Annotations with Multiple Repeating Layers
Ok, this has to have been done before but I just can't find any examples or references to it.
We use TeleAtlas-Multinet data, which breaks down the states network of streets into 8 or 9 different layers. So fitting with the enhanced MapService(MSD) we need to use annotation layers versus MapLex to get optimized processing. But we use the same layer over and over changing the symbols and labels based on the scale.
Now, we are seeing we can't use the same layer for annotations at different scales, and we don't want to be creating 14 copies of each layer and building annotations for them.
With the Shift to the Google/Bing compatable zoom-scales we see a need to have a better structure to label these roads which we adjust to show better for every couple scales.
Suggestions oh'ye GURU's of all things Arc!
Mapping Center Answer:
First, there are not too many people or organizations who have done this before, so the expectation of there being a developed best practice is a bit lofty. So, I'll describe this relative to how we created the annotation for the World Topographic Map Service.
We produced annotation for 10 of our map scales (resulting in ~4,000,000 annotation features), including 1:72,000 for the entire U.S. To do that we used a prototype of a tool we will be releasing in 9.4 (Generate Annotation). To create that annotation we created a different MXD for each scale. The resulting annotation was added to a "master map" that is used as the basis for map services.
There are a couple of big reasons we made separate MXDs (by scale) for producing annotation. First is that we needed to have a reference scale for each scale of annotation. Thus, the data frame in each MXD had it's reference scale set to match the corresponding scale in our tiling scheme. We also found that having a specific MXD for each scale made the task of managing labeling rules considerably easier. (Imagine 25-40 layers and 50-100 label classes per scale!)
We also appended all of the TeleAtlas road data we used into a single feature class & therefore layer to make that part of the job as uncomplicated as possible. We used a File Geodatabase (making sure to set our GP environments for current and scratch workspace to also be a file geodatabase). That made for a dataset (for the U.S.) with about 15 million features weighing in at about 3Gb. We then separated the highways into another dataset and dissolved them by highway number, shield type, and state (no multipart features)--mainly to make it possible to use them at smaller scales and to make the job for Maplex easier and considerably faster.
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