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Leveraging Large Language Models for Post-OCR Correction of Nineteenth-Century British Newspapers

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Montage of images from this blog post, mixed with images from British Library Newspapers archive

│By Alan Thomas, AI Research Engineer at the Centre for Machine Intelligence, University of Sheffield│

Poor optical character recognition (OCR) quality is a major obstacle for humanities scholars seeking to make use of digitised primary sources such as historical newspapers. To improve the quality of noisily OCR’d historical documents, we introduce BLN600 – an open-access dataset derived from Gale’s British Library Newspapers – and showcase the potential of large language models (LLMs) for post-OCR correction using Llama.

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Exploring Named Entity Recognition in Gale Digital Scholar Lab

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│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

One of six embedded tools in Gale Digital Scholar Lab, Named Entity Recognition (NER) processes Optical Character Recognition (OCR) text data and captures information about a range of words defined as ‘entities’, detailed below. The tool is ideally suited for text-based analysis, including text encoding and mapping. This blog post will discuss some of the highlights of the Lab’s NER tool, and things to bear in mind when creating an analysis configuration. We’ll finish with a couple of sample use cases to inspire your own NER analysis.

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Re-imagining Assignments in the DH Classroom II: Timelines, Digital Exhibits, and Maps

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│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

This is a follow-up blog post to last month’s overview of working with Storymaps in the DH classroom.  We will consider a few more ways to engage students in the creative and intellectually rigorous process of building Digital Humanities projects, conducting analyses, and demonstrating the outcomes of a quarter or semester’s-worth of work. Developing timelines, exhibits and maps involves making use of Gale Digital Scholar Lab’s export functionality, which includes the ability to download:

  • The OCR text output of up to 5,000 documents in any given content set.
  • The full metadata of a content set, up to 10,000 documents.
  • Individual document images.
  • Analysis visualisations in multiple image formats.
  • Analysis raw data in CSV or JSON formats.
  • Documentation and records completed using the Notebook feature, in multiple text formats.

This exported information can then be used as the underlying data for a variety of interactive and public-facing student assignments. 

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Digital Humanities and Data Mining: The Key to Efficient Seminar Preparation

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Header image - piles of leather bound books with spines facing outwards

│By Becca Leeland, Gale Ambassador at the University of Exeter│

Anyone that says to a humanities student ‘all you have to do is read a book and have an opinion’ is someone who’s never had to prepare for a seminar! Seminars are the foundation of my degree – they guide me to the crucial works in a given field, they give me the space to explore ideas, and sharpen my skills in argument and writing. But they can also be daunting, especially when you’re presented with the work of the finest minds in history and are expected to make sense of it; you know you’re intelligent, you know you can do this, but sometimes you just need a little push in the right direction…

*Enter Gale Digital Scholar Lab.*

Gale Digital Scholar Lab is designed to make data mining and primary research more efficient with a three-step process of build, clean, and analyse. Utilising some of these techniques, you can gain a solid idea of where the texts are going and what to look out for, something that is really helpful when you start reading the material more closely.

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Working with Datasets, A Primer

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Notes from a DH Correspondent

│By Dr. Sarah L. Ketchley, Senior Digital Humanities Specialist, Gale│

This month’s blog post will discuss datasets – what they are, and how they might be used by a researcher or student who plans to use digital tools to generate answers to questions they have about their data. The timing of this post coincides with the release of Gale Digital Scholar Lab’s newest feature: downloadable datasets, pre-curated for use in the classroom or by individual users. We’ll look at some of the options for working with these datasets, and end with some suggestions for sourcing open plain text data for curation and analysis.

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A Global Community: Learning and Networking Opportunities for Digital Humanists

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Notes from a DH Correspondent

│By Dr. Sarah L. Ketchley, Senior Digital Humanities Specialist, Gale │

If you speak with many Digital Humanists and discuss their route into the field, a large number will reference the training opportunities afforded by annual conferences, institutes, and workshops. These events provide a forum to develop new skills, with opportunities for hands-on practice. At the same time, attendees can learn about current project work, digital tools and methodologies and, importantly, these events provide an opportunity to mingle with peers. Digital Humanities conferences are somewhat unique in that they attract audiences from many academic disciplines, who all share the common interest of incorporating methods of digital scholarship into their research or pedagogical workflow. The Digital Humanities team at Gale is no exception, with many of us attending conferences, since our goal is to continue the ongoing development of Gale Digital Scholar Lab to ensure that it’s a relevant, functional and user-friendly platform. Many of the conferences have continued in an online format over the past couple of years, with a gradual shift back to in-person or hybrid gatherings.

As well as highlighting some of the main conferences and publications to be aware of as a Digital Humanist, this post will provide a range of resources for training, also sharing other useful networks like the Digital Humanities Slack channel. It’s not exhaustive but will provide a good starting point for those who wish to start their DH journey, brush up on existing skills, or learn about current research.

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Separating the Wheat from the Chaff: Identifying Themes and Topics in Archives Using Gale Digital Scholar Lab

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Notes from our DH Correspondent

│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

Getting to grips with the scope and content of a digital primary source archive held by an institution’s library can be daunting, particularly if the archive consists of thousands of documents in a variety of formats. For an individual researcher, the task of sifting through vast quantities of data in the quest for material that is relevant for a particular research topic is something that can take years to accomplish. This blog post will explore some of the ways a researcher can use Gale Digital Scholar Lab in conjunction with Gale Primary Sources as a platform for exploratory analysis to gain insights into the topics and themes represented in a chosen archive.

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Doing the Digital Laundry? Notes on Cleaning Unstructured Text Data

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Notes from our DH Correspondent

│By Sarah L Ketchley, Senior Digital Humanities Specialist│

An integral part of the workflow of any digital humanities project involving text generated automatically by Optical Character Recognition (OCR) is the correction of so-called OCR errors. The process is also called ‘data cleaning’. This post will explore some of the considerations researchers should be aware of before starting to clean their data in Gale Digital Scholar Lab, using the built-in text cleaning tool. It will also offer additional resources for working with data in other formats outside of the Lab.

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Creating an Export Workflow with Gale Digital Scholar Lab

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Notes from our DH Correspondent

│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

This digital project was prompted by the broad research question: how was archaeology reported in The Illustrated London News (ILN)? The ILN is a publication notable for its fine illustrations and contributions by some of the pre-eminent archaeologists of the day. Gale Primary Sources offers access to the entire run of the newspaper covering the period 1842-2003. This blog post describes a workflow for the preliminary investigation of the data: initial content set creation, cleaning, analysis, export and visualization. At the outset, the research questions were necessarily broad:

  • Which words were most prevalent in articles reporting on archaeological digs?
  • What themes or topics are most prevalent in the dataset?
  • What was the overall feeling about this type of reporting? Was it reported favourably?
  • Is it possible to identify which archaeologists were directly contributing to the publication and how many contributions they made?

Engaging in the practical process of curation and analysis offers opportunities to refine these questions, and almost inevitably suggests new avenues for future exploration.

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A Sense of Déjà vu? Iteration in Digital Humanities Project Building using Gale Digital Scholar Lab

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Notes from our DH correspondent design

│By Sarah L. Ketchley, Senior Digital Humanities Specialist, Gale│

This post explores the iterative process of digital humanities project work in Gale Digital Scholar Lab, which provides a user-friendly interface for text mining historical primary source documents from Gale Primary Sources and plaintext material uploaded by researchers. The post discusses how each stage of the curation and cleaning process (Build, Clean, Analyse) is impacted by the need for a flexible and regenerative mindset and workflow that is less linear in nature, more cyclical and iterative.

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