bibliography.bib

@book{validatingKG,
  doi       = {10.2200/s00786ed1v01y201707wbe016},
  url       = {https://doi.org/10.2200/s00786ed1v01y201707wbe016},
  year      = {2017},
  month     = {sep},
  publisher = {Morgan {\&} Claypool Publishers {LLC}},
  volume    = {7},
  number    = {1},
  pages     = {1--328},
  author    = {Labra Gayo, Jose Emilio and Prud{\textquotesingle}hommeaux, Eric and Boneva, Iovka and Kontokostas, Dimitris},
  title     = {Validating {RDF} Data},
  series    = {Synthesis Lectures on the Semantic Web: Theory and Technology}
}

@misc{Vue,
  title        = {{Vue.js}, Documentation},
  howpublished = {\url{https://v3.vuejs.org/}}
}

@misc{Primeue,
  title        = {{PrimeVue}, Documentation},
  howpublished = {\url{https://www.primefaces.org/primevue/}}
}

@book{validatingKG,
  doi       = {10.2200/s00786ed1v01y201707wbe016},
  url       = {https://doi.org/10.2200/s00786ed1v01y201707wbe016},
  year      = {2017},
  month     = {sep},
  publisher = {Morgan {\&} Claypool Publishers {LLC}},
  volume    = {7},
  number    = {1},
  pages     = {1--328},
  author    = {Labra Gayo, Jose Emilio and Prud{\textquotesingle}hommeaux, Eric and Boneva, Iovka and Kontokostas, Dimitris},
  title     = {Validating {RDF} Data},
  series    = {Synthesis Lectures on the Semantic Web: Theory and Technology}
}

@misc{Jena,
  title        = {{Apache Jena}, Documentation},
  howpublished = {\url{https://jena.apache.org/index.html}}
}

@misc{Primeue,
  title        = {{PrimeVue}, Documentation},
  howpublished = {\url{https://www.primefaces.org/primevue/}}
}

@misc{werkmeister_rdf2graph_git,
  author       = {WerkMeister, Lucas},
  title        = {RDF2Graph},
  year         = {2022},
  publisher    = {GitHub},
  journal      = {GitHub repository},
  howpublished = {\url{https://github.com/lucaswerkmeister/RDF2Graph}},
  commit       = {522a636c551b88a6b24cae9d19a3447596d65e5c},
  note         = {Accessed: 2022-01-16}
}
}

@mastersthesis{werkmeister2018,
  author = {Lukas Werkmeister},
  title  = {Schema Inference on Wikidata},
  school = {Karlsruher Institut für Technologie, Fakultät für Informatik},
  year   = {2018}
}

@misc{original_rdf2graph_git,
  author       = {van Dam, Jesse},
  title        = {RDF2Graph},
  year         = {2022},
  publisher    = {GitHub},
  journal      = {GitHub repository},
  howpublished = {\url{https://github.com/jessevdam/RDF2Graph/}},
  commit       = {9873826a53bd9cedc31df9dfbb172a08ea74b0f8},
  note         = {Accessed: 2022-01-16}
}
}

@article{vanDam2015,
  author   = {van Dam, Jesse CJ
              and Koehorst, Jasper J.
              and Schaap, Peter J.
              and Martins dos Santos, Vitor AP
              and Suarez-Diez, Maria},
  title    = {RDF2Graph a tool to recover, understand and validate the ontology of an RDF resource},
  journal  = {Journal of Biomedical Semantics},
  year     = {2015},
  month    = {Oct},
  day      = {23},
  volume   = {6},
  number   = {1},
  pages    = {39},
  abstract = {Semantic web technologies have a tremendous potential for the integration of heterogeneous data sets. Therefore, an increasing number of widely used biological resources are becoming available in the RDF data model. There are however, no tools available that provide structural overviews of these resources. Such structural overviews are essential to efficiently query these resources and to assess their structural integrity and design, thereby strengthening their use and potential.},
  issn     = {2041-1480},
  doi      = {10.1186/s13326-015-0038-9},
  url      = {https://doi.org/10.1186/s13326-015-0038-9}
}

@misc{RDFShape,
  author       = {Jose Emilio Labra Gayo},
  title        = {RDFShape},
  year         = 2021,
  howpublished = {\url{https://rdfshape.herokuapp.com/validate}},
  note         = {Accessed: 2022-01-23}
}

@article{Shexer,
  title    = {Automatic extraction of shapes using sheXer},
  journal  = {Knowledge-Based Systems},
  volume   = {238},
  pages    = {107975},
  year     = {2022},
  issn     = {0950-7051},
  doi      = {https://doi.org/10.1016/j.knosys.2021.107975},
  url      = {https://www.sciencedirect.com/science/article/pii/S0950705121010972},
  author   = {Daniel Fernandez-Álvarez and Jose Emilio Labra-Gayo and Daniel Gayo-Avello},
  keywords = {Knowledge Graph, RDF, ShEx, SHACL, Automatic extraction},
  abstract = {There is an increasing number of projects based on Knowledge Graphs and SPARQL endpoints. These SPARQL endpoints are later queried by final users or used to feed many different kinds of applications. Shape languages, such as ShEx and SHACL, have emerged to guide the evolution of these graphs and to validate their expected topology. However, authoring shapes for an existing knowledge graph is a time-consuming task. The task gets more challenging when dealing with sources, possibly maintained by heterogeneous agents. In this paper, we present sheXer, a system that extracts shapes by mining the graph structure. We offer sheXer as a free Python library capable of producing both ShEx and SHACL content. Compared to other automatic shape extractors, sheXer includes some novel features such as shape inter-linkage and computation of big real-world datasets. We analyze the features and limitations w.r.t. performance with different experiments using the English chapter of DBpedia.}
}
       
@inproceedings{Spahiu2016ABSTATOL,
  title     = {ABSTAT: Ontology-driven Linked Data Summaries with Pattern Minimalization},
  author    = {Blerina Spahiu and Riccardo Porrini and Matteo Palmonari and Anisa Rula and Andrea Maurino},
  booktitle = {SumPre@ESWC},
  year      = {2016}
}

@misc{git_shapes,
  author       = {McKenney, Danielle 
  				and Magnussen, Kristina 
  				and Gritsch, Philipp
  				and Wintner, Valerian
  				and Hochrainer, Jamie},
  title        = {KG Shapes},
  year         = {2022},
  publisher    = {GitHub},
  journal      = {GitHub repository},
  howpublished = {\url{https://git.uibk.ac.at/csaz8448/kg-shapes}},
  note         = {Accessed: 2022-02-04}
}