Introducing TaxGraph

The taxation of multi-national companies is a complex field, since it is influenced by the legislation of several states. Laws in different states may have unforeseen interaction effects, which can be exploited by allowing multi-national companies to minimize and avoid taxes.

Thus, we created a knowledge graph of multi-national companies and their relationships. Many commonly known tax avoidance strategies can be formulated as subgraph queries to this graph, which allows for identifying companies using certain strategies. Moreover, we can identify anomalies in the graph which hint at potential tax avoidance strategies.

Query the Graph

using our SPARQL endpoint

Why don't you query for companies with headquarter in the United States and legal address in Cayman Islands?

SELECT ?a
WHERE {
    ?a tgp:headquartersAddressCountry tgc:US .
    ?a tgp:legalAddressCountry tgc:KY .
}

Alternatively, you can query for companies employing a structure called Duck-Rabbit Construct:

SELECT *
WHERE {
    ?b tgp:headquartersAddressCountry tgc:BM .
    ?b tgp:isUltimatelyConsolidatedBy ?a .
    ?c tgp:headquartersAddressCountry tgc:NL .
    ?c tgp:isDirectlyConsolidatedBy ?b .
    ?c tgp:legalForm tglf:54M6 .
}

You can also issue federated queries to pull in data from other knowledge graphs like Wikidata. This query uses the area of cities in Wikidata to compute the density of companies by headquarter and legal address in each city:

PREFIX wdt: <http://www.wikidata.org/prop/direct/>
SELECT ?c ?count ?a (?count/?a as ?density) WHERE {
    { SELECT COUNT(?x) AS ?count ?c WHERE {
        ?x tgp:headquartersAddressCityID ?c .
        }
        GROUP BY ?c
        HAVING(COUNT(?x)>1000)
    }
    ?c owl:sameAs ?wdc .
    SERVICE <https://query.wikidata.org/sparql> {
        ?wdc wdt:P2046 ?a
    }
} ORDER BY DESC(?density)

Browse the Graph

using dereferencable URIs

We provide a Linked Open Data endpoint so that you can inspect all elements of the graph in the browser. Here are some examples:

Countries

United States
Germany
Netherlands
Bermuda

Statistics

Size of the graph
Class Count
Company 1,491,143
Country 225
City 95,306
Legal Form 1,286
Relation Count
direct subsidiary 87,020
ultimate subsidiary 96,465

Resources

A dump of the graph can be downloaded here.

The complete source code for the extraction of TaxGraph is available on GitHub.

Credits

TaxGraph is the result of a student project conducted at the Chair for Data Science at the University of Mannheim. The project was conducted by the students Niklas Lüdemann, Ageda Shiba, and Nikolaos Thymianis. The project was supervised by Christopher Ludwig, Nicolas Heist, and Heiko Paulheim.