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Personal geodatabases: How were annotation reference scales determined?

abaldenweck@blm.gov_BLM_EGIS

Note: I know that Personal Geodatabases are deprecated. Please do not inform me of that here, I am well aware.

That being said, I'm working on a project involving them here and could use some help. ArcMap is not an option for me.

How were annotation reference scales in personal geodatabases determined?

For example, I have a personal geodatabase containing an annotation feature class that I know for a fact has a reference scale of 1:24,000.

In this version of the MDB format, annotation properties were stored in an XML in a particular field of a certain system table.

The reference scale is documented like so:

<Key>ReferenceScale</Key>
<Value xsi:type='typens:XMLPersistedObject'> 
     <Bytes>xtrDhXhl0xGfugDAT2vGpQAAAAACAAAAAAAAcNdACQAAAA==
     </Bytes>
</Value>

That appears to be a base 64 value, but I can't get anything useful out of it

import codecs
y = b"xtrDhXhl0xGfugDAT2vGpQAAAAACAAAAAAAAcNdACQAAAA=="
y = codecs.decode(y, "base64")
print(y)
#b'\xc6\xda\xc3\x85xe\xd3\x11\x9f\xba\x00\xc0Ok\xc6\xa5\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00p\xd7@\t\x00\x00\x00'

print(y.decode("mbcs"))
#ÆÚÃ…xeÓ&#17;Ÿº

Similarly, on a different dataset using an earlier form of MDB (these were set up differently, so what we get instead is the entire annotation definition in a blob field) I could get the field as hex. If I decode it online (since I'm having trouble getting the right encoding with python) I can see that there's reference scale in there somewhere, but nothing around it maps to any number. I don't know what the scale of this one is supposed to be.

Spoiler

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#Reference scale begins below

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So, all in all, I'm pretty confused as to how I can figure this out in either version and would appreciate any pointers.

Thanks!

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abaldenweck@blm.gov_BLM_EGIS

That's kind of the problem. ArcMap was completely taken away (I asked at UC 2 years ago and was told the only way to get is on a business license. My organization removed access to us all in March 2024. And no hope of getting a specific version) and there isn't a tool to get this stuff anymore.

You have FME or Data Interoperability (extra licensing), and sometimes Q/GDAL (doesn't see feature datasets, for one), and those aren't always enough. For example, at this point ArcMap is the only program to my knowledge that opens MDBs made in Access 97. Access itself can't, unless you download Access 2006 (or 2007?) which iirc is the last version that could upgrade to a more modern format.

I am well aware of why Pro doesn't read personal geodatabases anymore (deprecated Jet driver, etc.), but it should not be impossible to retrieve old data from older formats. Personal Geodatabases, coverages, interchange files are all floating around various organizations folders and largely inaccessible. Tools like GDAL do a pretty good job of retrieving them, but things like Access 97 and compressed or partially compressed interchange files fall through the cracks.

I really don't care about the symbology itself, I just want to get the text in roughly the right size and shape, and it's proving much more difficult to do that than I feel it should be. I got the right placement, but the reference scale is really killing me here. If I can tell by looking at the original footprint that a given Annotation should not be scaled to 1:100,000 but I have no idea how to guess what the correct scale should be with the information that is available to me.

I do appreciate your responses.

rkrisher

Yeah, what you really need is access to an ArcMap environment where you can just copy this data out to a file or mobile geodatabase where you can start working with it using ArcGIS Pro. If you want to preserve the exact look and feel of the annotation, you're going to need access to the binary data stored in the element, since users can make fine adjustments to the annotation in the element that aren't reflected in the properties of the feature or even the symbol definition itself.

abaldenweck@blm.gov_BLM_EGIS

I'm not even bothering with that. I'm matching font size/style since those are found in the attribute table and any leaders but the symbol is just plain black text.

In part because the way the annotation symbol was stored in the Element field radically changed between then and now.

FFFFF9FF0200006825C6BA6E314180EBF6F4639A2041803CA18C3E6F314180EBF6F4639A2041060000004D004300000001000000000000000000000000000000000200000000000A000000540065007800740000000000FFFF060000002001000080C94EB5C16D314100C77E396D9A20410200
ÿÿùÿh%Æºn1A€ëöôcš A€<¡Œ>o1A€ëöôcš AMC
Textÿÿ €ÉNµÁm1AÇ~9mš A

There's information in there to show the string "MC" and the type of symbol "Text" and then everything else (haloes, color) is completely opaque to me here. A modern annotation stores JSON (iirc) in there.

This particular annotation is supposed to be blue text on a white rectangle but I have no idea how you're supposed to get that from looking at the stuff above. I'm focusing on reference scale because that is far more important.

I initially tried reverse-engineering the scale, but it turns out that things like haloes and backgrounds affect the shape of the annotation, so there's not really a reliable way to determine that if you don't know what the symbol is supposed to be.

rkrisher

You can likely figure out how to get the reference scale, but there may be other properties you'll want to get access to like the symbol classes, etc.

abaldenweck@blm.gov_BLM_EGIS

You can't, I'm using GDAL. It works for the vast majority of my workflow, but annotations are nasty in and of themselves and also have radically changed between ArcMap and Pro (but not as bad as coverage to geodatabase annotations. Yikes)

@HaydenWelch suggested that those things may map to a C struct, in which case I'm wondering if there's something there.

The refusal to provide a blind conversion process without paying for an additional license (Data Interop, FME) is a huge problem. Super frustrating to lose access to archival data because you can't get ArcMap anywhere anymore.

rkrisher

What happens if you do an Arcpy.Describe on the class? I'm not even sure if you can access the contents of the Personal Geodatabase using Arcpy in the ArcGIS Pro runtime.

abaldenweck@blm.gov_BLM_EGIS

Pro 3.5

rkrisher

What form and version of ArcGIS is installed in the environment where you're running your Python? This will determine which APIs are available to you.

abaldenweck@blm.gov_BLM_EGIS

Good information. Unfortunately, no ArcMap for me, which is why I'm as deep into this as I am. Do you have any information on accessing ArcObjects through python these days?

rkrisher

The easiest way to access that programmatically is to use one of the APIs provided to read the annotation properties. Because you're using a MGDB I assume you're using ArcGIS Desktop? Which means you would use .NET, Java, or C++ and ArcObjects to access this information.

It is possible to access ArcObjects using Python code, but it requires jumping through some extra hoops in order to load and work with the COM Objects used by ArcObjects.

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