One of the first knowledge graphs (KG) that we at DataFabric built (and continue to evolve) was the knowledge graph of Federal Tax Service of Russian Federation (FTS) which accumulates tremendous amount of data about Russian companies and individuals. In this story I dive into the details of the steps we took and what we continue to do to maintain the knowledge graph.

What is the Federal Tax Service’s data about?

The data contains information about russian and foreign companies, sole proprietorships (a.k.a. individual entrepreneurs), people, government organizations, open-end funds.

Here and after, the numbers may be inexact, since during the generation of the knowledge graph some data…

We at DataFabric help companies build knowledge graphs on top of their existing data to facilitate better access through unified interfaces, reusability, data enrichment and as a result better analytics and automation. And as in case of any relatively new and complex technology, it’s important to understand and exploit the same terms (a.k.a. names) for things.

It’s a one way to build knowledge graphs

In DataFabric, we tend to exploit the characteristics of a knowledge graph proposed in [1], saying that a knowledge graph:

  1. mainly describes real world entities and their interrelations, organized in a graph.
  2. defines possible classes and relations of entities in a schema.
  3. allows for…

I believe, converting bunch of CSV, JSON or XML files to an RDF format is a very popular task for people dealing with Semantic Web, Linked Data, RDF and such stuff. However, I can’t easily name a ready-to-use converter that I’d recommend, so I’ve decided to review some of them to use the most suitable one next time.


I found more than a dozen of converters, but included in the review only those which:

  • are alive and well maintained,
  • I’ve managed to install and use.

In the result we have six tools. I also classified them based on the functions…

Maksim Kolchin

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