Geschiedenisschoolboeken (FiNGS) (Photos in
Dutch History textbooks) http://www.persistent-identifier.nl/?identifier=urn:nbn:nl:ui:13-
l37n-bi( 2013b).
Kleppe, M.: “Wat is het onderwerp op een foto? De kansen en problemen bij het
opzetten van een eigen fotodatabase” (What is the subject of a picture? The opportunities and
difficulties in setting up their own photo database). In: Tijdschrift voor Mediageschiedenis 293
– 107 (2012).
Reser, G., & Bauman, J.: “The Past, Present, and Future of Embedded Metadata for
the Long-Term Maintenance of and Access to Digital Image Files”. In: International Journal of
Digital Library Systems (IJDLS), 3(1), 53-64 (2012).
Smeulders, Arnold W. M. e.a., “Content-Based Image Retrieval at the End of the
Early Years”, IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 1349 – 1380
(2000).
Terras, M. M., and I. Kirton. “Where do images of art go once they go online? A
Reverse Image Lookup study to assess the dissemination of digitized cultural heritage.”
Selected papers from Museums and the Web North America, 237 – 248 (2013) .