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Accessibility of Big & Broad Data

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@article{Harper2014aa, …

@article{Harper2014aa,
Abstract = {Visually disabled people typically use methods of `sensory translation' to access data via assistive technology. These technologies conventionally render content under the direction of the user into a form that can be perceived by that user -- in effect the interface and content are adapted to suit their sensory requirements -- but simple sensory translation is not enough for big, broad and complex data. Why is this -- and how can things be better?},
Author = {Simon Harper},
Date-Added = {2014-05-27 13:03:23 +0000},
Date-Modified = {2014-05-27 13:03:34 +0000},
Doi = {http://dx.doi.org/10.6084/m9.figshare.1037547},
Howpublished = {Slideshare},
Journal = {Invited Talk - Human Behaviour Network, Manchester Informatics, Manchester UK},
Month = {May},
Title = {Accessibility of Big and Broad Data - http://goo.gl/UpekPK},
Url = {http://www.slideshare.net/simon-harper/accessibility-of-big-broad-data},
Year = {2014},
Bdsk-Url-1 = {http://www.slideshare.net/simon-harper/accessibility-of-big-broad-data},
Bdsk-Url-2 = {http://dx.doi.org/10.6084/m9.figshare.1037547}}

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  • 1. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Accessibility of Big & Broad Data Simon Harper University of Manchester http://goo.gl/UpekPK @sharpic simon.harper@manchester.ac.uk 27 May, 2014 Accessibility of Big & Broad Data 1 / 38
  • 2. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Thinking; when putting this together 1. Applications often designed to conform to a theoretical user, context, and interactions – autobiographical design; 2. techniques evolved to correct these theoretical misconceptions when reality interfered (such as in accessibility / Assistive Technology); 3. extended to include ideas of physiology and cognition for enhanced use; 4. ‘Big & Broad Data’ is complex, and consumption characteristics are not know at the time of data production; and 5. can our knowledge of ‘reality’ help? Accessibility of Big & Broad Data What? Why? 2 / 38
  • 3. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Adaptation Visually disabled people typically use methods of ‘sensory translation’ to access data via assistive technology. These technologies conventionally render content under the direction of the user into a form that can be perceived by that user – in effect the interface and content are adapted to suit their sensory requirements – but simple sensory translation is not enough for big, broad and complex data. Why is this – and how can things be better? Accessibility of Big & Broad Data What? Why? 3 / 38
  • 4. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Adaptation Move expertise about a user from the developer to the user (or at least the tools that user actually uses). How to get the computer to understand the ‘stuff’; how to automatically split this stuff up; and how to present this split-up-stuff back to users? Accessibility of Big & Broad Data What? Why? 3 / 38
  • 5. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Why Might this be More Generally Important? Removing autobiographical design increases flexibility and future proofing; support mobile, small screen real estate (audio maybe more natural); supports distributed attention; augments complex visual data; and remove reductionism / simplification Accessibility of Big & Broad Data What? Why? 4 / 38
  • 6. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Accessibility of Big & Broad Data Adaptation/Transcoding 5 / 38
  • 7. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Accessibility of Big & Broad Data Adaptation/Transcoding 6 / 38
  • 8. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Accessibility of Big & Broad Data Adaptation/Transcoding 7 / 38
  • 9. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Accessibility of Big & Broad Data Adaptation/Transcoding 8 / 38
  • 10. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Accessibility of Big & Broad Data Adaptation/Transcoding 9 / 38
