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@ARTICLE{Menon:1052752,
      author       = {Menon, Sarath and Azocar Guzman, Abril and Waseda, Osamu
                      and Sandfeld, Stefan and Hickel, Tilmann},
      title        = {tools4{RDF}: {A} {P}ython toolkit for working with {RDF}
                      data},
      journal      = {The journal of open source software},
      volume       = {11},
      number       = {117},
      issn         = {2475-9066},
      address      = {[Erscheinungsort nicht ermittelbar]},
      publisher    = {[Verlag nicht ermittelbar]},
      reportid     = {FZJ-2026-01109},
      pages        = {9482 -},
      year         = {2026},
      abstract     = {tools4RDF is a lightweight Python framework designed to
                      simplify working with RDF-based ontologies and data models.
                      It allows one or more ontologies to be parsed and
                      represented as Python classes, making it easier to navigate
                      and explore their structure through features like
                      autocompletion in interactive environments such as Jupyter
                      notebooks. The framework preserves key semantic details such
                      as domain and range information, which can then be used
                      programmatically within Python workflows. A central goal of
                      the tool is to make querying knowledge graphs with SPARQL
                      more accessible to users without deep expertise in semantic
                      web technologies. This is achieved through a programmatic
                      interface that abstracts away much of the complexity
                      involved in writing SPARQL queries. The overall workflow of
                      the approach is illustrated in Figure 1, showing how
                      tools4RDF parses ontologies, constructs a network
                      representation, and generates SPARQL queries to retrieve
                      data from knowledge graphs. This design lowers the barrier
                      to entry for domain scientists and developers unfamiliar
                      with RDF, while still exposing enough control for advanced
                      use cases. Originally developed for ontology-driven data
                      integration in materials science, tools4RDF is
                      ontology-agnostic and can be used across a wide range of
                      scientific domains.},
      cin          = {IAS-9},
      ddc          = {004},
      cid          = {I:(DE-Juel1)IAS-9-20201008},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / DFG project
                      G:(GEPRIS)460247524 - NFDI-MatWerk - Nationale
                      Forschungsdateninfrastruktur für Materialwissenschaft $\&$
                      Werkstofftechnik (460247524)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(GEPRIS)460247524},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.21105/joss.09482},
      url          = {https://juser.fz-juelich.de/record/1052752},
}