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This is a crucial use of images that cuts right to the bottom line: timely payment of the invoice. Specific, unambiguous visual information linked directly to contract information is useful in numerous scenarios, such as construction progress photos, property insurance claims, product placement in retail environments (supermarkets, bookstores, department stores), and equipment or fixture installation.
STEP 2. IMPLEMENTING THE ARCHIVE
This is how Clear Channel identifies its image databases.
The basic components of this system, image-based data, includes photographs of structures, advertising content, installations, equipment, locations, creative images, and maps. These images are tagged with the supporting text
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data that makes them "smart." There are three dedicated image databases, which hold a total of more than 800,000 images:
1. Bulletin Inventory Search (BIS). Each of Clear Channel's 56 offices has a dedicated server that stores images of all the displays in the area served by that office. These repositories are the main source of images used for billing and site-specific sales, marketing, and operations.
Typical BIS image
2. Digital Image Library (DIL). The DIL has images of all types of outdoor displays dating back to the beginning of the company in 1901. The account executive goes to the marketing manager and says, "I need to show a client examples of fashion billboards," and they go to the DIL and search it and pull down these images.
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Creative example from DIL
3. The Exchange. This database contains licensed, royaltyfree images—marketing materials, spec art—a whole list of elements that creative artists in the company can use to generate advertisements for clients or marketing material for the company.
Creating the Lexicon
With the document work-flow systems in place, Clear Channel turned its attention to the construction of its smart-image databases. Since text is used to help make images smart, it is essential that the vocabulary used be standardized company-wide. Therefore, one of the critical components of Clear Channel’s strategy was the development of a corporate lexicon, a dictionary of words used to describe its many products and client categories. Because he understood how important the creation of this lexicon would be to the overall success of the Going Visual strategy, Mason hired an information science
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consultant, Linda Rudell-Betts, to coordinate the process. “To begin,” says Mason, “we had to come up with the 16 main categories that describe our business, and then go much deeper into concepts like display categories in order to organize the images so they could be easily searched.”
The Importance of a Lexicon
Linda Rudell-Betts, the expert who worked with Clear Channel to develop its lexicon, applies classic methods in approaching smart imaging. "With a digital image entry," she says, "what you have is the image information, the zeros and ones that make up a picture. Depending on what your recording device was, you may also have the date of the image capture, the JPEG number or file number that's automatically assigned, and perhaps some other capture data relating to exposures and settings. You have very little information telling you what the image is about; you don't know what you're looking at. The founding principles of the things we do in information science, the superset discipline over computer science and library science, go back three or four thousand years ago, to the library of Alexandria. I might use the word hierarchy or taxonomy, which is starting with a broad concept and going down to a narrower concept. You might have seen that on many web sites where they have a drop-down menu and you climb your way down a tree starting with a broad concept and going down to a narrow concept. That's a taxonomy, and it's the same thing as a biological taxonomy: vertebrates, mammals,
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primates, and on down the line. So, we start with a broad concept, getting ever narrower, and subdividing into very specific concepts."
Rudell-Betts continued, "Using really large collections, especially digital collections, where you don't have a physical set of items, if you had a set of folders, 20 or 30 physical folders sitting on your desk, you'd place your folders in certain piles. You have this spatial connection between this pile over here, which has all the interviews you've been working on, and this pile over here, which is the interviews you need to do. This pile over here is the bills you don't want to look at. So you've got a classification that is a physical classification—it's spatial. The same kind of classification works in a library, where you have books on a shelf. You know if you go to the area in the back of the library, where it says '900' on the side, that's where the biographies are (and usually there's a sign that says 'Biography' just to help people out), and so you just go there. That is an instance of classification in a physical environment. You take that into a digital environment, there is no 'place' to go to. All the data are on a server somewhere. They might have an arbitrary session number. The first item you put in may be called '001,' the second '002,' and so on. Now how does a user find that? With digital objects, be they images or text, when we feed them into a database we'll put them into specific fields."