Notes from the session are below in the comments OR on Google Docs at bit.ly/eZrbqH
I am struggling with the problem space around how best to provide digital images for teaching and research across a large campus and multiple disciplines. How to get one’s head around issues of
- usability (discover and presentation)
- ingest/cataloging,
- preservation, and
- rights management
I love the cool “technology ecosystem” graphic that shows Omeka falling at a crossroads of Web Content Management, Collections Management, and Archival Digital Collections Systems, and would like to know more about how this might work with more academic focused products, like ARTstor SharedShelf or Luna Insight .
One a similar but different note, the draft ACRL/IRIG Visual Literacy Competency Standards for Higher Education says a visually literate student…
- identifies a variety of image sources, materials, and types
- conducts effective image searches
- situates an image in its cultural, social, and historical contexts
- evaluates the effectiveness and reliability of images as visual communications
- uses technology effectively to work with images
- produces images for a range of projects and scholarly uses
- understands many of the ethical, legal, social, and economic issues surrounding images and visual media
Are we ourselves visually literate? Are the DH tools and projects that we are creating promoting these skills in our users?
#1 by Moira on March 4, 2011 - 8:42 pm
Kim, I’m very interested in your session proposal.
#2 by Kim on March 5, 2011 - 12:40 pm
Thanks to all the session participants for a great discussion. Here are my notes BUT I hope you will add more comments, too. Kim Collins
I. Permissions – a lot of work required of the scholar who wants to publish images
a. Use Fair Use – don’t let the impulse for safety keep you from doing good work
b. CULTURE of risk aversion – FORGE AHEAD with scholarship, ask permission and highlight that something is an ACADEMIC article
c. Make a Good Faith Effort- and document every e-mail , letter, attempt
d. If EDU server limits you, consider web publishing outside our academic institution – issues of long-term preservation? Nothing new
e. Safe places? Flicker Advanced search limited with creative-commons, asking the museum, library, repository directly, etc.
II. Visual Literacy ACRL/IRIG Visual Literacy Competency Standards for Higher Education
a. How can the visual articulate DH?
b. PROBLEM that people in a very visual culture don’t know how to read images – they have never been trained in this critical skill – we teach them how to critically analyze text, but often people see images as just something to help visualize that text – rather than a primary sources that has it’s own vocabulary, context, meaning, etc.
c. Solution? Education system acknowledges the need to promote these skills and makes it part of the protocol. Professors teach to this and include assignments that help foster Visual Literacy competency. We build this into our DH tools and projects, see rural image cooperatives About our Site Banner page
III. Things we viewed during the session
omeka.org/about/ How Omeka fits into the Technology Ecosystem
www.googleartproject.com/ Art Project, powered by Google
www.ruralimagecoop.org/ Especially the About our Site Banner page
www.flickr.com/search/advanced/ “only search with-in Creative-Commons-licensed content
smarthistory.org/ Smarthistory: a multimedia web-book about art and art history
IV. Other things we discussed:
www.nocaptionneeded.com/ Robert Hariman and John Louis Lucaites provide the definitive study of the iconic photograph as a dynamic form of public art.
ireport.cnn.com/ CNN iReport – Share your story, discuss the issues with CNN.com
Flickr Badge Photo Sharing – how the widget works in LIBGuides
prezi.com/ Prezi – The Zooming Presentation Editor
www.artstor.org/shared-shelf/s-html/shared-shelf-home.shtml
ViPR – Visual Pattern Recognition … Google Goggles: Google publishes facial recognition patent, could use social network photos…but also applications with academic projects, for example globalhealthchronicles.org/smallpox could identify one person in one photo and then have all that face automatically recognized and identified in other images throughout the project
Tea Party Adopts ‘Don’t Tread On Me’ Flag
www.npr.org/templates/story/story.php?storyId=125184586
work of Alex Juhasz about Learning from YouTube that MIT has just “published”
MIT Press link to the book with ISBN info, etc.: mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=12596 and The book itself: vectors.usc.edu/projects/learningfromyoutube/index.php
#3 by rebecca.s.koeser on March 10, 2011 - 6:36 pm
A few more things that we talked about from my notes…
One thing we talked about was some of the relevant technology that is available.
I know there are tools/services to search for images by a sketch/drawing, but when I looked for this I couldn’t find the one I had come across before. The most prominent one now seems to be www.gazopa.com/ but I don’t know how good it is.
There is also “reverse image search” – so if you find an image you might be able to figure out where it came from. Examples: www.tineye.com/ and saucenao.com/
One question that was raised in the session was, if you are making a repository of images available, should you make them google-able? With the image search options Google makes available (e.g., search by color or type of image), that seems like it would be valuable – see googleblog.blogspot.com/2009/07/search-options-now-on-google-images.html for more.
One thing we didn’t address in the session, though, is how much metadata do you embed in the photos themselves? (Which seems to me to be even more important when people may discover images out of context via search engines Google.)
Picasa has the capability for facial recognition in photos –
lifehacker.com/#!5365267/picasa-35-organizes-your-photos-with-facial-recognition