  • 11. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Transcoding / Adaptation “A category of technologies to transform inaccessible content to accessible content on the fly” To Accomplish Text Magnification; Colour Scheme Changes; Serialisation; Text Insertion; Page Rearrangement; and Simplification. Approaches Syntactic: such as removing images; Semantic: rearrangements and fragmentation; Annotation: created by a reader; and Generated: annotations by CMS. Accessibility of Big & Broad Data Adaptation/Transcoding 10 / 38
  • 12. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Content Driven Transcoding Screen-Scraping - 1990’s Originally content was ‘made accessible’ via a method called screen-scraping which used the visual rendering to create accessible content, by creating an off-screen model (a representation of the GUI). Screen-scraping was problematic because it was often wrong, did not take account of structure, and could not form accurate semantics between elements of the content. DOM Analysis - 2000’s Document Object Model analysis took over from screen-scraping and enables accurate structural semantics to be created as all elements and attribute values are available to the assitive technology. Accessibility of Big & Broad Data Adaptation/Transcoding 11 / 38 Harper and Yesilada (2008)
  • 13. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Page Annotation - 2000 - Doesn’t Scale Before After Asakawa and Lewis (1998) Accessibility of Big & Broad Data Adaptation/Transcoding 12 / 38
  • 14. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Style Annotation - 2008 - Scalable Harper and Bechhofer (2007) Accessibility of Big & Broad Data Adaptation/Transcoding 13 / 38
  • 15. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Annotate 1 Style File Scales to Many HTML Files . cnnCeilnav , d i v . cnnHeaderNav {uom−s t r u c t u r a l −r o l e : L i n k L i s t ; } i n p u t . c n n I n p u t {uom−s t r u c t u r a l −r o l e : SearchEngine ; } d i v . CNNhomeBox , o l . cnnMostPopular , d i v#cnnTopStories . . . {uom−s t r u c t u r a l −r o l e : Chunk ; } d i v#cnnHeaderRightCol u l {uom−s t r u c t u r a l −r o l e : PageSummary ; } Accessibility of Big & Broad Data Adaptation/Transcoding 14 / 38
  • 16. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Code Driven Transcoding - 2011 Lunn and Harper (2011); Chen et al. (2012) Accessibility of Big & Broad Data Adaptation/Transcoding 15 / 38
  • 17. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Beyond Accessibility - Readability - 2011 Before After Accessibility of Big & Broad Data Adaptation/Transcoding 16 / 38
  • 18. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Beyond Accessibility - Evernote Clearly - 2012 Before After Accessibility of Big & Broad Data Adaptation/Transcoding 17 / 38
  • 19. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Experience Driven Transcoding ‘Content and Code Driven Transcoding’ is focused on transforming the computer code based on its representation; however ‘Experience Driven Transcoding’ goes a step further and attempts to transform the content/code based on both its representation, and the predicted experience of the user into an equivalent sensory experience. BBC News with AoI’s Accessibility of Big & Broad Data Adaptation/Transcoding 18 / 38
  • 20. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Example – Graph Ranked Order Comparison Accessibility of Big & Broad Data Adaptation/Transcoding 19 / 38
  • 21. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Interacting with Calendars (Brown et al., 2012) Accessibility of Big & Broad Data Adaptation/Transcoding 20 / 38
  • 22. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Beyond Accessibility (again) - 2011 Visual Complexity Rankings & Visual Aesthetics Rankings Heat Map of Visual Complexity – Harper et al. (2009) Accessibility of Big & Broad Data Adaptation/Transcoding 21 / 38
  • 23. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Big & Broad Data Data sets so large and complex that it becomes difficult to process; data is too big, moves too fast, or doesn’t fit the strictures of your database architectures; broad Data is the huge amount of freely available, but widely varied, Open Data on the World Wide Web (Structured and Semi-structured); often found in broad Data Mash-ups; to gain value from this data, you must choose an alternative way to process it... and Visualise / interact with it. Accessibility of Big & Broad Data Big & Broad Data 22 / 38 Hendler (2012); Dumbill (2012); White (2014)
