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I have a lot of photos from site visits to different libraries around the U.S. I ultimately want to share these photos on a website so that viewers can sort by the various tags (e.g. "student study spaces"). The tagging needs to be done on local windows machines (due to users I am working with). I want the website to be as simple and clean as possible.

here are two components (A) easily tagging the exif data on a windows machine and (B) creating a website w/ upload process that extracts and creates tags from the exif data.

I spent a lot of time searching for a good workflow, and didn't find anything perfect. Flickr, Picasa, etc. all had flaws. I also searched for similar questions here on the photography stackexchange but didn't find this question.

So, I am going to provide my best custom solution as an answer below, and then hope that this either helps out other people, or better yet, stimulates an even better answer.

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    \$\begingroup\$ This strikes me more as a software development question rather than a photography one. You might ask in Stack Overflow for a better response. \$\endgroup\$
    – kenny
    Sep 16, 2013 at 16:04
  • \$\begingroup\$ Thanks, @kenny ... I thought about that but figured the stackoverflow peeps would provide a pure python answer, and that photographers here may have more of a turnkey solution. In a few hours, I'll be able to post my solution (didn't have the reputation to do it right away). \$\endgroup\$
    – Steve Koch
    Sep 16, 2013 at 21:19

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(I was meaning to post this answer right after making my post--but didn't have the privileges to do so. In the meantime, there is a good answer posted by AJ Henderson that I want to take a look at.) Here is the best solution I've developed so far.

Resources

  • Windows 7 platform for tagging .jpg images
  • Access to a hosted server on bluehost.com

Part A -- Tagging

I found that Microsoft "Photo Gallery" (part of Windows Live Essentials) was the best GUI tool for adding multiple tags to images AND adding these tags to the exif data. I could tag easily with Picasa, but couldn't figure out how to get the tags to go into the exif metadata. A surprisingly helpful feature of Photo Gallery is that you can rename tags and it will change the exif data for all photos with that tag. So you don't need to have your tags completely decided ahead of time. Another bonus is that once you start tagging, these tags show up in Windows Explorer.

Part B -- Uploading, extracting tags from exif, and displaying galleries

I toyed with the idea of just creating a website from scratch, and using python scripting to create the galleries, etc. However, in the interest of time I searched for a more out of the box solution. I've found a decent one:

  • Wordpress installed on my bluehost server
    • I am using Wordpress 3.6 with the "Photo Book" 1.0.6 theme. I just picked that theme without much thought, I am sure there will be a better one.
  • NextGEN Gallery by Photocrati plugin.
    • This was the breakthrough. It adds a gallery function that will automatically create tags from the photos exif data as you upload the photos.

That's where I am now. You can see my status here: http://sjkode.com/PT/ (click on a tag in the cloud). I believe this workflow is sufficient and now it's just a matter of customizing the WP site to make it look as simple as I want and get a better light box for slideshows.

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I don't have a specific process for you, but I know that you can set keywords in Lightroom and then export them in the EXIF information when you do an export of the images for posting. There are then EXIF reading libraries that can be used to pull in that data. I don't know of one particularly for WP, but I know the capability exists for Piwigo and is provided by an independent library, so presumably the functionality should be available for some WP gallery as well.

If you are not particularly married to WP, then Piwigo could do it for you and runs on PHP and MySQL, so if your hosting is WP compatible, it should also be Piwigo compatible unless you are using a WP hosted account.

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