Future-proofing the tagging of digital photographs.

[Greensleeves]

If you can attach metadata files to the raster (eg jpg)  image, this would be invaluable for reference purposes in the distant and not so distant future.

I was involved with geospatial data when it was a new tool for environmental management in the UK.  We we happily captured data,  made our maps and manipulated and interrogated them, and gradually added more and more datasets.   Records were kept, but these were generally in the form of hard copy worksheets, but this didn't really matter as we were all working independently. 

Then came the Foot & Mouth epidemic of 2001, local authorities and environmental organisations needed to disseminate maps and info quickly, and we suddenly realised  the importance of easily accessible  and standardised  metadata.

I know this is not the same as attaching metadata to photos, but it is similar because spatial data without any background information is practically useless, and the same applies to photos.

[Mart 'n' Al]

These are all very interesting, and I hope this thread runs and runs and helps people in the future.  I still haven't decided on my strategy, but I will report here in due course.  I hadn't heard of Dublin Core metadata standard, but my taxonomist partner is familiar with it.  When i look back over nearly 40 years of working with computers, it is interesting to think about what I implemented as leading edge technology over the years, but now would be considered ripe for the skip.

My one thought is that the longer I leave deciding on a strategy, the closer we will be to having an Artificial Intelligence solution that decides for me.  And I am not joking.  My collection of holiday photos on Google can be split be clicking on options to show my photos, by main colour, and even clicking on dog/cat/sheep/horse or church or castle or various modes of transport, and it usually gets them right, although it does seem to struggle between some dogs and some sheep.  I take a lot of photos of coats of arms, but it can't identify those.  Yet.

Martin

[a chesters]

Not directly related to the initial subject, but, to me, of considerable interest, is, who owns the copyright to photos etc "in the cloud".

Is it the photographer, the computer operator (hopefully the same person), the programme, or the cloud operator.

Also, what happens to said information if the cloud operator suffers from a serious attack of bankruptcy, let alone cyber attack, or electro-magnetic pulse?

[Guy Etchells]

The copyright holder depends on the jurisdiction some countries do not respect copyright.

In the main the copyright of a photograph is held by the photographer or the person who commissioned the photograph but that may change depending on the specific circumstances.

Owning a photograph is not the same as owning the copyright of it.

If the cloud operator goes bankrupt in most cases the photograph will be lost (wiped from the hard drives when they are reused by someone else) or sold on.
If an electromagnetic pulse occurred the hard drive will most likely be wiped clean.

Cheers
Guy

[mike175]

Copyright might also be affected by the terms and conditions you sign up to with the 'cloud' operator 

[RJ_Paton]

Anyone interested in this topic may find the photography section at https://iptc.org/ of interest.

The IPTC standard is reputed to be the most widely used and accepted standard among professional photographers worldwide and the IPTC sets the global standards for News Media

[bluesofa]

US based company, with an interesting app

"that enables users to describe their photos in their own words and use QromaScan’s cutting edge voice recognition technology to detect and embed photo metadata tags for key details such like the date, location and people. A new Relationship Manager detects the use of common nouns used for describing family members such as ‘mom’ and ‘dad’ and automatically tags the image with their full names."

Requires an iphone, data appears to be recorded using EXIF and IPTC.

http://qroma.net/qromascan.html

[tonyknight]

I'm Tony Knight, and I am the developer of QromaScan, which was mentioned here.

So QromaScan has had the ability to create metadata using voice recognition since our first release about 2 years ago.  You scan your photos with our special lightbox and your iPhone, and then use voice recognition to describe the date, location and people in the image, and they are converted to industry standard standard photo metadata.

QromaScan v3, which we released about a month ago introduces something called natural language tagging. This means that you describe a photo your own way, as you might if you wrote it on the back of a photo, and our technology uses machine learning and linguistic parsing to find things like the date the photo was taken, where it was taken, and who is in it. The full description is also embedded into the image, and writing the metadata to the file accomplishes two purposes.

First, when the image is opened, the user can see things like a map of the where the images was taken, a description to tell the user the backstory of what was going on, and other historically important information that you might have otherwise written on the back of the photo.  The second purpose is probably the most important of all.  Applying this industry standard metadata means that image is now indexed by your operating system and is searchable across all of your other images.  I have more than 44,000 images, but I can find almost any one in seconds because they are all tagged with metadata for date, location and people.  Whether I am on my phone, tablet, computer, or even any computer connected via a web browser, I can type something like "Izzy Paris" and I can quickly find just the photos of my daughter in Paris 4 years ago.

I think photo tagging is in many ways as important as the photo itself.  It provides context in a way that will be used many generations from now by those you pass your photos down to.

[sami]

Marking my place on this thread so that I can keep up with further posts. So far, it's been very interesting.

sami