  • 24. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Accessibility of Big & Broad Data Big & Broad Data 23 / 38
  • 25. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Accessibility of Big & Broad Data Big & Broad Data 24 / 38
  • 26. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Big Simplification Tendency to simplify and aggregate; moving complex data to info-graphics and visualisations; does this really increase our understanding? Accessibility of Big & Broad Data Big & Broad Data 25 / 38
  • 27. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Big Simplification Wattenberg et al. (2007a) The first three letters of a string determine colour in a Chromogram. The first letter determines the hue; the second letter the saturation, and the third the brightness. Many Wikipedians engage in systematic activities: that is, a sustained related sequence of edits – Wattenberg et al. (2007b). Accessibility of Big & Broad Data Big & Broad Data 25 / 38
  • 28. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Auditory Display Ferres et al. (2013) Accessibility of Big & Broad Data Big & Broad Data 26 / 38
  • 29. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References More Complex Auditory Display Guardian Group (2010) Accessibility of Big & Broad Data Big & Broad Data 27 / 38
  • 30. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Sonification? Difficult to Understand - mostly Aesthetic Listen to this... http://geant3.archive.geant.net/Media˙Centre/Media˙ Library/Media%20Library/Higgs˙Boson˙Atlas˙Piano˙Solo. mp3 Accessibility of Big & Broad Data Big & Broad Data 28 / 38
  • 31. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Sonification? The First Higgs Boson Data Sonifcation LHC Open Symphony (2012) Accessibility of Big & Broad Data Big & Broad Data 28 / 38
  • 32. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Auditory Perception – ‘Cocktail Party Problem’ Been talking about translating parallel visual experience into a serial auditory one. BUT auditory perception is parallel too. ‘The separation of two simultaneously spoken messages’, in which Cherry first poses the question ‘how do we recognise what one person is saying when others are speaking at the same time (the ‘cocktail party problem’)?’ is key. This can only be useful work in the domain of blindness, auditory interfaces, and multi-modal interfaces in that it may be possible to convey aggregated big data much faster because of the ability to comprehend highly parallel speech. Accessibility of Big & Broad Data Auditory Perception 29 / 38 Cherry (1953)
  • 33. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Properties of Sound Accessibility of Big & Broad Data Auditory Perception 30 / 38
  • 34. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Multi-Talker Display – Brungart We now have between seven and nine people intelligibly multi-talking at the same time based on spatial location and voicing. Again, this can only be useful work in the domain of blindness, auditory interfaces, and multi-modal interfaces in that it may be possible to convey aggregated big data much faster because of the ability to comprehend highly parallel speech. Accessibility of Big & Broad Data Auditory Perception 31 / 38 (Brungart and Simpson, 2005; Bronkhorst, January/February 2000; Brungart et al., 2009)
  • 35. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References The Ear Accessibility of Big & Broad Data Auditory Perception 32 / 38 (Bear et al., 2006)
  • 36. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Neurophysiology - Signal Transmission Accessibility of Big & Broad Data Auditory Perception 33 / 38 (Bear et al., 2006)
  • 37. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References The Auditory Cortex Accessibility of Big & Broad Data Auditory Perception 34 / 38 (Bear et al., 2006)
  • 38. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Wrapping-Up 1. Adaptation to the user is key; we must remove the presumptions that have dogged software development, most big or broad data is actually created without a clear knowledge of how it will be used; Accessibility of Big & Broad Data Wrapping-Up 35 / 38
