Four thousand entries seen whole, rather than one record at a time. Each view is built from the same index that drives the database search, so nothing here is a separate dataset that can drift out of step — and each says plainly what it shows and what it cannot. Every chart is clickable: a point, a bar or a party takes you into the database search for exactly that set of documents.
When
Timeline
Documents per year across the whole span of the Regesta, with the peaks and the silences both visible. Click any year to see that year’s entries.
Where
Map
The beneficiary institutions on a map of the Latin East, geocoded against Wikidata with every coordinate cited. Dot area is proportional to entries; click a place for its houses.
What connects to what
Network
Grantors and recipients as a force-directed graph: who issued documents, who received them, and the handful of parties that did both. Searchable, and filterable by how often a party appears.
To whom, and of what kind
Institutions and Types
The beneficiary institutions ranked by how many entries name them, beside the transaction types that classify the corpus. Click a bar to search that grouping.
A visualisation of this corpus is partly a picture of its gaps: Not every entry carries a grantor, a recipient or a named institution, and the coverage of the database itself thins towards its later years, where new entries are still being added. Empty stretches on these charts are the edge of what the evidence — and the edition — currently supports, not a statement about the Latin East. Each page repeats the specific caveat that applies to it.
About the map: The Regesta carries no coordinates of its own, so the institutions were geocoded against Wikidata in September 2026 and every coordinate on that page cites the record it came from. 46 of the 66 named houses could be placed; the rest are listed unplaced rather than given a plausible-looking dot.
Artificial Intelligence (AI): The Regesta database is now too large for the connections between its entries to be traced by hand without hundreds of hours of research time. So, we experimented using Anthropic’s Claude.ai, which identified, seemingly new, links between charters, dates, grantees, grantors and geography.
AI does not run on the site itself. The analysis was carried out once, offline, and only its results were uploaded. As the database grows we will repeat the exercise from time to time and refresh the site with the new findings and new research questions which are generated as part of the process. We do hope you find these insights useful, but if you notice an error, or a connection the analysis has missed, then please do email us.
We used Claude for the current analyses, but Google Gemini, OpenAI’s ChatGPT and other tools are available, and in future we will use whichever AI tool produces the best results at the time.
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