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Evolvable transformation of knowledge graphs into human-oriented formats

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Abstract

Along with the ongoing digitalization of society, we witness a strong movement to make scientific data FAIR, machine-actionable, and available in the form of knowledge graphs. On the other hand, converting machine-actionable data from knowledge graphs back into human-oriented formats, including documents, graphical, or voice user interfaces, poses significant challenges. The solutions often build on various templates tailored to specific platforms on top of the shared underlying data. These templates suffer from limited reusability, making their adaptations difficult. Moreover, the continuous evolution of data or technological advancements requires substantial efforts to maintain these templates over time. In general, these challenges increase software development costs and are error-prone. In this paper, we propose a solution based on Normalized Systems Theory to address this challenge with the aim of achieving evolvability and sustainability in the transformation process of knowledge graphs into human-oriented formats with broad applicability across domains and technologies. We explain the theoretical foundation and design theorems used in our solution and outline the approach and implementation details. We theoretically evaluate our solution by comparing it to the traditional approach, where the systems are crafted manually. The evaluation shows that our solution is more efficient and effective on a large scale, reducing the human labor required to maintain various templates and supported target platforms. Next, we demonstrate the technical feasibility of our solution on a proof-of-concept implementation in a domain of data management planning that may also serve as a basis for future development.

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Availability of Data and Material

All data and materials are published on GitHub. The links to the GitHub repositories are included in the article.

Code Availability

All created code is published on GitHub. The links to the GitHub repositories are included in the article.

Notes

  1. https://www.dbpedia.org

  2. https://www.wikidata.org

  3. https://developers.google.com/knowledge-graph

  4. Scientific knowledge graphs are also widely supported by public funding, such as by the European Commission (https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/horizon-infra-2023-eosc-01-03)

  5. https://www.w3.org/2018/09/rdf-data-viz

  6. https://normalizedsystems.org/about-us/

  7. http://vowl.visualdataweb.org/v2/

  8. http://purl.org/dc/terms/

  9. https://www.w3.org/2018/09/rdf-data-viz/

  10. https://registry.ds-wizard.org/templates/datenzee:rdf-template:latest

  11. http://purl.org/datenzee/view-ontology

  12. https://github.com/datenzee/template-editor-frontend

  13. https://github.com/datenzee/template-editor-backend

  14. https://github.com/RDFLib/rdflib

  15. https://palletsprojects.com/p/jinja/

  16. https://vuejs.org

  17. https://github.com/datenzee/expanders

  18. https://github.com/datenzee/dmp-vue-handcrafted

  19. https://github.com/datenzee/dmp-doc-handcrafted

  20. https://github.com/datenzee/dmp-data-components

  21. https://github.com/datenzee/dmp-vue-expanded

  22. https://github.com/datenzee/dmp-doc-expanded

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Acknowledgements

This research was supported by grant No. LM2023055 of the Ministry of Education, Youth and Sports of Czech Republic and grant No. SGS20/209/OHK3/3T/18 of Czech Technical University in Prague.

Funding

This research was supported by grant No. LM2023055 of the Ministry of Education, Youth and Sports of Czech Republic and grant No. SGS20/209/OHK3/3T/18 of Czech Technical University in Prague.

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Authors and Affiliations

  1. Faculty of Information Technology, Czech Technical University in Prague, Thákurova 9, 160 00, Prague, Czech Republic

    Jan Slifka, Vojtěch Knaisl & Robert Pergl

Authors
  1. Jan Slifka
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  2. Vojtěch Knaisl
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  3. Robert Pergl
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Contributions

Jan Slifka participated in the design of the solution. He created a view ontology and an expander from data components to the Vue App. He further created a client application for the Template Editor. Vojtech Knaisl participated in the design of the solution. He created data components for the data management plans and an expander from data components to the DSW document template. He further created a server application for the Template Editor. Robert Pergl supervised the work.

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Correspondence to Jan Slifka.

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Jan Slifka and Vojtech Knaisl these authors contributed equally to this work.

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Slifka, J., Knaisl, V. & Pergl, R. Evolvable transformation of knowledge graphs into human-oriented formats. J Intell Inf Syst (2023). https://doi.org/10.1007/s10844-023-00809-w

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