  • 39. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Wrapping-Up 1. Adaptation to the user is key; we must remove the presumptions that have dogged software development, most big or broad data is actually created without a clear knowledge of how it will be used; 2. this makes the context of use and the user similar to Assistive Technology; responsibility for display and interaction should be with the user; Accessibility of Big & Broad Data Wrapping-Up 35 / 38
  • 40. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Wrapping-Up 1. Adaptation to the user is key; we must remove the presumptions that have dogged software development, most big or broad data is actually created without a clear knowledge of how it will be used; 2. this makes the context of use and the user similar to Assistive Technology; responsibility for display and interaction should be with the user; 3. we can learn from Assistive Technology adaptation research and development; Accessibility of Big & Broad Data Wrapping-Up 35 / 38
  • 41. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Wrapping-Up 5. how this can be applied in practice is yet to be seen, but we need to dispense with surface presentations and allow deep interaction; indeed, Accessibility of Big & Broad Data Wrapping-Up 36 / 38
  • 42. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Wrapping-Up 5. how this can be applied in practice is yet to be seen, but we need to dispense with surface presentations and allow deep interaction; indeed, 6. I contend that most public visualisations convey information but are not rich enough to enable us to make an informed decision; possibly, Accessibility of Big & Broad Data Wrapping-Up 36 / 38
  • 43. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Wrapping-Up 5. how this can be applied in practice is yet to be seen, but we need to dispense with surface presentations and allow deep interaction; indeed, 6. I contend that most public visualisations convey information but are not rich enough to enable us to make an informed decision; possibly, 7. adaptive enhanced visual analytics – focusing on analytical reasoning facilitated by interactive visual interfaces – might be the key. Accessibility of Big & Broad Data Wrapping-Up 36 / 38
  • 44. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Big & Broad Data Revisited Are these ideas applicable to the mainstream? Guardian Group (2014) Accessibility of Big & Broad Data Wrapping-Up 37 / 38
  • 45. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Any Questions? Contact vC: http://goo.gl/yzJFx W: http://wel.cs.manchester.ac.uk H: http://simon.harper.name E: simon.harper@manchester.ac.uk T: @sharpic G: http://goo.gl/ySGJhW Citations (BibTex) http://goo.gl/3szs2e Accessibility of Big & Broad Data Wrapping-Up 38 / 38
  • 46. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Chieko Asakawa and C Lewis. Home page reader: IBM’s talking web browser. In Closing the Gap Conference Proceedings, 1998. Mark F. Bear, Barry W. Connors, and Michael A. Paradiso. Neuroscience: Exploring the Brain. Lippincott Williams & Wilkins, 2006. ISBN 0781760038. URL http://www.amazon.com/Neuroscience-Exploring-Mark-F-Bear/dp/0781760038%3FSubscriptionId% 3D0JYN1NVW651KCA56C102%26tag%3Dtechkie-20%26linkCode%3Dxm2%26camp%3D2025%26creative% 3D165953%26creativeASIN%3D0781760038. Adelbert W. Bronkhorst. The cocktail party phenomenon: A review of research on speech intelligibility in multiple-talker conditions. Acta Acustica united with Acustica, 86:117–128(12), January/February 2000. URL http://www.ingentaconnect.com/content/dav/aaua/2000/00000086/00000001/art00016. Andy Brown, Caroline Jay, and Simon Harper. Tailored presentation of dynamic web content for audio browsers. International Journal of Human-Computer Studies, 70(3):179 – 196, March 2012. ISSN 1071-5819. doi: http://dx.doi.org/10.1016/j.ijhcs.2011.11.001. URL http://www.simonharper.info/publications/Harper2012ab.pdf. Douglas S. Brungart and Brian D. Simpson. Optimizing the spatial configuration of a seven-talker speech display. ACM Trans. Appl. Percept., 2:430–436, October 2005. ISSN 1544-3558. doi: http://doi.acm.org/10.1145/1101530.1101538. URL http://doi.acm.org/10.1145/1101530.1101538. Douglas