Anyone who’s laboured through the task of digitising physical photos from multiple (analogue) sources will have been confronted with the issue of how to sort them or, more specifically, what to name the files before introducing them to an existing collection of (digital) images.
Although names may be unique, throwing all files into one directory/folder is dangerously stupid. Worse, still, is the scenario when photos are strewn across several data carriers — whether they be hard drives, optical discs, memory cards, NAS, or the cloud.
A simple internet search reveals a wide choice of photo management/organisation applications and as many top-ten lists and reviews thereof. Any media professional worth his salt will already be using some form of digital asset management software, and anyone calling himself a serious photographer is probably using Adobe Lightroom/Bridge — which consistently score at the top. XnView MP, FastStone and Apple’s Photos are other programs that appear to be the most promising for photo collectors and family historians who need a database to help sort, geotag, share, or caption their stash or to keep track of each photo’s most dominant colour.
For those with the burning desire to have mobile access to their photos and don’t have an issue with cloud services foraging through their personal stuff, then Google Photos, SmugMug/Flickr or 500px would probably meet their requirements (until your stuff is inevitably deleted when yet another cloud evaporates).
If you are comfortable with all this, by all means, jump on the bandwagon to see what happens. [Google Photos] does have some fascinating image search capability. — John C. Dvorak
As for me and my personal collection of family snapshots?
While AI- and ML-powered functions such as face recognition and automatic image enhancement can certainly be helpful gimmicks, I simply don’t need or trust them right now: I know the people — else I wouldn’t keep photos of them. In fact, anyone with the slightest modicum of common sense ought to be capable of creating a suitable folder structure on a local drive (backed up, of course).
My core photo folders are named after their subjects: People, Places, and Objects.
If, for instance, I were looking for photos of my mother I would expect to find them in a subfolder named Mother. It’s not exactly rocket science, nor does it matter to me if she was wearing a red dress, a floral blouse or whatever the dominant colour of her surroundings happens to be. To a fashionista, however, these factors would probably be as important as ingredients are to an instagramming hobby baker or the species and location to a wildlife photographer. Everyone has their own filing criteria, and that’s fine.
Additionally, since shots taken during holidays, parties or trips could overlap one or more of the aforementioned core categories, I drop these into a separate folder named Events because those are centred around a spot on a calendar instead of a map or family tree.
While this approach has served me well for over twenty years it is not without its challenges. Let me explain.
Collating different digital sources created over various periods and from several cameras will inevitably cause an overlap in file names. Each camera and scanning utility have their own naming standards, and DSC00001.JPG or scan0066.jpg aren’t particularly meaningful in the long run either. I needed a method to rename thousands of (existing) image files into something meaningful. Enter a powerful utility named BRU (Bulk Rename Utility) which allows me to prefix the generic DSCF0001.JPG convention (or whatever it may have become over the years) with a YYYYMMMDD-HHMMSS_ string based on the available EXIF date. The likelihood of me having two photos taken with two different cameras at the same second is unlikely.
The photo above, for instance, has now been filed away with the name 20090713-181301_074_Frankfurt Tour.jpg. I usually strip the typical DSC-prefix (but keep the last three digits of the number) and may even add an extra word or three to the file name for additional info. It then gets placed in the appropriate folder, cementing its position in time, space, and/or subject matter. It sorts beautifully in a file manager/explorer window and appears before the next in chronological sequence in an image viewer.
This approach works great for me personally and doesn’t depend on (potentially costly) external utilities or a database to maintain any specific tags (ergo: device independent). Your mileage may differ.
It is, however, dependent on two things: The presence of EXIF dates (some were wilfully removed in my early days of digital photography), and the accuracy thereof.
And this is where the fun starts!
Although I know that the photo above was taken at the almost same time as the previous one, the embedded time stamps didn’t match by a significant margin. The camera’s internal clocks were wrong. So when exactly were the photos taken?
Sometimes you’re lucky to find a clock somewhere in the background — and hope that it’s correct. Make a judgement call, manually adjust the EXIF dates for photos taken with that camera on that day, sync them all up, and then do a bulk rename. No matter the source camera/s, you now have a chronology of an event. This, of course, isn’t much of an issue if snaps are taken with smartphones where your network provider keeps the time.
Worse still is when you travel across time zones. Smartphones adjust, digital cameras don’t. Then what… do you stick to your home time zone? What happens if you take a sequence of photos mid-air… while flying westward? Your cameras’ internal clocks also need to be adjusted twice a year thanks to daylight savings time.
Then there are the photos that have no time stamps or cues of any kind because they’re from analogue sources (or you were a fool and removed them). Wildcard placeholders (I use an “x”) at least help ensure that the photo is sorted within close proximity of when it was really taken.
This picture of the Rottweiler girl and her dork, for example, was taken in 1988.
Only the year is known with a confident degree of certainty; the month and day (and certainly the time) are unknown. The file is named 1988xxxx-xxxxxx_Print0186.jpg; where the year is known, “x” are placeholders for unknown values, “Print” signifies it’s a scan from a print, and “0186” is an arbitrary number assigned during the scanning procedure (which I keep intact because there are other photos from that day in 1988).
Simple, right? Curtis Biesel at Scan Your Entire Life, quite coincidentally, dishes out almost identical advice.
As for my own negatives, I was enough of a trainspotter to have originally jotted down the date (but not the time) when each photo was taken. External information like diary entries also helped, as did the frame numbers on strips of negatives: these indubitably show the sequence in which the snaps were taken. The timeline is a useful forensic tool.
In the case of the slides originally curated by my parents I was almost entirely reliant on the accuracy of their handwritten scribbles — if any. Your detective work begins by reassembling the original film development sequence based on the type of photo mounts; in my case they were by Kodachrome (white cardboard/plastic), Agfacolor (blue), Perutz (green), and Pakon (white) — or the typesetting of text on them.
Additional clues can be found via vehicle registration numbers (locations), grass and foliage (seasons), clothes and hairstyles (age), the construction progress of buildings in the background (year, cross-referenced with Wikipedia or elsewhere) — or even the length of shadows (time).
What hardly ever gets mentioned is the sheer amount of time the endeavour takes!
But now it’s done. On to the next project…
