The market value of a photograph is dependent on your ability to get that image into the hands of someone who wants it. All of the work that you do to rate and group your images will add value to them, by making them easier to find and bring to market. And don't forget, sometimes the "client" is you. By applying a sound rating system to your collection, you can get the maximum commercial, artistic, and personal value out of your images.
Ratings, keywords, and groupings are different categories of evaluation that can be cross-referenced with each other to narrow down your searches to a small number of likely results. For example, if you are looking for "good pictures of Josie" for some purpose, your work assigning ratings, keywords, and groupings can be very helpful.
If you use a comprehensive rating system, the concept of "good" can be defined by the rating (e.g., "search all three-star or better images"). The term "Josie," if it appears in the keywords, enables you to search through only those images that have something to do with Josie. If you have saved previous groupings of "good pictures of Josie"—images used in a birthday slideshow, for instance—you can narrow your search even further. Let's examine these tools a little more closely.
Figure 2-6 shows one visual representation of a collection of images. As you can see, if the images were not organized in any way it would be very difficult to find the particular one that you were searching for—a bit like looking for a needle in a haystack.
Figure 2-6. Finding a specific image in an unorganized collection is like looking for a needle in a haystack.
As you can see in Figure 2-7, that haystack becomes a lot easier to search if it is divided into sections. By making broad classifications of subject matter (the vertical lines) and adding ratings (the horizontal divisions), you can more easily find what you are looking for. You can, for instance, search just your best images (at the top of the pyramid) for a particular photo. If you find something that's close to but not exactly what you want, you can follow that thread downward to see if there is a more appropriate image included in that subject-matter group.
Figure 2-7. Dividing up the haystack allows you to more easily pinpoint the image you're looking for.
The most basic component of higher metadata is the rating. Rating is the evaluation of images based on relative quality. This is what you do when you look through a group of images and indicate that some are better than others.
As you rate your images, you are assigning a higher value to better pictures, and you are making it easier to find the high-value images within the groups at a later date. Rating an image as superior will make it much easier to pick it out from amongst its more ordinary brethren during a search.
In general, when you are searching for images, you will first want to look through pictures with the highest rating. If you are unable to find a suitable image among those, you can move down the pyramid, broadening your search to include images with the next-highest rating, and so on. By using ratings this way, you can instantly reduce the size of the haystack you are looking through in order to find your needle.
In addition, rating your images will help you ensure that you spend more production time on your highest-quality images and less time on images that are of lesser value. (We'll discuss this further in Chapter 6.) Ratings will also be valuable if you ever want to thin out your archive at a later date.
Having a systematic, organized rating process will streamline the tasks of searching for pictures and identifying images to throw away. For instance, you might want to throw out any images labeled as "outtakes" once the job has been delivered and paid for, or you might want to delete all neutral images from shoots with a large number of similar frames at some date in the future.
Figure 2-8 shows the most basic view of the ratings pyramid. As you can see, organizing an undifferentiated mass of photographs into a rated pyramid lets you easily separate out the best ones. This will be helpful throughout the entire lifecycle of the images—it helps you in determining how to adjust and store the images, how to thin them out later, and how to search them.
Figure 2-8. By using a comprehensive ratings system, you divide your collection into subsets that are more easily searchable.
To determine how to apply ratings, we need to examine some of the concepts behind them. Let's take a look at the DAM rules from the last chapter and how they relate to ratings:
Fortunately, our friends at Adobe have given us some very good tools to rate images in a systematic way: the star ratings. The Bridge star ratings are easy to understand and use, and they are likely to become a standard among all DAM software. The work you do with rating stars in Bridge can serve as the foundation of a collection-wide quality designation for the life of your photos.
What's so great about those Bridge stars? In addition to their front-runner status in becoming the worldwide standard, they are simple, well designed, and flexible. You can use the stars to build a set of top-down inclusive groups. What does that mean? It means that at any given time, you can chop off the top of the ratings pyramid and confine your search to that top-level subset. In effect, it lets you choose a smaller haystack to search through.
The filtering in Bridge—which I will show you how to translate to almost any other application that reads metadata—lets you confine a search to, say, images with three stars and better. Thus, you can very efficiently start a search narrowly (only the best images) and then widen it out to the next level if you have not found exactly what you want. Figure 2-9 shows how this "top-down filtering" is superior to "filtering by the slice."
Figure 2-9. Top-down filtering (right) makes searching for "all three-star and above images" more efficient. If you were to filter "by the slice" (left), you would have to search three times to get the same results.
Most photographers I know have had the experience of finding images that they'd forgotten about: sometimes these have become favorite images. By rating images for quality when you first edit them, or any other time you look through them, you keep great photographs from "slipping off the light table."
