Hi all,

The latest issue of Code4Lib Journal is now available: 
https://journal.code4lib.org/issues/issues/issue55

Editorial
https://journal.code4lib.org/articles/17062
Junior Tidal
Journal updates, recent policies, and a call for editors.

A Fast and Full-Text Search Engine for Educational Lecture Archives
https://journal.code4lib.org/articles/16996
Arun F. Adrakatti and K.R. Mulla
E-lecturing and online learning are more common and convenient than offline 
teaching and classroom learning in the academic community after the covid-19 
pandemic. Universities and research institutions are recording the lecture 
videos delivered by the faculty members and archiving them internally. Most of 
the lecture videos are hosted on popular video-sharing platforms creating 
private channels. The students access published lecture videos independent of 
time and location. Searching becomes difficult from large video repositories 
for students as search is restricted on metadata. We presented a design and 
developed an open-source application to build an education lecture archive with 
fast and full-text search within the video content.

Click Tracking with Google Tag Manager for the Primo Discovery Service
https://journal.code4lib.org/articles/16890
Hui Zhang
This article introduces practices at the library of Oregon State University 
aiming to track the usage of Unpaywall links with Google Tag Manager for the 
Primo discovery interface. Unpaywall is an open database of links to full-text 
scholarly articles from open access sources[1]. The university library adds 
Unpaywall links to Primo that will provide free and legal full-text access to 
journal articles to the patrons to promote more usage of open-access content. 
However, the usage of the Unpaywall links is unavailable because Primo does not 
track the customized Unpaywall links. This article will detail how to set up 
Google Tag Manager for tracking the usage of Unpaywall links and creating 
reports in Google Analytics. It provides step-by-step instructions, 
screenshots, and code snippets so the readers can customize the solution for 
their integrated library systems.

Creating a Custom Queueing System for a Makerspace Using Web Technologies
https://journal.code4lib.org/articles/16876
Jonathan Bradley
This article details the changes made to the queueing system used by Virginia 
Tech University Libraries' 3D Design Studio as the space was decommissioned and 
reabsorbed into the new Prototyping Studio makerspace. This new service, with 
its greatly expanded machine and tool offerings, required a revamp of the 
underlying data structure and was an opportunity to rethink the React and 
Electron app used previously in order to make the queue more maintainable and 
easier to deploy moving forward. The new Prototyping Queue application utilizes 
modular design and auto building forms and queues in order to improve the 
upgradeability of the app. We also moved away from using React and Electron and 
made a web app that loads from the local filesystem of the computer in the 
studio and runs on the Svelte framework with IBM's Carbon Design components to 
build out functionality with the frontend. The deployment process was also 
streamlined, now relying on git and Windows Batch scripts to automate updating 
the app as changes are committed to the repository.

Designing Digital Discovery and Access Systems for Archival Description
https://journal.code4lib.org/articles/16963
Gregory Wiedeman
Archival description is often misunderstood by librarians, administrators, and 
technologists in ways that have seriously hindered the development of access 
and discovery systems. It is not widely understood that there is currently no 
off-the-shelf system that provides discovery and access to digital materials 
using archival methods. This article is an overview of the core differences 
between archival and bibliographic description, and discusses how to design 
access systems for born-digital and digitized materials using the affordances 
of archival metadata. It offers a custom indexer as a working example that adds 
the full text of digital content to an Arclight instance and argues that the 
extensibility of archival description makes it a perfect match for automated 
description. Finally, it argues that building archives-first discovery systems 
allows us to use our descriptive labor more thoughtfully, better enable 
digitization on demand, and overall make a larger volume of cultural heritage 
materials available online.

Data Preparation for Fairseq and Machine-Learning using a Neural Network
https://journal.code4lib.org/articles/17038
John Schriner
This article aims to demystify data preparation and machine-learning software 
for sequence-to-sequence models in the field of computational linguistics. The 
tools, however, may be used in many different applications. In this article we 
detail what sequence-to-sequence learning looks like using code and results 
from different projects: predicting pronunciation in Esperanto, predicting the 
placement of stress in Russian, and how open data like WikiPron (mined 
pronunciation data from Wiktionary) makes projects like these possible. With 
scraped data, projects can be started in automatic speech recognition, 
text-to-speech tasks, and computer-assisted language-learning for 
under-resourced and under-researched languages.

We will explain why and how datasets are split into training, development, and 
test sets. The article will discuss how to add features (i.e. properties of the 
target word that may or may not help in prediction). By scaffolding the tasks 
and using code and results from these projects, it's our hope that the article 
will demystify some of the technical jargon and methods.

DRYing our library's LibGuides-based webpage by introducing Vue.js
https://journal.code4lib.org/articles/16941
Mark E. Eaton
At the Kingsborough Community College library, we recently decided to bring the 
library's website more in line with DRY principles (Don't Repeat Yourself). We 
felt we this could improve the site by creating more concise and maintainable 
code. DRYer code would be easier to read, understand and edit. We adopted the 
Vue.js framework in order to replace repetitive, hand-coded dropdown menus with 
programmatically generated markup. Using Vue allowed us to greatly simplify the 
HTML documents, while also improving maintainability.

Revamping Metadata Maker for 'Linked Data Editor': Thinking Out Loud
https://journal.code4lib.org/articles/16925
Greta Heng, Myung-Ja Han
With the development of linked data technologies and launch of the 
Bibliographic Framework Initiative (BIBFRAME), the library community has 
conducted several experiments to design and build linked data editors. While 
efforts have been made to create original linked data 'records' from scratch, 
less attention has been given to copy cataloging workflows in a linked data 
environment. Developed and released as an open-source application in 2015, 
Metadata Maker is a cataloging creation tool that allows users to create 
bibliographic metadata without previous knowledge in cataloging. Metadata Maker 
might have the potential to be adopted by paraprofessional catalogers in 
practice with new linked data sources added, including auto suggestion of 
Virtual International Authority File (VIAF) personal name and Library of 
Congress Subject Heading (LCSH) recommendations based on the users' text input. 
This article introduces those new features, shares the user testing results, 
and discusses the possible future steps.

Using Python Scripts to Compare Records from Vendors with Those from ILS
https://journal.code4lib.org/articles/17022
Dan Lou
An increasing challenge libraries face is how to maintain and synchronize the 
electronic resource records from vendors with those in the integrated library 
system (ILS). Ideally vendors send record updates frequently to the library. 
However, this is not a perfect solution, and over time a problem with record 
discrepancies can become severe with thousands of records out of sync. This is 
what happened when, at a certain point, our acquisitions librarian and our 
cataloging librarian noticed a big record discrepancy issue. In order to 
effectively identify the problematic records among tens of thousands of records 
from both sides, the author of this article developed some solutions to analyze 
the data using Python functions and scripts. This data analysis helps to 
quickly scale down the issue and reduce the cataloging effort.

Best,
Junior
Coordinating Editor, Code4Lib Journal Issue 55

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