245 00 |a Host bibliographic record for boundwith item barcode i1857042
774 1_ |t Methods of estimating recharge to the Floridan aquifer in northeast Florida / by G.G. Phelps ; prepared in cooperation with city of Jacksonville, Florida |w 9984636650001453
774 1_ |t Water-Resources investigations / U.S. Geological Survey. |w 9982433750001453
Although we now have a file that contains the MMS IDs of all the records associated with the boundwiths, the file is not in the format needed to use in Alma to create a set. Therefore, MS Word and Excel are used to reformat the file (into a file with a single column of all the MMS IDs) and to get rid of any duplicate MMS IDs.
Finally, a set of all the records associated with boundwiths will be created in Alma based on the file of MMS IDs created above.
When the job has completed, go to the job history tab (in Monitor Jobs), and on the line for your export job, select Actions -> Report. The report will have a hyperlink with a file name something like “BIBLIOGRAPHIC_8987926080001453_1.mrc”. Click on the file name link and on the next screen select Actions -> Download and save the file of bib records on your computer.
Step 3 – Extract the bib records that contain 774 $w subfields from the file downloaded in step 2.
Open MarcEdit and select Tools (along the top row) -> Select MARC Records -> Extract Selected Records. Change ‘Display Field’ to ‘774$w’, click on the folder for the ‘Source MARC File’ and select the file downloaded in step 2, and click the ‘Import File’ button.
Next, click on the “Display Field (774$w)” column heading to sort by that column by the values in the 774 $w subfield. Check the ‘Retain Checked Items’ box, click the top line with a value in 774$w (not the ones that start with (CKB)), hold down shift key and click the last line with a value in 774$w. If clicking on the line doesn’t check the appropriate boxes, click on one of the boxes (while the lines are still highlighted), and all the lines should be checked. Check to make sure all lines with a value in 774$w (other than CKB) are now checked.
Next, you need to create a file of the records with a value of interest in the 774$w subfield. To do this, click the ‘Export Selected’ button and tell MarcEdit where to put the file.
Finally, you need the convert the MarcEdit ‘.mrk’ file to a ‘.mrc’ MARC file. Go to MARC Tools (the big icon – not the top row), choose MarcMaker, select the file you just created as the input file (it will have a ‘.mrk’ extension), select the output file and allow MarcEdit to fill in the output file name, and click on the ‘Execute’ button.
Next, you need the convert the MarcEdit ‘.mrk’ file to a ‘.mrc’ MARC file.
Step 4 – Extract the MMS IDs from the 001 fields and 774 $w subfields in the file of records created in step 3.
In MarcEdit, select Tools (on the top row) -> Export -> Export Tab Delimited Records. For the top file name box, click on the folder and select the ‘.mrc’ file you created in step 3. Then click on the folder next to the second file name box and provide a file name for the ‘.txt’ file that will be created as part of this process. Leave the default values for the ‘Select Field Delimiter’ and the ‘In field delimiter’ fields and click on the ‘Next’ button.
Step 5 – Reformat the file of MMS IDs created in step 4.
Open the file of MMS IDs created in step 4 in MS Word. Replace “ (quote) with nothing (remove all quotes) and click the ‘Replace All’ button. Replace ^t (tab) with ^p (carriage return) and click the ‘Replace All’ button. Replace ; (semicolon) with ^p (carriage return) and click the ‘Replace All’ button.
Finally, replace the top lines (001 and 774$w) with a single line that contains only “MMS ID” (without the quotes). Save the file and close MS Word.
File #2 –remove lines 2-5000 and then 5,001 and greater, and save the file.
File #3 –remove lines 2-9,999 and then 5,001 and greater, and save the file.
If you have more than one file of MMS IDs, repeat the above process for each file, giving each file a different file name.
If you had multiple files of MMS IDs, you then must combine all sets of 5,000 into a single set. To so do, go to Manage sets, and for your first file, select Actions -> Combine sets. Modify the resulting merged file name, if desired (I used “Boundwiths File 1-2”), change the ‘Operation’ to “Or”, click on the blue arrow at the right end of the ‘With’ box, select your second file of MMS IDs, click the ‘Select’ button, then the ‘Submit’ button. Repeat this process, adding an additional set, until all your sets have been combined into one larger set (I named my final set “Boundwiths”).
Step 8 – Add a bib record marker for your boundwiths.
This step is entirely optional. The set created in step 7 should be a set containing all your boundwith records – both the host bibliographic records and the linked/related records. However, the set is an itemized set, so any boundwith cluster of records created in the future will not be added to this set. To make future maintenance (possibly) easier, I added a marker to each bib record in my set of boundwith records. If you want to do so, here’s how.
Select a local 9XX field to use for a marker (we had previously defined 965 as our field to use for any load or maintenance markers).
In the Metadata Editor, create a normalization rule to add a boundwith marker. My normalization rule was:
rule "Add Local Field"
(not exists "965.a.boundwiths")
addSubField "965.9.LOCAL" if (not exists "965.9.LOCAL")
If you haven’t already, create a job to run the normalization rule. Alma -> Resource Configuration -> General -> Processes, click the ‘Add Process’ button, set Business Entity = Bibliographic title, and Type = Marc 21 Bib normalization, click the ‘Next’ button, add name and description, click the ‘Next’ button, check MarcDroolNormalization and click the ‘Add to Selection’ button, click the ‘Next’ button, set the Drools File Key = [your normalization rule], click the ‘Save’ button.
Run your normalization rule. Alma -> Run a Job, check the job that runs your normalization rule, click the ‘Next’ button, select your file of boundwiths, click Next, Next, Next, and finally Submit.
Checking for broken boundwith links.
A simple way to check for bound with links is to do the following:
For each file created in “Step 7” above, go to the “Members” of the set and click on the “Tools” button. This currently only works for files of 5,000 or fewer records, so if you have more than 5,000 boundwith records, you must use the separate files created in “Step 6” above (which were used to create the Alma sets in “Step 7”). It takes Alma quite a few minutes to create the spreadsheet, so don’t do this step when you’re in a hurry.
In the resulting Excel spreadsheet, a blank cell in column “P” indicates a problem with a link (not necessarily a broken link).
|Current phase: NA||Written by: Bob Thomas
|Approved by: NA
||Last updated: 12/30/2015|
|Staff Contact: Cassie Schmitt||Nature of last update: NA