- From: Laura Carlson <laura.lee.carlson@gmail.com>
- Date: Wed, 19 Sep 2012 06:26:30 -0500
- To: Silvia Pfeiffer <silviapfeiffer1@gmail.com>
- Cc: Geoff Freed <geoff_freed@wgbh.org>, John Foliot <john@foliot.ca>, Sam Ruby <rubys@intertwingly.net>, HTML Accessibility Task Force <public-html-a11y@w3.org>
Hi Silvia, The incorrect usage argument is hollow. Many web pages have incorrect usage i.e., duplicate id values when they should be unique on a page. Arguing that some authors use longdesc ineffectively is no more sensible than arguing that we must obsolete the id attribute because some authors or spec writers [1] get it wrong. The argument is specious and a waste of time. Incorrect usage is not the fault of a mechanism. Almost every attribute and element is incorrectly coded or applied in ways not intended. That does not mean the feature is useless and should be killed. It only means specification, education, or tools may need improvement. [1] http://lists.w3.org/Archives/Public/public-pfwg-comments/2011OctDec/0000.html On Wed, Sep 19, 2012 at 6:16 AM, Silvia Pfeiffer <silviapfeiffer1@gmail.com> wrote: > On Wed, Sep 19, 2012 at 9:05 PM, Laura Carlson > <laura.lee.carlson@gmail.com> wrote: >> Hi Geoff, >> >> On Tue, Sep 18, 2012 at 4:52 PM, Geoff Freed wrote: >> >>> To bolster John's point, I'd like to say that there are efforts-- intense efforts-- underway to improve the quality of image descriptions. For example, NCAM expends a large amount of time and effort every year training publishers, teachers and others in the art of writing long image descriptions. I'm sure there are several others on this list who can (and, I hope, will) raise their hands and say the same thing about what they do. >> >> I teach how to write alternate text and longdesc in one-on-one >> settings as part of my daily job duties and formally in workshops >> multiple times a year. Debi Orton attested in the last HTML WG survey >> on ISSUE-30 that she always teaches longdesc and how to use it >> effectively. >> >> We have longdesc support base existing in the form of authoring tools, >> documentation, tutorials, books, etc. all of which is all a part of >> our evidence so I will not repeat it again here. > > This is all great and really necessary. But can we quantify the > effect? It would, for example, be a good argument if we were able to > say that 4 years ago we made this analysis and only 0.1% of images hat > a @longdesc and 99% of those were wrong, while now 1% of images have > one and 70% of them are correctly implemented. Just making up numbers > here - but something like this would be really helpful. > > Silvia. -- Laura L. Carlson
Received on Wednesday, 19 September 2012 11:26:58 UTC