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Research Scenario: Unlocking Born-Digital Literary Heritage II

Second blogpost on the case of the Herman de Coninck floppy disks


The aim of the CLARIAH-VL Open Humanities Service Infrastructure is to advance digitally-enabled research in Humanities and the Arts by, among other things, providing data-level access to digitized and born-digital resources. In this blogpost series, we will communicate on research scenarios leading to, and building upon, the datasets made available through CLARIAH-VL. This is the second blogpost on the research scenario ‘Unlocking born-digital literary heritage: the case of the Herman de Coninck floppy disks’, in which we reflect on the usefulness of computational methods for discovering the contents of the born-digital files of Herman de Coninck.

Aim of the research scenario

As mentioned in the previous blogpost, the Letterenhuis acquired 218 floppy disks (5¼- and 3½-inch) of the prominent Belgian poet, essayist, journalist, and publisher Herman de Coninck (1994-1997) in 1998, and more than 25 years later, the content of the digital files has never been analysed or compared with the paper archive on item level. The aim of the research scenario is, therefore, to partially analyse and discover the content of the digital files stored on the floppy disks by describing their contents, creating sub-datasets that group related files and linking the files with related files in the paper archive. While the full dataset of all the files held on the floppy disks could be used to answer various research questions relevant to biographical research, textual scholarship and genetic criticism, the first research question driving this research scenario relates to the initial access to the files: What is the content of each of the files on the disks, and what digital tools and methods can be used to reveal it?

Floppy disk Herman de Coninck
Floppy disk Herman de Coninck at the Letterenhuis

Steps taken

In 2018, the Letterenhuis took the first step in making disk images of the floppy disks. These disk images are not just copies of all the files, but are a literal representation of every bit of information on the floppy disks, to ensure that the original data is preserved. In total, the floppy disks contain over 1300 files (including .wpd and .doc format), which were converted by the Letterenhuis to .txt and .pdf for further processing. In some cases, the conversion rendered some characters incorrect (e.g. ‘ë’ instead of ‘é’) or illegible, but most files are perfectly suitable for further analysis. Several steps were then taken to gain more insight into the content of these plaintext files: 1) preprocessing, 2) filtering of correspondences, 3) content review, and 4) identifying corresponding files.

1) Preprocessing

Firstly, we ran a script to check whether the contents contained duplicate files. Ultimately, we found about 25 duplicates. We then conducted an initial analysis to discern any patterns in the file content. Initial observations indicated the presence of recurring elements, such as files beginning with “De vliegende keeper” followed by the column title. We therefore attempted to extract the column name (e.g., ‘De vliegende keeper’), the column title, and the author, which is crucial given the files also include contributions from authors of the Nieuw Wereldtijdschrift (NWT) under the editorship of De Coninck. In order to maximize data extraction efficiency, various exceptions were incorporated into the script. Manual correction was a more time-efficient approach for files with significantly different structures than script modification. Adjustments for line breaks, capitalization, and similar variations were integrated into the optimization process. During optimization, a subset of files was manually annotated and used to compare and refine the script’s accuracy.

2) Filtering of correspondences 

A large proportion of the files contained personal correspondences, and we wanted to separate these personal files from the work-related files. They may contain personal information and have to go through a more extensive sensitivity review in a later stage. We employed pattern recognition to filter out correspondence. De Coninck’s correspondences typically begin with a salutation, such as ‘geachte’ or ‘beste’. The script therefore identifies files with the most common salutations in Dutch, English and German at the beginning of a line and categorises them as correspondence. The remainder of the files were subjected to a quick manual inspection to filter out personal files without salutations. As such, we excluded 838 files from further analysis. This, of course, a very bare bone approach and not a very strong parameter for a more comprehensive sensitivity review and needs refinements for further applications.

3) Content review

We then turned our attention to Named Entity Recognition (NER) to get a general overview of the content of the files. The NER script used the nl_core_news_lg model by spaCy to extract person and place names from the text files. The results were compiled into separate text files and a CSV file with term frequencies and categories (person or place), alongside their occurrences in the dataset. It was necessary to manually clean the results to remove non-entity nouns, as uppercase initials at the beginning of sentences caused some false positives to be detected. The list still contains some errors and false positives, but the 3490 entries should provide a solid starting point for further research, such as: in which essays and in what way De Coninck discussed certain people or places – and whether this was subjected to any revision during the writing process.

4) Identifying corresponding files

The objective of this step was to identify files that corresponded to each other across De Coninck’s archive and publications, which included:

  1. The floppy disk files;
  2. Printouts of the files in the De Coninck’s paper archive at the Letterenhuis;
  3. Newspaper snippets files in the De Coninck’s paper archive at the Letterenhuis;
  4. Published columns in the collection of essays De flaptekstlezer (1992), Intimiteit onder de melkweg (1994) and De vliegende keeper (1995).

To facilitate the comparison of these sources, we firstly digitized the materials. We made use of an existing EPUB version of the collection of essays. For the printouts and newspaper snippets, we employed Optical Character Recognition (OCR) using Python-tesseract. Once all sources had been digitized, we proceeded to compare their contents using similarity ratios and list the top 5 similarities. For instance, comparing published columns with floppy disk files revealed a 0.90 similarity ratio between the column “Poëzie en toeval” and the file “DICKEY_74_968.txt”, which might suggest a strong correspondence.

Next Steps

By means of computational methods such as NER and similarity checks, we could gain some general insights into the content of the files on De Coninck’s floppies. The next and final blogpost within this series will provide further details on the dataset with the file titles related to De Coninck’s columns published under the title “De vliegende keeper” in De Morgen.

Link to the dataset

The CSV file containing the persons and places mentioned in the files stored on the floppy disks (with the exception of De Coninck’s personal communication) is made publicly available on Zenodo through CLARIAH-VL, the files from the floppies can – after approval – be consulted at the Letterenhuis.

References

Bekius, L., & Thijs, J. (2024). What does that little black square store? The contents of Herman de Coninck’s floppy disks in the Letterenhuis. DH Benelux 2024, Leuven, Belgium. Zenodo. https://doi.org/10.5281/zenodo.11401905

Written by Lamyk Bekius & Jordan Thijs


OpenEdition suggests that you cite this post as follows:
Lamyk Bekius (December 17, 2024). Research Scenario: Unlocking Born-Digital Literary Heritage II. CLARIAH-VL. Retrieved February 17, 2025 from https://doi.org/10.58079/12yo7


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