Julián Arenas-Guerrero
@ArenasGuerreroJ
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Assistant professor at @La_UPM.
Madrid
Joined November 2021
Arenas Guerrero, Julián (2025). Efficient and Extensive Construction of Knowledge Graphs from Diverse Data with Declarative Mappings. https://t.co/v87OQknbyt
#tesis @ArenasGuerreroJ @ocorcho
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🔴Ante el aviso de la @AEMET_Madrid del riesgo de inundaciones en la @ComunidadMadrid que recomienda evitar los desplazamientos, 𝗦𝗘 𝗦𝗨𝗦𝗣𝗘𝗡𝗗𝗘 toda la actividad académica y todas aquellas no imprescindibles durante el viernes 21 de marzo. #somosUPM
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Happy to share with you our most recent paper that presents the latest features implemented in Morph-KGC: https://t.co/HODeG1w8B2 In summary, the benefits of this latest implementation are: 1) Compliance to RML-FNML, the latest specification for data transformations in RML. 1/3
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"The RML Ontology: A Community-Driven Modular Redesign After a Decade of Experience in Mapping Heterogeneous Data to RDF", paper accepted at @iswc_conf is also proposed for the best paper award at the resources track! #iswc2023 🥳🥳🥳 Paper available ➡️➡️ https://t.co/0mBTAyxa3j
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Thrilled to introduce @ArenasGuerreroJ, a distinguished visiting researcher from @La_UPM. Julián delivered a very interesting presentation titled "Towards a new architecture for virtual Knowledge graphs". Let's embrace this collaboration and learn from Julián's expertise! 🧑💻🖥️
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Morph-KGC v2.6.0 is out featuring native support for user-friendly mappings with #YARRRML (also for RML-star & RML-FNML). The mapping parser has been upgraded to comply with the latest version of #RML. https://t.co/WqVr939jEg
github.com
This release features support for YARRRML, a user-friendly serialization of RML (also for RML-star and RML-FNML). Compliance with RML-Core has also been implemented. Changes #167: YARRRML support....
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@_aieme updates us on the new state of the #RML specification. The overview of the modular vocabulary is available at https://t.co/XQaOlsBI8a looking for your feedback!!! #eswc2023
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Morph-KGC 2.4.0 is out featuring transformation functions with #RML+#FnO! #Python user defined-functions are also supported @mijaspao @ocorcho @oeg_upm. https://t.co/bWwtlNj1ZY
github.com
This release of Morph-KGC features declarative data transformations with RML+FnO. In addition to a set of built-in functions, Python user-defined functions are also supported. Changes #117: RML+FnO...
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The @liusemweb group is bowling, with @Sijin_Cheng @HuanYuLi1 @Ying_Li924 @olafhartig @SeiekiSenpai & Mina, together with @oeg_upm guest: @ArenasGuerreroJ
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Our paper "Morph-KGC: Scalable Knowledge Graph Materialization with Mapping Partitions" has been accepted at the @SW_Journal 🥳 w/ @dchavesf @jhon_anibal @ocorcho @oeg_upm
https://t.co/7vVfzgjHs3
We are happy to announce a new member of the #morph family, Morph-KGC, the [R2]RML engine of @oeg_upm to construct #RDF knowledge graphs from heterogeneous data sources. https://t.co/jNKcRLdh2f
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Last session! @ArenasGuerreroJ from @oeg_upm presents Morph-KGC, an engine that parsers RML and RML-star mapping rules for constructing #KnowledgeGraphs
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On 29th May I will be presenting Morph-KGC at the Knowledge Graph Construction Tutorial at #ESWC2022 @eswc_conf @cost_dkg @kgc_workshop Check the Google #Colab notebook that we have prepared! https://t.co/LecOqSb2uG
colab.research.google.com
Colab notebook
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The tutorial is a joint effort with @cost_dkg, where we have such an amazing set of presenters @samstwitting @_aieme @ArenasGuerreroJ @mario_scrock @umutsims @DylanVanAssche and @sjrm_142857 coordinated by the W3C CG KGC chairs @dchavesf and @natadimou
https://t.co/3oyMU9Gqai
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In addition, Morph-KGC now integrates with @oxigraph to create and exploit RDF-star data all from #Python. You can read the docs in the brand new website! https://t.co/4NNKPzbOwT
https://t.co/08EFYNOkuS
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We have also prepared the RML-star test cases based on the RDF-star Syntax Tests by the RDF-DEV Community Group. Morph-KGC is currently passing all the RML-star test cases, which have been added to the continuous integration pipeline in #GitHub. https://t.co/LBAJlSeRdi
github.com
Archived repository. Contribute to kg-construct/rml-star-test-cases development by creating an account on GitHub.
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The RML-star specification is publicly available online, which is being developed by the Knowledge Graph Construction W3C Community Group as an extension of the #RML mapping language @kgc_workshop. Morph-KGC is the first engine supporting RML-star! https://t.co/hmbCSlSqmn
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Morph-KGC v2.0.0 is out featuring RML-star! We are now able to generate RDF-star datasets from heterogeneous data sources using declarative mappings w/ @_aieme @dchavesf @natadimou @dgarijov @ocorcho @oeg_upm
https://t.co/jNKcRLdh2f
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Getting data in the right format to uncover hidden knowledge is a challenge. #RDF is one of the best knowledge building @w3c formats but it's not popular. We want to change this - here are some tools for data transform. ingestion, updates & virtualization:
ontotext.com
Data transformation, ingestion, updates and virtualization for turning data into a graph and managing it with GraphDB
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