IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v9y2025i4p144-d1769754.html

Interoperable Knowledge Graphs for Localized Supply Chains: Leveraging Graph Databases and RDF Standards

Author

Listed:
  • Vishnu Kumar

    (Department of Industrial and Systems Engineering, Morgan State University, Baltimore, MD 21251, USA)

Abstract

Background : Ongoing challenges such as geopolitical conflicts, trade disruptions, economic sanctions, and political instability have underscored the urgent need for large manufacturing enterprises to improve resilience and reduce dependence on global supply chains. Integrating regional and local Small- and Medium-Sized Enterprises (SMEs) has been proposed as a strategic approach to enhance supply chain localization, yet barriers such as limited visibility, qualification hurdles, and integration difficulties persist. Methods : This study proposes a comprehensive knowledge graph driven framework for representing and discovering SMEs, implemented as a proof-of-concept in the U.S. BioPharma sector. The framework constructs a curated knowledge graph in Neo4j, converts it to Resource Description Framework (RDF) format, and aligns it with the Schema.org vocabulary to enable semantic interoperability and enhance the discoverability of SMEs. Results : The developed knowledge graph, consisting of 488 nodes and 11,520 edges, enabled accurate multi-hop SME discovery with query response times under 10 milliseconds. RDF serialization produced 16,086 triples, validated across platforms to confirm interoperability and semantic consistency. Conclusions : The proposed framework provides a scalable, adaptable, and generalizable solution for SME discovery and supply chain localization, offering a practical pathway to strengthen resilience in diverse manufacturing industries.

Suggested Citation

  • Vishnu Kumar, 2025. "Interoperable Knowledge Graphs for Localized Supply Chains: Leveraging Graph Databases and RDF Standards," Logistics, MDPI, vol. 9(4), pages 1-25, October.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:4:p:144-:d:1769754
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/9/4/144/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2305-6290/9/4/144/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sarkis, Joseph & Dhavale, Dileep G., 2015. "Supplier selection for sustainable operations: A triple-bottom-line approach using a Bayesian framework," International Journal of Production Economics, Elsevier, vol. 166(C), pages 177-191.
    2. Shaojun Zhou & Yufei Liu & Yuhan Liu, 2024. "A Market Convergence Prediction Framework Based on a Supply Chain Knowledge Graph," Sustainability, MDPI, vol. 16(4), pages 1-20, February.
    3. Li, Yuhong & Zobel, Christopher W. & Seref, Onur & Chatfield, Dean, 2020. "Network characteristics and supply chain resilience under conditions of risk propagation," International Journal of Production Economics, Elsevier, vol. 223(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maria Björklund & Helena Forslund, 2019. "Challenges Addressed by Swedish Third-Party Logistics Providers Conducting Sustainable Logistics Business Cases," Sustainability, MDPI, vol. 11(9), pages 1-15, May.
    2. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    3. Davis-Sramek, Beth & Robinson, Jessica L. & Darby, Jessica L. & Thomas, Rodney W., 2020. "Exploring the differential roles of environmental and social sustainability in carrier selection decisions," International Journal of Production Economics, Elsevier, vol. 227(C).
    4. Giovanna Culot & Matteo Podrecca & Guido Nassimbeni & Guido Orzes & Marco Sartor, 2023. "Using supply chain databases in academic research: A methodological critique," Journal of Supply Chain Management, Institute for Supply Management, vol. 59(1), pages 3-25, January.
    5. Lin, Edward M.H. & Sun, Edward W. & Yu, Min-Teh, 2020. "Behavioral data-driven analysis with Bayesian method for risk management of financial services," International Journal of Production Economics, Elsevier, vol. 228(C).
    6. Ghanei, Shima & Contreras, Ivan & Cordeau, Jean-François, 2023. "A two-stage stochastic collaborative intertwined supply network design problem under multiple disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    7. Dmitry Ivanov, 2026. "Collaborative emergency adaptation for ripple effect mitigation in intertwined supply networks," Annals of Operations Research, Springer, vol. 359(2), pages 1727-1743, April.
    8. Liang, Zhenglin & Li, Yan-Fu, 2023. "Holistic Resilience and Reliability Measures for Cellular Telecommunication Networks," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    9. Chen, Yucheng & Xia, Yongxiang & Hua, Zhen, 2025. "Risk propagation in supply-chain network considering node heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 657(C).
    10. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    11. Jimin Shim & Joonho Moon & Won Seok Lee & Namho Chung, 2021. "The Impact of CSR on Corporate Value of Restaurant Businesses Using Triple Bottom Line Theory," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    12. Jiuping Xu & Xianglan Jiang & Zhibin Wu, 2016. "A Sustainable Performance Assessment Framework for Plastic Film Supply Chain Management from a Chinese Perspective," Sustainability, MDPI, vol. 8(10), pages 1-23, October.
    13. Nihan Kabadayı, 2020. "An Integrated Fuzzy DEMATEL and Intuitionistic Fuzzy TOPSIS Method to Evaluate Sustainable Suppliers," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 8(2), pages 201-226, December.
    14. Baghersad, Milad & Zobel, Christopher W., 2021. "Assessing the extended impacts of supply chain disruptions on firms: An empirical study," International Journal of Production Economics, Elsevier, vol. 231(C).
    15. Tanksale, Ajinkya N. & Das, Debabrata & Verma, Priyanka & Tiwari, Manoj Kumar, 2021. "Unpacking the role of primary packaging material in designing green supply chains: An integrated approach," International Journal of Production Economics, Elsevier, vol. 236(C).
    16. Xingqi Zou & Qing Yang & Qinru Wang & Bin Jiang, 2024. "Measuring the system resilience of project portfolio network considering risk propagation," Annals of Operations Research, Springer, vol. 340(1), pages 693-721, September.
    17. Esra Boz & Sinan Çizmecioğlu & Ahmet Çalık, 2022. "A Novel MDCM Approach for Sustainable Supplier Selection in Healthcare System in the Era of Logistics 4.0," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
    18. Irina Makarova & Rifat Khabibullin & Eduard Belyaev & Larisa Gabsalikhova & Eduard Mukhametdinov, 2016. "Improving the Logistical Processes in Corporate Service System," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 11(1), pages 5-18, March.
    19. Zhu, Qingyun & Shah, Purvi & Sarkis, Joseph, 2018. "Addition by subtraction: Integrating product deletion with lean and sustainable supply chain management," International Journal of Production Economics, Elsevier, vol. 205(C), pages 201-214.
    20. Hossein Mirzaee & Sahand Ashtab, 2024. "Sustainability, Resiliency, and Artificial Intelligence in Supplier Selection: A Triple-Themed Review," Sustainability, MDPI, vol. 16(19), pages 1-28, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlogis:v:9:y:2025:i:4:p:144-:d:1769754. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.