A Knowledge Graph of Medieval and Renaissance Geographical Works

Submitted by Valentina Bartalesi on 02/26/2026 - 01:58

Tracking #: 4030-5244

Authors: 
Valentina Bartalesi
Nicolò Pratelli
Emanuele Lenzi

Responsible editor: 
Guest Editors 2025 OD+CH

Submission type: 
Full Paper
Abstract: 
Geographical works from the Middle Ages and Renaissance offer crucial insights into the cultural and intellectual landscapes of their time. However, digital scholarship in this domain remains fragmented, with key historical sources scattered across various physical and digital repositories. The Index Medii Aevi Geographiae Operum (IMAGO), an Italian national research project conducted from 2020 to 2024, addresses this gap by building a semantically enriched, interoperable knowledge graph focused on Latin geographical literature from the 6th to the 15th centuries. By combining expertise in medieval studies, philology, and digital humanities, IMAGO employs Semantic Web technologies and a dedicated ontology extending CIDOC CRM and LRMoo. The project facilitates data integration and reuse by applying Linked Open Data (LOD) principles, thereby enhancing the discoverability and interoperability of cultural heritage data. Beyond the release of the IMAGO knowledge graph, this work contributes a methodological pipeline for semantic modelling, annotation, integration, and publication of data related to medieval and Renaissance geographical works using established Knowledge Representation and Semantic Web standards. The approach is evaluated through a set of scholarly queries. These queries showcase the IMAGO infrastructure’s potential for data retrieval and deeper scholarly analysis. Finally, a user-friendly web application further enables access to the knowledge graph via interactive maps, dynamic tables, and exportable formats.
Full PDF Version: 
PDF icon swj4030.pdf
Previous Version: 
A Knowledge Graph of Medieval and Renaissance Geographical Works
Tags: 
Reviewed
Long-term Stable Link to Resources: 
https://github.com/AIMH-DHgroup/IMAGO/tree/main

Decision/Status: 
Minor Revision

Solicited Reviews:
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Review #1
Anonymous submitted on 04/Mar/2026
Suggestion:
Accept
Review Comment:

In my opinion, the authors have done an excellent job of adapting the paper to the requested revisions. They have perfectly integrated the suggestions, and I believe the article is now ready to be accepted for publication in the journal.

Review #2
By Miguel Ceriani submitted on 27/Mar/2026
Suggestion:
Reject
Review Comment:

I had carefully read the authors’ response to the previous round of reviews and the changes they made to the manuscript.
I appreciate that they covered most of my previous comments and I think they significantly improved the quality of the description of the resource (the KG) and the design process.
Nevertheless, in my opinion they did not consider adequately the first and most important issue I raised: that this work did not meet the standards of a research work, unless more experimentation and extensive rewriting was carried on in order to reframe the contribution, clearly stating the novelty of the general presented method (the pipeline?) and evaluating it as such.
This is why in my previous review I strongly suggested the change of the paper category to "Dataset Descriptions", for which I still think this would be a valuable contribution.
The changes they made regarding the general framing of the contribution seem to be mostly cosmetic and no additional experimentation has been carried on.
Crucially, the methodological pipeline and the web application, which the authors now present as contributions of the paper along the KG, are not adequately framed in respect the state of the art nor evaluated on their own.
This is why I suggest that the contribution is rejected.

Review #3
Anonymous submitted on 14/Apr/2026
Suggestion:
Accept
Review Comment:

I previously reviewed an earlier version of this paper. This revised version appears to have met all the recommendations from that earlier review.