The stars make systematizing easy; you'll have to exercise your brain a little to be comprehensive. In order to do this, you will need to make very broad definitions for each of the rating designations. These definitions will need to span across all the different types of photography that you do—for example, you wouldn't want three stars to mean "very good" for commercial work, and "pretty good" for personal work.
Remember that these designations will be helpful not only for searching, but also for image handling. In a minute, I'll show you the designations I use, and how I came to those definitions.
When deciding what designations to use, bear in mind that your collection will grow many times larger over your lifetime. You need to leave some headroom to grow. For instance, I am not using the fifth star in Bridge yet, because I want to save this designation for a time when my collection is much larger.
I think the greatest danger in terms of carrying a rating system into the future is that of the metamorphosis of the "ratings pyramid" into a "ratings light bulb" (Figure 2-10). A ratings light bulb would be much less useful.
Figure 2-10. The ratings light bulb isn't as handy as the ratings pyramid—there's much more value in being at the top if it's lonely there.
Because rating is a valuable tool that helps you determine how much work to do to a file, you should make a good effort as early as possible to assign ratings to your images. If you rate right away, you can spend the largest part of your Camera Raw adjusting time on the best images. Likewise, your time creating custom keywords will be much better spent if you work mostly on your best pictures. Rate your images as soon as possible after renaming, and make that work permanent.
Ratings are rough groupings, applied across your entire collection. I suggest trying to split by orders of magnitude (1 four-star image for every 10 three-star images, 10 three-star images for every 100 two-star images, and so on), not by subtle degrees. Of course, this doesn't work for every shoot, but if you keep this goal in mind, you have something to aim for. I'll outline later why this works from a mathematical perspective, a file-handling perspective, and a searching perspective.
It's important for you to decide what you mean when you give an image a particular rating. That rating will be a general quality guide and a file-handling guide. In this section, we'll look at the ratings I use, and the criteria that go into making the rating evaluations. Figure 2-11 shows examples of how I use my various ratings.
Figure 2-11. Examples of my ratings system in action. Clockwise from the top left: TrashMe (this is a "Polaroid"), Outtakes, Unrated (I need to examine in Camera Raw to rate this one), neutral, one star, two stars, three stars, and four stars.
In database geek-speak, the value is the name or meaning of the variable you assign—in this case, the label. Ratings can be neutral, positive, or negative. Neutral images receive neither a positive star nor a negative label. At this point, for positive ratings I use four of Bridge's five possible star ratings, right out of the box as Adobe intended. As I mentioned earlier, this is a very efficient way to use the rating pyramid, because when you're searching it lets you start at the top and work your way down quickly.
I use the colored labels in Bridge to enable me to rate negatively and to indicate images that have not yet been rated. In my system, for instance, I assign the red label the value "Unrated." I discuss what I use the various labels for below, and I'll show you how to set these values in Chapter 5. (In Chapter 6, we'll go over the rating workflow, and I'll show you how you can transfer your ratings for use in other applications.)
My decision criteria for assigning the positive star ratings are presented in the following list. Note that I use slightly different criteria for personal images and for commercial images, but that the general quality assessments and the workflow ramifications integrate well together.
These are the designations that I use:
Neutral images are ones that are neither good enough to rise above the crowd and get a star, nor flawed enough to deserve a negative rating. This is the most common rating for my personal images, encompassing more than 50% of my personal work. Some of these images are "diary" images, ones that I keep to help me remember what things looked like, who was there, or what happened. These will probably never be printed, or shown to many people in any form, but I want to keep them nonetheless.
Neutral work-related images are more defined by what they are not: they are not bad enough that I want to throw them away once the job delivers, and they are not good enough to send to the client in proofs or web galleries. For an editorial job, I may keep many of these neutral images in case the editor wants to "go deeper" into the take for some content reason. For a tightly structured portrait job, I don't generally give many images a neutral rating—the images tend to be either good enough to present to the client, or flawed enough to be tossed once the job has been paid for.
I use the one-star designation for images that are good enough for inclusion in a web gallery to be presented to the client. For personal images, one star means that I might want to use them in a web gallery, slideshow, or print. Through the life of the archive, these images will get much more attention than the neutral ones—even the broadest searches will generally be confined to one-star or better images.
Assigning one star to an image is a very rough cut. If I am in doubt as to whether the image deserves it, I assign the star. I think of it as a kind of large group that I put photographs into to evaluate later. Because neutral and worse images are searched only rarely, if you aren't sure about an image, it's probably best to err on the side of inclusion and give the photo a star.
