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Building Something Real
Assignment for MC-4 Fall 2025 © Anatoly Scherbakov

This document synthesizes technical and business considerations for building knowledge graphs in real-world enterprise contexts.

Big Picture Understanding: Technical and Business Considerations Combined

I first found out about the Semantic Web maybe around 2013, when I was a university student. I played a little bit with RDF, SPARQL, and with a PHP triple store that supported them (I think the up to date version of that product is now known as semsol/arc2).

Since then, time to time, I returned to this topic as a detour from my software development career. I had a few ideas about what to do, did some learning, prototypes and experiments. That went rather slowly though.

Linked Data Visualization book cover

Then, at one point, I read the book:

Linked Data Visualization: Techniques, Tools and Big Data by Laura Po, Nikos Bikakis, Federico Desimoni, and George Papastefanatos (Morgan & Claypool, 2020), ISBN: 9781681737256, linkeddatavisualization.com

I noticed that, even though the book analyzes a bunch of RDF visualization tools, none of them have been used to build tables, graphs, charts, lists in the book itself.

This hinted that there is a general issue with converting a piece of RDF into something a human can easily view.


Fresnel vocabulary was one attempt to solve the issue. It seems to be a little bit constraining though. Particular type of visualizations are tied to particular RDF terms from the vocabulary; Fresnel is coupled with HTML and CSS. What if we want to visualize data not in HTML but, say, in the terminal? Or in 3D?

I thought something more generic, which would allow using an arbitrary piece of code (known henceforth as a Facet) to render Linked Data in a certain fashion, would be interesting to implement. So I did; I started working on this iteration of Iolanta in January 2023.

I implemented facets, terms, and a rudimentary ontology, built a website, but… it is a frustrating experience to have a technology and search for use cases where it can be applied.

I feel the KGC Course helped me change my perspective.

Application to Work, Projects, and Real-World Situations

Going through the course was one particular use case for Iolanta — not just because its ontology was the subject matter but also because I used it to prepare the papers for the course extensively. Particular parts of the course motivated development of particular features.

In addition, what I feel I got from this course is this:

Use case should drive technology

I am reformatting the roadmap for the project with a distinct set of use cases for which Iolanta might be of use, and I am tying enhancements to its technology to those use cases. Primarily, these are the use cases I am interested at myself. Obviously, I will be very happy to find out what other people think.

This roadmap demonstrates how technical foundations enable higher-level usecases such as managing ADRs, building roadmaps, and writing nanopublications with Iolanta, reflecting the synthesis of technical and business considerations for real-world knowledge graph applications.

What Still Needs Clarification

  • What industries might benefit from an RDF visualization tool?
  • What use cases to focus on?
  • Are there perspectives of self-sustainability for this project, remembering that it must always remain open source?

Conclusion

The KGC course helped me shift from building technology in search of problems to identifying usecases that drive technical development. The roadmap reflects this change: technical foundations (facets, SPARQL, inference) now enable specific usecases (nanopublications, ADRs, roadmaps) rather than existing as solutions awaiting applications.

In the purely technological sense,

  • I learned a lot about ontology building as a discipline,
  • Found out about foundational ontologies,
  • Improved my understanding of OWL,
  • Got valuable feedback.

Thanks! I greatly enjoyed the experience.