I hope someone has a clear, concise answer to what exactly is the
Entity and Attribute Overview. Yes, I have head the definition many
times, but when I go to look for an example our in cyberspace, there are
so many permutations. Let's say I have a feature class with 20 attributes. They are listed and explained in detail in the Detailed
Discription under the Entity Attribute tab. So far, it sounds like under the Overview Description in the Entity and Attribute Overview, you just spit out the detained stuff in a table or something. What I would like to do is provide a concise and relavant description of what all the attributes mean as a whole, to tell the data's story, if you will. One of our datasets is a shapefile that describes landslides and it has 80 attributes added by one of our geologist. They go from A to Z: the direction of the landslide, how likely is the landslide to blow,
how big is it, how is it ranked, what is it made up of. Can I just write a short narrative that explains how the attributes work together?
I know this isn't a place for another abstract. But, I am confused because of the different examples I've found. What I hope this area is for is when someone sees 80 unique attributes and goes "Holy Smokes", that they can real the overview and get a better feel for what the data and it's enormous attibute library means and not just look at the attributes in a table.
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Entity and Attribute Overview
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I hope someone has a clear, concise answer to what exactly is the
Entity and Attribute Overview. Yes, I have head the definition many
times, but when I go to look for an example our in cyberspace, there are
so many permutations. Let's say I have a feature class with 20 attributes. They are listed and explained in detail in the Detailed
Discription under the Entity Attribute tab. So far, it sounds like under the Overview Description in the Entity and Attribute Overview, you just spit out the detained stuff in a table or something. What I would like to do is provide a concise and relavant description of what all the attributes mean as a whole, to tell the data's story, if you will. One of our datasets is a shapefile that describes landslides and it has 80 attributes added by one of our geologist. They go from A to Z: the direction of the landslide, how likely is the landslide to blow,
how big is it, how is it ranked, what is it made up of. Can I just write a short narrative that explains how the attributes work together?
I know this isn't a place for another abstract. But, I am confused because of the different examples I've found. What I hope this area is for is when someone sees 80 unique attributes and goes "Holy Smokes", that they can real the overview and get a better feel for what the data and it's enormous attibute library means and not just look at the attributes in a table.
Any takers on this one?
Thanks!
Anne