In the first part of this series, we talked about naming files, storage and the importance of backup. We looked at catalogs and structures in the second part, and ways to optimise the way we manage, select and deliver our images by clients and project. The third part to the story is how to find images system wide, independently from clients, projects, or file structure. We enter the powerful world of “keywords”.
The concept of key-wording is straight forward: A keyword is text information which is added to the meta-data of our file, and its sole purpose is to easily find all images with the same keyword. To use keywords effectively however, it is helpful to have a plan, and understand the power of a smart keyword hierarchy.
If you apply the keyword “Green apple” to one photo, and “Red apple” to another, some applications may not show these images when you search by keyword “Apple”. If however we apply “Green, Apple, Granny Smith”, we have applied three keywords (separated by commas), and the combination of the three is what makes keywords so powerful. You might think, this is a very obvious and rather simple example, but the point is to think about what keywords you use, and use them consistently. One day, we might like to find all images which predominantly feature a green colour, and the above simple example starts to make a lot of sense.
The obvious keywords to apply are of course subject driven, the person (or object) in a photo, the location perhaps, and the clients name. Where consistency starts to become essential is when you leave the realm of obvious keywords, and you dive deeper into the rabbit hole of ways to “describe” or tag your images, emotional sentiments like “happy”, “smiley”, “upbeat”, or “sad”, “moody”, “depressed”. Will you remember half a year down the track, if you used “happy” or “Happiness” for similar images?
Applying such “descriptive” keywords opens up a huge amount of possibilities, but consistency is key. Not to mention that the more images we produce (and the more keywords we use), our list of keywords will grow, and we will end up with a long and cumbersome list, which is hard to view and slow to maintain.
The best way to avoid an endless list of keywords is the creation of a Keyword Hierarchy. Using a keyword hierarchy has the added benefit, that it allows you to work much faster, since applying one keyword can automatically produce an entire series of keywords on export. In the “keyword Tag” window, you can chose, if such keywords (and possible Synonyms) should be included on export.
In some cases, the export of grouping keywords make no sense on export (if you use them for pure organisational purposes), in other cases, it is very helpful.
A good example of such a keyword hierarchy is “LOCATIONS”. We wouldn’t include the headline “locations” on export (so we un-tic the according checkbox), but surely all underlaying keywords will be helpful. As our keyword list and structure becomes more and more elaborate, we can simply apply the word “Union Station” to an image, and all the other location information will be taken care of (assuming, we have created a structure like the one below):
LOCATIONS → USA → California → Los Angeles → Union Station
Our image, even though we only tagged it with one keyword (“Union Station”) will be found in any search for the higher ranked keywords (like “California” or “Los Angeles”), and all of these keywords will be included on export.
Other ideas for such keyword groups could be “Subject”, “Colour”, “Mood”, “Style” etc. And lastly, not to forget a group called “Portfolio” (with perhaps grouped keywords like “Portraits” and “Landscapes” etc), so we can find all of our absolute favourite images with a couple of clicks.
At the end of the day, the way you apply keywords is a question of personal preference, some use it extensively, others don’t use it at all. When done consistently however, it becomes yet another (and very powerful) tool to find and filter our images throughout our entire system.
Article and image © 2012 by Stephan Bollinger.
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