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Visualizing and Annotating the Digital Scriptorium

Mace A. Jones

Ph.D. Candidate at UMD College of Information Studies�2023 LEADING Fellow

8 March, 2024

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Thanks to those who made this work possible!

  • The LEADING program staff and specialist mentors through the data science bootcamp and beyond�
  • The Schoenberg Institute at UPenn�
  • Digital Scriptorium mentors:�
    • Lynn Ransom�
    • L. P. Coladangelo�
    • Doug Emery�
  • Co-Fellow: Jade Snelling

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Core Project Goals

Reflect changes in DS SPARQL properties and organization through a series of analytical and research SPARQL Queries

1st

Create interactive visualizations of SPARQL queries that represent the DS collection in part or as a whole.

2nd

Conduct an analysis of DS data and explore potentials for additional SPARQL queries for addition in the DS GitHub

3rd

Test the viability of an extraction and annotation of IIIF images represented in the DS collection in the Digital Mappa platform.

4th

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Three Major Outputs

Visualizing Aspects of the DS Collection

2

Sample Digital Mappa Library for Annotated IIIF Editions from DS catalog

3

Creating and Updating SPARQL Queries

1

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Create and Revize SPARQL Queries

Taking SPARQL queries from DS Catalog Prototype and updating properties in order to reflect DS Catalog Beta Version changes and make queries usable.

Creating new SPARQL queries with different research or analytical functions to better understand the collection organization and makeup

Building more complex SPARQL queries to extract IIIF Manifest data and other object data for modeling and annotating in different applications

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SPARQL as the Basis for Tableau Visualizations

  • Using SPARQL queries to target specific features in the collection.�
  • Extracting this data for visualization in Tableau.�
  • Create analytical visualizations to represent the collection at various levels.�
  • Export visualization for interactive use elsewhere.

Fig. 1 An image of a dataset from the Digital Scriptorium Wikidata Query Service

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Tableau Visualizations

Name and Role Association in DS Catalog

Fig. 2 Bubble visualization of Name and Role Data from the Digital Scriptorium Catalog

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Name and Role Association in DS Catalog cont.

Fig. 3 Focus on Catholic Church author datapoint with distinct count of records.

Fig. 4, highlight of author role in red within larger visualization.

Fig. 5 Bar graph representation of name and role data in the catalog.

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Languages present in DS Catalog

Fig. 6 Bubble graph of language frequency within DS catalog

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Digital Mappa and Reusing IIIF Manifests in DS

Create new detailed organization that demonstrates the utility of IIIF inclusion in DS records

Reorganize

Give a sample of annotated IIIF images based on the cross-institutional catalog

Represent

Demonstrate future potential of updated DS for DH and other humanistic research projects

Reuse

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Draft DM Annotation Glossary

Fig. 7 Digital Mappa annotation glossary for annotating various material qualities of IIIF objects.

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Digital Mappa and Annotating DS From SPARQL

Fig 8. Image of metadata, example annotation, and annotation text from the Digital Mappa platform

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Readings and References

Bartalesi, Valentina, Nicolo’ Pratelli, Emanuele Lenzi, and Paolo Pontari. “Using Semantic Web to Create and Explore an Index of Toponyms Cited in Medieval Geographical Works.” Journal on Computing and Cultural Heritage 16, no. 2 (June 30, 2023): 1–18. https://doi.org/10.1145/3582263.

Bianchini, Carlo, Stefano Bargioni, and Camillo Carlo Pellizzari di San Girolamo. “Beyond VIAF: Wikidata as a Complementary Tool for Authority Control in Libraries.” Information Technology and Libraries 40, no. 2 (June 17, 2021). https://doi.org/10.6017/ital.v40i2.12959.

Bikakis, Nikos, and Timos Sellis. “Exploration and Visualization in the Web of Big Linked Data: A Survey of the State of the Art.” arXiv, January 29, 2016. http://arxiv.org/abs/1601.08059.