S. Brungart, Peter S. Chang, Brian D. Simpson, and DeLiang Wang. Multitalker speech perception with ideal time-frequency segregation: Effects of voice characteristics and number of talkers. The Journal of the Acoustical Society of America, 125(6):4006–4022, 2009. doi: 10.1121/1.3117686. URL http://link.aip.org/link/?JAS/125/4006/1. Alex Chen, Simon Harper, Darren Lunn, and Andrew Brown. Widget identification: A high-level approach to accessibility. World Wide Web, pages 1–17, Jan 2012. ISSN 1386-145X. doi: http://dx.doi.org/10.1007/s11280-012-0156-6. URL http://www.simonharper.info/publications/Harper2012-1.pdf. 10.1007/s11280-012-0156-6. Colin E. Cherry. Some Experiments on the Recognition of Speech, with One and with Two Ears. Journal of the Acoustical Society of America, 25(5):975–979, 1953. doi: 10.1121/1.1907229. URL http://dx.doi.org/10.1121/1.1907229. Edd Dumbill. What is big data? http://strata.oreilly.com/2012/01/what-is-big-data.html, Jan 2012. Accessibility of Big & Broad Data References 38 / 38
  • 47. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Leo Ferres, Gitte Lindgaard, Livia Sumegi, and Bruce Tsuji. Evaluating a tool for improving accessibility to charts and graphs. ACM Trans. Comput.-Hum. Interact., 20(5):28:1–28:32, November 2013. ISSN 1073-0516. doi: 10.1145/2533682.2533683. URL http://doi.acm.org/10.1145/2533682.2533683. Guardian Group. Does funding equal happiness in higher education? http://ouseful.wordpress.com/2010/03/20/does-funding-equal-happiness-in-higher-education/, March 2010. Guardian Group. Disease and environmental factors across england and wales mapped. http://www.theguardian.com/news/datablog/ng-interactive/2014/apr/25/ disease-and-environmental-factors-across-england-and-wales-mapped, April 2014. Simon Harper and Sean Bechhofer. Sadie: Structural semantics for accessibility and device independence. ACM Trans. Comput.-Hum. Interact., 14(2):10, 2007. ISSN 1073-0516. doi: http://dx.doi.org/10.1145/1275511.1275516. URL http://www.simonharper.info/publications/Harper2007kx.pdf. Simon Harper and Yeliz Yesilada. Web Accessibility: A Foundation for Research, volume 1 of Human-Computer Interaction Series. Springer, London, 1st edition, September 2008. ISBN 978-1-84800-049-0 (Print) 978-1-84800-050-6 (Online). doi: http://dx.doi.org/10.1007/978-1-84800-050-6. URL http://www.simonharper.info/publications/Harper2008zp.pdf. Simon Harper, Eleni Michailidou, and Robert Stevens. Toward a definition of visual complexity as an implicit measure of cognitive load. ACM Trans. Appl. Percept., 6(2):1–18, March 2009. ISSN 1544-3558. doi: http://dx.doi.org/10.1145/1498700.1498704. URL http://www.simonharper.info/publications/Harper2008yl.pdf. Jim Hendler. Big data is going broad according to government internet guru jim hendler. http://semanticommunity.info/AOL˙Government/Big˙Data˙is˙going˙Broad˙According˙to˙ Government˙Internet˙Guru˙Jim˙Hendler, Feb 2012. LHC Open Symphony. The first higgs boson data sonifcation! https://lhcopensymphony.wordpress.com/the-first-higgs-boson-data-sonifcation/, July 2012. Darren Lunn and Simon Harper. Providing assistance to older users of dynamic web content. Computers in Human Behavior, July 2011. ISSN 0747-5632. doi: http://dx.doi.org/10.1016/j.chb.2011.06.004. URL http://www.simonharper.info/publications/Harper2011fl.pdf. Accessibility of Big & Broad Data References 38 / 38
  • 48. What? Why? Adaptation/Transcoding Big & Broad Data Auditory Perception Wrapping-Up References Martin Wattenberg, FernandaB. Vi´egas, and Katherine Hollenbach. Visualizing activity on wikipedia with chromograms. In Cecilia Baranauskas, Philippe Palanque, Julio Abascal, and SimoneDinizJunqueira Barbosa, editors, Human-Computer Interaction – INTERACT 2007, volume 4663 of Lecture Notes in Computer Science, pages 272–287. Springer Berlin Heidelberg, 2007a. ISBN 978-3-540-74799-4. doi: 10.1007/978-3-540-74800-7 23. URL http://dx.doi.org/10.1007/978-3-540-74800-7˙23. Martin Wattenberg, FernandaB. Vi´egas, and Katherine Hollenbach. Chromogram. http://hint.fm/projects/chromogram/, July 2007b. Tom White. Building hadoop data applications with kite. https://www.youtube.com/watch?v=aJmfgKyFcLA, Feb 2014. Accessibility of Big & Broad Data Wrapping-Up 38 / 38