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Documents authored by Acosta, Maribel


Artifact
Software
EDIFACT-VAL

Authors: Johannes Mäkelburg and Maribel Acosta


Abstract

Cite as

Johannes Mäkelburg, Maribel Acosta. EDIFACT-VAL (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@misc{dagstuhl-artifact-25246,
   title = {{EDIFACT-VAL}}, 
   author = {M\"{a}kelburg, Johannes and Acosta, Maribel},
   note = {Software, version 2.0., swhId: \href{https://archive.softwareheritage.org/swh:1:dir:d820a10d861cfd9e361208220cf7aad3b03ef1a6;origin=https://github.com/DE-TUM/EDIFACT-VAL;visit=swh:1:snp:14393634954285b38ae3b633fcef776355055a82;anchor=swh:1:rev:466199b528ed85d7ffeae6441455d705253283fc}{\texttt{swh:1:dir:d820a10d861cfd9e361208220cf7aad3b03ef1a6}} (visited on 2025-12-10)},
   url = {https://github.com/DE-TUM/EDIFACT-VAL},
   doi = {10.4230/artifacts.25246},
}
Document
Use Case
Automating Invoice Validation with Knowledge Graphs: Optimizations and Practical Lessons

Authors: Johannes Mäkelburg and Maribel Acosta

Published in: TGDK, Volume 3, Issue 3 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 3


Abstract
To increase the efficiency of creating, distributing, and processing of invoices, invoicing is handled in the form of Electronic Data Interchange (EDI). With EDI, invoices are handled in a standardized electronic or digital format rather than on paper. While EDIFACT is widely used for electronic invoicing, there is no standardized approach for validating its content. In this work, we tackle the problem of automatically validating electronic invoices in the EDIFACT format by leveraging KG technologies. We build on a previously developed pipeline that transforms EDIFACT invoices into RDF knowledge graphs (KGs). The resulting graphs are validated using SHACL constraints defined in collaboration with domain experts. In this work, we improve the pipeline by enhancing the correctness of the invoice representation, reducing validation time, and introducing error prioritization through the use of the severity predicate in SHACL. These improvements make validation results easier to interpret and significantly reduce the manual effort required. Our evaluation confirms that the approach is correct, efficient, and practical for real-world use.

Cite as

Johannes Mäkelburg and Maribel Acosta. Automating Invoice Validation with Knowledge Graphs: Optimizations and Practical Lessons. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 2:1-2:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@Article{makelburg_et_al:TGDK.3.3.2,
  author =	{M\"{a}kelburg, Johannes and Acosta, Maribel},
  title =	{{Automating Invoice Validation with Knowledge Graphs: Optimizations and Practical Lessons}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:24},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.2},
  URN =		{urn:nbn:de:0030-drops-252137},
  doi =		{10.4230/TGDK.3.3.2},
  annote =	{Keywords: Electronic Invoice, Ontology, EDIFACT, RDF, RML, SHACL}
}
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