For business images, I assign two stars to photographs that I think are the best of the shoot. An executive portrait shoot might generate 40 images to present to the client (each of which receives one star) and 4 that I think are really the best (which receive two stars). For most business applications, this is all that I feel I need out of a rating system: good enough to present, and recommended by the photographer. As I go through images in Bridge, I try to keep a 10:1 differentiation in rating in mind (i.e., 1 two-star image for every 10 one-star images). I find that this is a very useful way to narrow down the shoot. Of course, if the shoot is large enough, this rubric may not narrow down the shoot enough. In those cases, I may use three stars.
For personal work, the calculation is similar: images get an additional star if they are the best of the take, and this designation should be used sparingly. Images that get a second star effectively become the "best of" the collection or group. The difference between one and two stars doesn't really mean anything unless you use the additional star sparingly, so be frugal.
I use the three-star designation even more sparingly. An image gets a permanent third star in one of two ways: either I like it enough that I think it's a strong stock image or portfolio candidate, or the client has chosen it as an image to be prepared as a master file. In the latter case, I might not even like the image that much, but because of the work done to it and its value to the client, I think it makes sense to tag it as particularly valuable.
Note that images that have been selected by the client for batch conversion do not get this designation. By definition, there are more of these images, and I put less work into them.
The four-star designation is reserved for images that are worthy of the "best of collection" designation.
I am currently resisting the urge to use the fifth star. One day, it will be useful to further divide images within the four-star bestof- collection group.
As you can see, I don't give out high ratings very freely. When you're working with a large number of images, it's best to set the bar high and really think about the quality designations that you make—if you find yourself putting half your images into the three-star or higher categories, it's definitely time to regroup. Remember, the pyramid is most useful when it retains its proper form.
I use the labels in Bridge to apply the following negative ratings and status designations (I also use the same designations within my cataloging software). The number and color in parentheses are the label assignment key and the label color in Bridge:
This status tag indicates that the image has not yet been evaluated. This designation is very helpful from an evaluation standpoint, because it lets me distinguish between an image that is neutral (deserving neither a good nor a bad rating) and one that has no rating because it has never been evaluated. From a workflow standpoint, the Unrated label can also be useful as a marker to show where you left off when evaluating images.
If you are on a tight deadline and are able to evaluate only a small subset of the entire shoot, use the Unrated tag to note which images still need rating. Additionally, I sometimes use this tag to remind myself that an image needs to be rated for critical focus issues in Camera Raw, where I can get a full-sized preview of the image. I often also apply this tag to personal images, because they have less "deadline pressure" associated with them—I tend to save these for a day when I can go through them at my leisure.
This is the first of the negative ratings. This designation is for images that I probably won't need, but I'm not ready to trash just yet. I use this designation for images that I expect to erase eventually, but that may contain a useful element such as a hand, an item of clothing, or a part of the background (Figure 2-12). An image that is backfocused, for instance, might be useful to copy and paste elements from. In general, this designation is for images that can be tossed once the job has been delivered.
Figure 2-12. One reason to delay throwing away outtakes is that you might need to use an element from one picture in another picture. In this case, the client wanted the sign removed from the final photo. The best image to clone this area from happened to be an image that was an outtake.
This rating is for images that are to be thrown away immediately. Of course, you could throw away images individually, but there are a couple of reasons not to do this. First, it takes more time to throw away individual images as you edit, and it breaks the workflow pace. Additionally, if you are throwing out many images, you might find yourself accidentally throwing out the wrong one as you move through a set. Third, and most important, using the TrashMe label lets you view your trash selections in the context of the entire shoot, and confirm that you do indeed want to delete the designated images forever. You can confirm, for example, that you are keeping a photograph from every situation—all the pictures of Jim may be pretty bad, but you may decide that you want to keep at least one.
I save the last two labels for temporary usage. If I want to make some kind of selection of images, I can assign one of these labels a temporary value and use it to quickly apply a designation to the pictures. For instance, if I am looking over a shoot with a client, I can temporarily define the blue label as "Client X Select" and apply it to the images that he likes. I might also use this label to designate an "Alt Pick" (an image that I like, but that I don't think the client will want to use).
As we think about the designation of ratings—what they mean and how to apply them—it's useful to go through a little bit of math. In order for the star ratings to be of value (and to keep the ratings pyramid from turning into the ratings light bulb), make some mental notes about how many image files should be getting a particular rating. I'll use my own collection as an example. (These are rough numbers.)
Table 2-1 shows the current breakdown by rating of my current collection of digital originals, taken in the last three years. If I keep the shooting rate and the rating system constant over the next 30 years, I could expect to see a collection with the numbers listed in the righthand column. You can see that putting a bunch of images into the high rating categories would make these divisions much less useful in the long term.
|Star rating||Year 2005||Year 2035|
|Neutral (no stars)||68,000||680,000|
Using a disciplined rating system will enable you to find the images you want more quickly and easily. If you cross-reference a simple rating system with bulk metadata, or with keywords (see the next section), you'll be able to search for your needle in a much smaller haystack.
