The Metadata Working Group (MWG) kicked off a Field of the Month initiative in October 2021. This project is intended to help ensure that we move forward with implementing last year’s recommendations for revisions to a variety of fields, many of which are still in the planning stage because they are dependent on metadata clean-up and/or we have not made a decision on our tolerance of metadata inconsistencies.
Each month for the next year, we will highlight one ScholarWorks field, rolling out revised help text on the work forms and guidance to campuses for required vs. optional metadata clean-up. This information will be shared at each Open Forum meeting (the first Friday of each month) as well as through subsequent email communications. Changes will also be tracked in the Metadata Change Log.
For additional background information, please consult the MWG slide deck from the October 1, 2022 Open Forum.
Batch Metadata Editing Instructions
If you are not yet familiar with the batch metadata editing process for ScholarWorks, please consult the training documentation created by David Walker.
Field #1: Title (November 2021-December 2021)
Overview
In 2020-2021, the MWG identified the need for additional clarity regarding capitalization practices for the Title field, which formerly advised users to capitalize the first word and any proper nouns, as shown in the screenshot below.
In keeping with the 2020-2021 recommendation of the MWG, David Walker has updated the Title field help text to allow for sentence case or title case capitalization. The help text now also links to a title case converter, as shown in the screenshot below.
Clean-up Recommendations (Optional)
The MWG has not identified clean up of existing Title metadata that is not in compliance with the above change (e.g., all caps) as a requirement. However, campuses are welcome to undertake this clean up, and two potential methods are detailed below. We encourage campuses to choose whichever method will best meet your needs, and you are welcome to adjust the process as you see fit. Based on initial testing, both methods handle diacritics well.
Option #1: Using the Title Case Converter
The Title Case Converter allows you to convert text based on the capitalization guidelines of various formatting styles. To facilitate batch editing, your campus may want to decide to use one style in all cases, regardless of disciplinary variations. Please consult the Which Title Case Style Should You Use? page for additional information.
Download the .zip file for your campus. Contact David if you don’t have that URL.
There is a separate CSV file within the .zip file for each data model/work form, of which we currently have four: dataset, educational resource, publication, and thesis. If your campus will be cleaning up Title metadata for more than just ETDs, you will need to complete the following clean up steps for each CSV separately.
For each CSV file, download it and save it locally. Then delete all fields (columns) except for id (column A) and title (column I).
Copy all metadata in the title column and paste it into Notepad or a similar program of your choice to strip out unwanted formatting.
Then paste that text into the text box on the homepage of the Title Case Converter. Note: The converter does not have an explicit character limit, but it seems to work best with approximately 500 or fewer words, so you may need to do this in batches.
Select the title case style your campus has decided to use. If your titles are in all caps, you will also want to uncheck the “Keep Words in All Caps” option. Then click the “Convert” button.
Once the conversion is complete, you will be taken to a list of converted titles. Click the “Copy All” button.
Back in the CSV file, add a new column (you can name it “title_revised” for now) and paste the converted titles into that column as plain text.
You will probably want to do some spot checking, as issues can arise with acronyms, book/film titles, etc. Depending on the original formatting of your Title metadata, it may be helpful to refer to that column as you spot check.
Once the spot checking is completed, delete the original title column, and rename the “title_revised” column “title”.
That’s it! Be sure to save the CSV again, and you can send the file back to David. He will take it from there and give you the opportunity for a “sanity check” before finalizing the changes.
Option #2: Use the PROPER function in Excel
The PROPER function in Excel is a potentially faster method for converting all caps to title case, but it will capitalize the first letter of all words, including some that you would likely prefer to be lowercase (e.g., 2-3 letter words including articles and prepositions), so more manual clean-up may be needed.
Download the .zip file for your campus. Contact David if you don’t have that URL.
There is a separate CSV file within the .zip file for each data model/work form, of which we currently have four: dataset, educational resource, publication, and thesis. If your campus will be cleaning up Title metadata for more than just ETDs, you will need to complete the following clean up steps for each CSV separately.
For each CSV file, download it and save it locally. Then delete all fields (columns) except for id (column A) and title (column I).
Add a new column C (you can name it “title_revised” for now), and in cell C2, type =PROPER(B2) and press enter/return on your keyboard. This will convert the all caps text in B2 to title case.
Then fill the formula down the entire column. Please consult Excel’s documentation for additional guidance with that.
As noted above, this formula will capitalize the first letter of all words and lower case the rest, so spot checking will likely be required to identify those words that should be all caps (e.g., acronyms) and identify words that should not be capitalized (e.g., a, an, of, at).
You may want to consider using find and replace to automate this process a bit. For example, you could replace all instances of “Of “ with “of “ as shown in the screenshot to the right. Just be sure to include the subsequent space after the word in order to avoid replacing longer words that simply begin with the same letters, and also be sure to check the “Match case” option.
Once the spot checking is completed, delete the original title column, and rename the “title_revised” column “title”.
That’s it! Be sure to save the CSV again, and you can send the file back to David. He will take it from there and give you the opportunity for a “sanity check” before finalizing the changes.