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Using Knowledge Graphs to Model Green Investment Opportunities

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New Trends in Database and Information Systems (ADBIS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1850))

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Abstract

International institutions are funding renewable energy initiatives to transition to a carbon-neutral economy and combat the effects of climate change. However, the involvement of multiple institutions and the absence of a standardized database of investment opportunities make it difficult for interested parties to discover and consider these opportunities.

In this paper, we propose a standardized modeling approach based on knowledge graphs to represent green change investment opportunities funded by international organizations. Such an approach offers many advantages, including the ability to obtain a comprehensive overview of all available investment opportunities and uncover hidden patterns in the underlying data.

We also report the results of an exploratory analysis of green investments in African countries using traditional graph metrics and community detection algorithms on a knowledge graph created with our model. The results are consistent with the existing literature on this topic.

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Acknowledgments

This work was partially supported by Università di Roma - La Sapienza Research Project 2021 “Caratterizzazione, sviluppo e sperimentazione di algoritmi efficienti”. It was also supported in part by INdAM - GNCS Project 2023 “Approcci computazionali per il supporto alle decisioni nella Medicina di Precisione”. It was also supported by the PON Project, DM1062 10/08/2021, “AIGREET: using Artificial Intelligence to support GREEn investments for promoting the Ecological Transition”, financed by the “Ministero dell’Università e della Ricerca”. Finally, it was supported by an initiative with the industrial partner “Internationalia S.r.L.” for the “Development and design of a system for the automatic detection of green investment documents from freely available resources, based on machine learning and NLP”.

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Authors and Affiliations

  1. Sapienza University of Rome, Piazzale Aldo Moro 5, 00185, Rome, Italy

    Giorgio Grani, Lorenzo Di Rocco & Umberto Ferraro Petrillo

Authors
  1. Giorgio Grani
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  2. Lorenzo Di Rocco
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  3. Umberto Ferraro Petrillo
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Corresponding author

Correspondence to Giorgio Grani .

Editor information

Editors and Affiliations

  1. Universitat Politècnica de Catalunya, Barcelona, Spain

    Alberto Abelló

  2. University of Ioannina, Ioannina, Greece

    Panos Vassiliadis

  3. Universitat Politècnica de Catalunya, Barcelona, Spain

    Oscar Romero

  4. Poznań University of Technology, Poznan, Poland

    Robert Wrembel

  5. University of Paris-Saclay, Gif-sur-Yvette, France

    Francesca Bugiotti

  6. Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

    Johann Gamper

  7. CNRS, Villeurbanne Cedex, France

    Genoveva Vargas Solar

  8. University of Calabria, Rende, Italy

    Ester Zumpano

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Grani, G., Di Rocco, L., Petrillo, U.F. (2023). Using Knowledge Graphs to Model Green Investment Opportunities. In: Abelló, A., et al. New Trends in Database and Information Systems. ADBIS 2023. Communications in Computer and Information Science, vol 1850. Springer, Cham. https://doi.org/10.1007/978-3-031-42941-5_38

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  • DOI: https://doi.org/10.1007/978-3-031-42941-5_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-42940-8

  • Online ISBN: 978-3-031-42941-5

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