Birnbaum, David J., Sheila Bonde, and Mike Kestemont. “The Digital Middle Ages: An Introduction.” Speculum 92, no. S1 (October 2, 2017): S1–38. https://doi.org/10.1086/694236.

Blake, Erin, Itza A. Carbajal, Regine Heberlein, Sarah Horowitz, Jason Kovari, VANESSA LACEY, Cory Lampert, et al. “Archives and Special Collections Linked Data: Navigating between Notes and Nodes,” 2020. https://doi.org/10.25333/4GTZ-ZD88.

Burrows, Toby. “Linked Open Data and Medieval Studies: Some Lessons from the Mapping Manuscript Migrations Project.” International Journal of Humanities and Arts Computing 16, no. 1 (March 2022): 64–77. https://doi.org/10.3366/ijhac.2022.0277.

Davis, Edie, and Bahareh Heravi. “Linked Data and Cultural Heritage: A Systematic Review of Participation, Collaboration, and Motivation.” Journal on Computing and Cultural Heritage 14, no. 2 (June 2021): 1–18. https://doi.org/10.1145/3429458.

Desimoni, Federico, and Laura Po. “Empirical Evaluation of Linked Data Visualization Tools.” Future Generation Computer Systems 112 (November 2020): 258–82. https://doi.org/10.1016/j.future.2020.05.038.

Heath, Tom, and Christian Bizer. Linked Data: Evolving the Web into a Global Data Space. Synthesis Lectures on Data, Semantics, and Knowledge. Cham: Springer International Publishing, 2011. https://doi.org/10.1007/978-3-031-79432-2.

Hyvönen, Eero. “Using the Semantic Web in Digital Humanities: Shift from Data Publishing to Data-Analysis and Serendipitous Knowledge Discovery.” Edited by Pascal Hitzler and Krzysztof Janowicz. Semantic Web 11, no. 1 (January 31, 2020): 187–93. https://doi.org/10.3233/SW-190386.

Maillot, Pierre, Olivier Corby, Catherine Faron, Fabien Gandon, and Franck Michel. “KartoGraphI: Drawing a Map of Linked Data.” In The Semantic Web: ESWC 2022 Satellite Events, edited by Paul Groth, Anisa Rula, Jodi Schneider, Ilaria Tiddi, Elena Simperl, Panos Alexopoulos, Rinke Hoekstra, Mehwish Alam, Anastasia Dimou, and Minna Tamper, 13384:112–17. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-11609-4_21.

McKenna, Lucy, Christophe Debruyne, and Declan O’Sullivan. “Using Linked Data to Create Provenance-Rich Metadata Interlinks: The Design and Evaluation of the NAISC-L Interlinking Framework for Libraries, Archives and Museums.” AI & SOCIETY 37, no. 3 (September 2022): 921–47. https://doi.org/10.1007/s00146-021-01373-z.

Ni, Lixian, Zhuoming Xu, Ting Wu, and Wenjie He. “Visualizing Linked Data with JavaScript.” In 2013 10th Web Information System and Application Conference, 211–16. Yangzhou, China: IEEE, 2013. https://doi.org/10.1109/WISA.2013.48.

Rodriguez Diaz, Alejandro, Alejandro Benito-Santos, Amelie Dorn, Yalemisew Abgaz, Eveline Wandl-Vogt, and Roberto Theron. “Intuitive Ontology-Based SPARQL Queries for RDF Data Exploration.” IEEE Access 7 (2019): 156272–86. https://doi.org/10.1109/ACCESS.2019.2948115.

Ruttenberg, Judy. “ARL White Paper on Wikidata: Opportunities and Recommendations,” n.d.

Veen, Theo van. “Wikidata: From ‘an’ Identifier to ‘the’ Identifier.” Information Technology and Libraries 38, no. 2 (June 17, 2019): 72–81. https://doi.org/10.6017/ital.v38i2.10886.

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Contact Information

Questions?

Mace Jones

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Email: majones@umd.edu