Presented at the “5th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion (DSAI).

1. Bruno Splendiani, Mireia Ribera
Adaptabit Group – University of Barcelona
DSAI Conference 2013 - 13/11/2013

2. 
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Introduction
Our work
Methodology
Results
Conclusions
Further work
Bruno Splendiani (2013) – splendiani@ub.edu
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3. 
Accessibility scientific literature
published by computer science journals
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Computer science researchers play an
active role in digital accessibility
research
Bruno Splendiani (2013) – splendiani@ub.edu
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4. 
Many computer science subjects rely on
visual resources such as graphs, diagrams
and charts.
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Visual content in computer science academic
papers is a critical information source
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Readers with visual impairments cannot
access graphical information
Bruno Splendiani (2013) – splendiani@ub.edu
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5. Sources: [1 -4]
Bruno Splendiani (2013) – splendiani@ub.edu
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6. “If I can’t see the image I read its description”
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Recommended by the Web Content Accessibility
Guidelines
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Incorporated to the publishing workflow guidelines of
Bruno Splendiani (2013) – splendiani@ub.edu
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7. 
Readers
 Access to the content
 Publishers
 Advantages in article retrieval
 Fulfil accessibility regulations
 Comply with social responsibility
Bruno Splendiani (2013) – splendiani@ub.edu
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8. Analysis
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Do actual practices of image submission fulfil
basic recommendations on accessibility?
Proposal
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What should be done for including accessibility
practices and principles in the submission
process of academic journals?
Bruno Splendiani (2013) – splendiani@ub.edu
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9. 10 journals in computer science in JCR
Follow accessibility policy?
Submission policy and guidelines related to the visual
content?
Follow international guidelines on image submission?
Bruno Splendiani (2013) – splendiani@ub.edu
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10. 1 paper for each journal in PDF version
Are figures “readable”?
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Image format
Color contrast and coding
Label font type and size
Minimum resolution
Minimum dimensions
Do figures have alternative text?
Source: [4]
Bruno Splendiani (2013) – splendiani@ub.edu
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11. Bruno Splendiani (2013) – splendiani@ub.edu
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12. 
The practices do not fulfill basic
recommendations on accessibility
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Images lack alternative descriptions
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Lack of consistency between image
submission policies and their application
Bruno Splendiani (2013) – splendiani@ub.edu
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13. The visual information of computer science articles
is not accessible to people with visual disabilities
Bruno Splendiani (2013) – splendiani@ub.edu
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14. Common set of international guidelines
for image submission
universal accessibility improved
Easier graphical authoring: shared guidelines
Bruno Splendiani (2013) – splendiani@ub.edu
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15. Start from
existing guidelines on image description
Bruno Splendiani (2013) – splendiani@ub.edu
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16. Some depth work done in common charts (bar, line, pie...)
But
NO clear foundation for describing
other types of images
The image is….
It shows….
Panel a shows..
Panel b shows..
Legend shows…
Bruno Splendiani (2013) – splendiani@ub.edu
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17. Currently computer science articles are not
accessible to everybody
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Accessibility of scientific papers and their figures
should gain relevance in computer science research
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Research in the field will
 improve image accessibility
 Improve retrieval
 Improve the efficiency of the submission process
Bruno Splendiani (2013) – splendiani@ub.edu
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18. Domain - specific
Science
Technology
Engineering
Mathematics
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Graphic type - specific
Illustration
Diagram
Photograph
………
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Bruno Splendiani (2013) – splendiani@ub.edu
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19. 
Adapted to the image role/function within the
article
 Support the article results?
 Offer a visual example?
 Show numerical data?
 Emphasize special details?
Bruno Splendiani (2013) – splendiani@ub.edu
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20. In the context of all image-related textual
information
Source: [5]
Bruno Splendiani (2013) – splendiani@ub.edu
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21. 
Linked to the publishing workflow
 Supporting formats
 Recommendations in submission system
 Automatic image check
(contrast, resolution, font size..)
 Alt text check
Bruno Splendiani (2013) – splendiani@ub.edu
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22. Questions?
splendiani@ub.edu
Bruno Splendiani (2013) – splendiani@ub.edu
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23. 1.
2.
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4.
5.
Zargar, S.T., J. Joshi, y D. Tipper. «A Survey of Defense Mechanisms
Against Distributed Denial of Service (DDoS) Flooding Attacks». IEEE
Communications Surveys Tutorials, Volume PP Issue 99 (2013):1 -24 .
Wu, Gin-Der, y Pang-Hsuan Huang. «A Vectorization-OptimizationMethod-Based Type-2 Fuzzy Neural Network for Noisy Data
Classification». IEEE Transactions on Fuzzy Systems 21, n.o 1 (2013): 1-15.
Toews, Matthew and William M. Wells III. «Efficient and robust modelto-image alignment using 3D scale-invariant features». Medical Image
Analysis 17, n.o 3 :271-282.
Chen, Zhihu, Kwan-Yee K. Wong, Yasuyuki Matsushita, y Xiaolong Zhu.
«Depth from Refraction Using a Transparent Medium with Unknown
Pose and Refractive Index». Int. J. Comput. Vision 102, n.o 1-3 (2013): 3–
17.
Splendiani, B., Ribera,M. « Do physicians make their articles readable
for their blind or low-vision patients? An analysis of current image
processing practices in biomedical journals from the point of view of
accessibility» (under review)
Bruno Splendiani (2013) – splendiani@ub.edu
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