Keywords are words or phrases that you associate with a picture to describe the subject matter, style, usage, or connotations of the image. These descriptions can be of great use when organizing and searching your picture collection.
Keywords can be abstract terms (like "victory") or subject-oriented terms (like "cat" or "Maddy"). Subjectoriented terms are generally easier to apply because they require less careful consideration. Abstract terms are generally economical to apply only to the very best images, such as ones that will be made available in a searchable stock photography database.
The term "keyword" can have two meanings: it can refer to the term itself, or it can refer to the place where the keyword lives (in the IPTC Keywords field, or in the virtual sets in your DAM program). It's important to understand these differences—just because you want to associate a term with an image does not necessarily mean that you want that term to live in the IPTC Keywords field.
Some of the keywording that you will do should be best left as private metadata (information intended for your use but not to be shared with others). Anything you write into the IPTC Keywords field becomes embedded metadata, and is therefore public. (See the "Storing Metadata" section for further discussion about private and embedded metadata.)
As your collection grows, finding an image by its associated terms (keywords) will become more useful and feasible than trying to find an image by remembering when you took it or where you stored it. To maximize the value of your sorting work, you should develop a method of tagging that is consistent.
Your designation for both ratings and keywords should be standardized, so that you are performing only one search—collection-wide—to find all applicable images. To do this, you will need to use a controlled vocabulary. A controlled vocabulary is simply a set of descriptive terms or keywords that has been standardized into a list.
Figure 2-13. Keywords: Jobs, Annual Report, Executive Photograph, Group Shot, Portraits
Ratings are qualitative assessments of images, whereas keywords are content- based or usage-based assessments. Groupings can be rating-, content-, or usage-based assessments, or some combination of all three. Groupings are collections of images that share a particular quality, such as "these came from the shoot today," "these are my best pictures from the last year," "make 4×6 prints of these for Mom," or "these are all my pictures of Josie."
Some groupings may be generated by a simple keyword search, such as pictures of "Josie," or a keyword search combined with a rating search, such as "two-star and better pictures of Josie" (Figure 2-14). More complex—and valuable—groupings may be made by hand-picking images from these search results and saving them as a virtual set ("Selected images of Josie for slideshow").
Figure 2-14. Cross-referencing quality with some kind of subject matter information can let you generate a specific set of images. (This screenshot is from iView MediaPro.) Using cataloging software, you can take these cross-referenced sets and do further selection.
Groupings are valuable because they turn your collection of images into smaller, subject-oriented "haystacks" (called virtual sets). Using virtual sets can greatly increase the speed and efficiency of any searching or browsing that you do. By systematically creating groupings of images as you look at and work with your pictures, you will gradually add considerable value to the collection.
The ability to create multiple "virtual" groupings of images is one of the most important capabilities of cataloging software. All assignment photographs, for instance, can live in a virtual set ( Jobs) that can be expanded and collapsed for easy viewing. Because the virtual grouping adds little data to the catalog file, and does not involve making duplicates of the images, you can make a practically unlimited number of these virtual sets, and you can nest them together in multiple hierarchies.
Examples of virtual sets that I use are Jobs, Personal, Collections of images to print, Collections to send to my stock agency, and Collections to consider for portfolio use. These groupings are quick and durable identifiers of my most valuable images. I also find that the best of my images may live in many groups (e.g., Web Portfolio, Print Portfolio, Stock Submission 050202, and so on). When I want to find an image quickly, one of the first places I look is in groups that I have already made.
As you consider making groups, again remember a few of the DAM rules:
The most effective way to make groups is simply to save the results of every search or division of images that you do into a virtual set. In the course of doing your regular work with your images (for example, doing a stock or portfolio search, making a slideshow, or selecting images that the client want to have made into master files), you will often find that you are culling images into groups. If you use your cataloging software to make and save these groupings, you will be creating valuable virtual sets that can speed up your work for the lifetime of the collection.
Groups are very useful, but don't go too crazy here. Don't make groups just because it's possible; instead, make them (and save them) as you actually need them, and not before. The groups you make because you need them are the ones that will turn out to be most valuable to you.
Remember that by assigning bulk metadata, keywording images, and rating your pictures, you can generate some pretty specific groups automatically.
If you are a professional, or ever foresee licensing your photographs to anyone, deliver files with the license and your contact information embedded in the photos, and keep a record of those licenses. As an aside, you should also register copyright. You can find a complete tutorial on how to copyright images at http://www.thedambook.com.
Figure 2-15. There's a place to put nearly every kind of information you want to keep about an image. Keywords: Jobs, School, Motion, Lockers, Students, Long Exposure, Blur
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