Revealing La Revolution: The Environmental Scan & MARCedit, Part 1
As the interim Curator of Literature and Rare Books I am
writing the Environmental Scan for the French Pamphlet Project. Two tools I
have found very useful to help with this are MARCedit and
Microsoft Excel (I sort of love spreadsheets). I became familiar with MARCedit
over the summer as I attempted to gain intellectual control over my expanded
collection responsibilities and learned a new (to me) feature of Microsoft
Excel which has proved very useful for putting together this report. So I
wanted to tell you a little about what I’ve learned.
After I was appointed interim Curator for Literature and
Rare Books in May, I requested a report from Technical Services of all
catalogued items in Rare Books and Special Collections. I already had a
comfortable grasp of the literary manuscript collections but had not had an
opportunity to really get to know the Rare Books and Special Collections
volumes. In an effort to become better acquainted with these collections, I
asked Technical Services to include several descriptive MARC fields (language
and subject entries) for each item in Rare Books and Special Collections.
Rare Books and Special Collections Stacks |
Rare Books and Special Collections Oversize Stacks |
I was hoping that the final report would provide me a broad
overview of the collection as well as the ability to examine the collection at
a more granular level without having to go and browse the stacks. While I do
love browsing the Rare Books stacks this just seemed a very inefficient way to
get to know the collections. Additionally, Rare Books are fragile (sorry to
state the obvious) and I don’t want to be pulling them of the shelves, flipping
through them, and the re-shelving them to gather information about them that
should be discernible from their catalog records.
Rare Book Shelf |
Technical Services ran a standard report version of my
request and offered me a MARC file with all Rare Book and Special Collections items
complete MARC records if I wanted to create my own report using MARCedit. I
accepted the challenge and a short guide to MARCedit.
MARCedit |
After downloading and installing MARCedit, the first step to
using MARCedit requires running the entire MARCfile through MARCbreaker to
create a UTF-8 MARC file. By converting the file to a UTF-8 file the succeeding
programs that this information is run through will recognize the special
characters and diacritics. MARCbreaker will clean up and search for errors in
MARC records while providing preliminary data about the entire file. This data let
me know how many times each MARC field was used which helped me in figuring out
what MARC fields I wanted MARCedit to provide in my report.
MARCbreaker |
I then ran my new MARC UTF-8 file through MARCedit and
checked the result of my report in Microsoft Excel. My report was a mess! Many
of the records were missing information in the MARCfields I had requested and
most of the records in foreign languages using special characters and
diacritics came through garbled. The problems were not MARCedit or Excel’s they
were mine. I realized that I was going to need to dig a little deeper into MARC
fields and get crafty about how I imported my data into Excel.
I had a basic understanding of the MARC fields from one of my introductory iSchool courses but found it necessary to rely heavily on the Library of Congress’s MARC21 Bibliographic Data website to make sure that I was getting the MARC fields I truly wanted.* I had to run the report several times before I was able to figure out all of the MARC fields I wanted and how to request them from MARCedit.
Entering the fields I wanted into MARCedit was the hardest
part. I could only select a single MARC field or field and subfield at a time
when I knew I wanted about 20 fields in my report. So it was time consuming to
select each one individually and see whether or not UMD Libraries was using
that field the way I expected them to or not. The fields I finally ended up
with in my report are:
008$35 – Language Code (letter 1)
008$36 – Language Code (letter 2)
008$37 –
Language Code (letter 3)
* Did you
know that for MARC’s three-letter-language-code each letter is entered individually
into three separate subfields? Also, I had to enter each subfield individually
so that each letter gets its own column in the spreadsheet!!! Why catalogers? Why?
035 – OCLC #
050 – LOC
Call Number
090 – Local
Call Number
100 – Main
Entry (Personal Name)
110 – Main Entry
(Corporate Name)
240 –
Uniform Title
245 – Title
Statement
246 – Title
Variation
260 –
Publication
300 –
Physical Description
362 – Dates
of Publication
500 –
General Note
510 –
Citation & References
600 – Subject
Entry – Personal Name
610 – Subject
Entry – Corporate Name
611 – Subject
Entry – Meeting Name
630 – Subject
Entry – Uniform Title
648 – Subject
Entry – Chronological Term
650 – Subject
Entry – Topical Term
651 – Subject
Entry – Geographic Name
653 – Index Term
– Uncontrolled
655 – Index Term
– Genre/Form
700 – Added Entry
– Personal Name
740 – Added Entry
– Uncontrolled Related Title
752 – Added Entry
– Hierarchal Place Name
800 – Series
Added Entry – Personal Name
830 – Series
Added Entry – Uniform Title
852 –
Location (Local)
856 – Electronic
Location & Access
Having
finally established all the MARC fields I needed. I returned to MARCedit to
begin the process of exporting my final file. Under the “Tools” Menu I choose
“Export Tab Delimited File” and set up a path to my new file, including the
file name and .txt file type.
Next I
entered each of the individual MARC fields I wanted for my report.
Exporting from MARCedit Step 1 |
Exporting from MARCedit Step 2 |
However I did not really want to keep my data as a .txt
file. I wanted to be able to analyze the data and manipulate it in a table
format. So I needed to import my .txt file into Microsoft Excel.
To be continued in
Part 2… Revealing La Revolution: The Environmental Scan & Microsoft
Excel, Part 2
*While I
was working on this the government (including all Library of Congress webpages)
was shut down. I had to use the Internet Archive’s Way Back Machine to
retrieve the information I needed.
Have a great day and keep smiling!
Have a great day and keep smiling!
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