What this is — and what it isn't

Credit where it's due

We build on decades of other people's work

The Provenance Project did not create this evidence, and it does not stand apart from the field — it depends on it entirely. Archivists, provenance researchers, restitution commissions, and museums assembled these records over decades of patient, expert work. Our role is narrow: to cross-reference their open records at a scale no individual can hold in their head at once, and to link you straight back to the original. Every trail we draw ends at someone else's authoritative document — never at ours.

If you maintain one of these resources: we cite and link to you, we don't re-host or replace you, and we would genuinely welcome your corrections at [email protected].

Method

A knowledge graph built from claims, not assertions

Most databases store facts and overwrite conflicts. Provenance can't work that way — the historical record is full of deliberate lies, gaps, and disagreements. So the graph stores claims: each one carries the document it came from, a confidence score, and a citation back to the scan. Competing claims coexist. Identities are never hard-merged; "this is the same object as that" is itself a scored, reversible edge. A false merge would manufacture a false lead — the discipline that prevents it is what separates a research tool from a generator of plausible fiction.

Graph analytics do the heavy lifting that no reader could: collective entity resolution that links the same painting across archives despite different titles, languages, and inventory numbers; custody-gap detection — every work documented as seized with no documented return; laundering-motif matching borrowed from anti-money-laundering analysis and pointed at the 1940s art market; and dealer-network centrality, which doubles as a map of which archive to digitise next. Read the full methodology →

Worked example · verified against the primary source

One painting, one gap, one match

The French state holds La rue Saint-Rustique à Montmartre, a Maurice Utrillo street scene, in trust as an MNR work — recovered to France after the war, its pre-war history never fully established. The official record jumps from Paris to a Cologne art society in January 1944 with no explanation of how the painting entered Germany.

Cross-referencing the Getty Provenance Index against that gap, the engine found the painting offered for sale at Commeter, Hamburg, on 20 November 1937 (lot 288, consignor withheld), and again a year later. To check the match, we pulled plate I of the digitised 1937 catalogue from Heidelberg University's IIIF service: it is captioned "M. Utrillo. Nr. 288" and matches the museum's own photograph of the painting element for element — the buildings, the figures, the signature placement.

That auction appearance is a concrete, previously unconnected step toward the painting's wartime path — sourced entirely to public records, and checkable by anyone. It is presented as a documented lead, not a conclusion: who consigned it, and how it reached Cologne, remain open.

The data

The graph is built from openly-licensed records — bulk datasets and public APIs, no scraping behind logins. Today it spans more than 3.5 million records across eleven sources, and now joins the three sides of the problem: the loss (Nazi seizure records), the market (wartime sales), and the present day (museum collections).

Plus the Getty Knoedler and Goupil dealer stock books and the U.S. NEPIP provenance index. Next, through partnership and public archives: U.S. National Archives recovery records (Munich Central Collecting Point property cards, ALIU reports), the German Lost Art Foundation registry, and the Dutch NK / Origins-Unknown restitution collection.

What we've found so far

Early results, stated carefully.

• The three sides now connect. With the loss records in the graph, a documented ERR seizure can be cross-referenced against present-day collections — surfacing candidate correspondences, each carrying the Nazis' own photograph of the object so a researcher can confirm or reject it by eye. These are leads to verify against the original records, never assertions that any institution holds looted property.
• The method finds the needles. Pointed at museum provenance texts, it independently surfaced documented looted-art cases with no prior knowledge — including the Gutmann family's Degas Landscape with Smokestacks, the subject of a landmark U.S. restitution case. Rediscovering known cases is exactly how a method earns trust before it is turned on the unexamined long tail.
• History, reproduced from open data. Measuring consignor anonymity in German auction catalogues, the engine traces the arc of the forced-sale market on its own: from roughly 40% anonymous in the late-Weimar years to about 76% at the 1942–44 looting peak.
• A standing question list. Of the French MNR works, 1,726 carry an officially undetermined spoliation status — a concrete, bounded set of open cases the engine is working through, match by cited match.

Principles & limitations