![]() Remember that the archive will grow all the time. Do not make the folders too small, several thousand images in one folder is not too much to ask for, but keep them small enough so that they can fit into a backup medium like an optical drive. In others words, the folders organization must be the physical information layout. The organization should be simple, unified and scalable, and it should be independent of the storage medium on which you host them. Keep in mind that you have to migrate one day onto some bigger volume. ![]() Your image files have to be somehow organized within the computer, you have to decide if others should have access to your photographs (sharing), if you put them on a dedicated drive, on a network drive etc. The first thing to do and to know before you put anything onto your system is to build an information structure (as opposed to data structure). By adjusting digiKam’s settings accordingly you can control what kind of data remains private and what will be embedded and eventually become public. On the other hand all non-embedded metadata in the database can be considered private as they stay in the database and go nowhere else. One could say that all file-embedded attributes are potentially public since the images may be exported, sold, and copied to other places and people. One distinction has to be interjected here between private and public metadata. If you do not transcribe some of it into your DAM system, it will be lost eventually as much as every event fades into oblivion over time. At the beginning, at the time of taking a photograph, all metadata is in your head (except for the Exif data). So if you can narrow down your search by remembering place or time or camera or theme or rating or owner you stand an infinitely better chance to find it quickly than by just one of those criteria or none. You will remember past events in a different context, it’s a fact of life. ![]() The key thing to remember is that you don’t know how you or somebody else will try to find an image 2 years ahead of our time. In terms of selection criteria for a DAM system, digiKam fares very well in terms of completeness, versatility, speed, scalability, accuracy and openness.Ī Geolocation in France Filtered by a String and Rating Value ¶ Searching for Salagou, having more than 3 rating stars, shot in France will surely leave you with very few candidates. Imagine having 800 photos of your loved one. Combining these views is the very powerful method to narrow down the search for a file and to find it quickly. Metadata categories as listed here are in fact different views of your photo library. As if this was not enough, you can search many standard metadata items like camera model, lens, coordinates, image size and many more. Use-Cases with digiKam ¶ĭigiKam provides a number of methods to classify photographs: filenames, albums, collections, time-stamp, tags, rating, GPS position and captions. The upcoming semantic web will totally integrate into and add value to a DAM environment. Keep in mind to be concise, plan for the future (30-50y), do it once. The ROI (return on investment) of DAM has been estimated in different studies to be better than 10. ![]() The dual approach to store metadata in a database and in the image files guarantees ultra fast searching and secure archiving freely accessible to other applications, platforms and formats.īut as much as there is no such thing as a free lunch, there is no free cataloging or DAM - those who spend the initial time of building a systematic method of their own will be better off as time passes and the number of photographs multiplies. And if you don’t know how many images are in your files you’re surely not using digiKam. We dare-say if you have more than 1000 photographs on your computer in no-DAM fashion it takes you too long to find any particular image. ![]()
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