Integrating Knowledge Engineering for Semantic Interoperability in Intelligent Digital Libraries and Health Research Information Systems

Pradhan, Ajit Kumar, Mishra, Manoj and Nanda, Susama Integrating Knowledge Engineering for Semantic Interoperability in Intelligent Digital Libraries and Health Research Information Systems. Journal of Library and Information Communication Technology, 2025, vol. 14, n. 2, pp. 15-26. [Journal article (Unpaginated)]

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English abstract

This article explores Knowledge Engineering (KE) technologies, including ontologies, knowledge graphs, and semantic reasoning, for developing flexible architectures for intelligent digital libraries (IDLs) and HRIS. Data from published case series, systematic reviews, and secondary sources were analysed thematically. Findings show that KE enhances semantic interoperability and information retrieval through ontology-based search, supporting effective decision-making. The approach is modular, scalable, and cross-disciplinary, benefiting librarians, healthcare informaticians, and policymakers.

Item type: Journal article (Unpaginated)
Keywords: Knowledge Engineering, Digital Libraries, Health Research Information Systems, Semantic Interoperability, Knowledge Graphs
Subjects: H. Information sources, supports, channels.
Depositing user: Mr Ajit Kumar Pradhan
Date deposited: 11 Aug 2026 19:10
Last modified: 11 Aug 2026 19:10
URI: http://hdl.handle.net/10760/47959

References

Bornmann, L., & Mutz, R. (2023). Growth rates of modern science: A bibliometric perspective. Quantitative Science Studies, 4(1), 1–16. https://doi.org/10.1162/qss_a_00235

Hajjem, C., Ben Yahia, S., & Slimani, Y. (2022). Semantic enrichment approaches for digital libraries: A systematic review. Journal of Information Science, 48(6), 798–815. https://doi.org/10.1177/01655515211028614

Hogan, A., Blomqvist, E., Cochez, M., D'Amato, C., de Melo, G., Gutiérrez, C., ... & Zimmermann, A. (2021). Knowledge graphs. ACM Computing Surveys, 54(4), 1–37. https://doi.org/10.1145/3447772

Kern, D., Alperin, J. P., & Haustein, S. (2023). Beyond metadata: The role of semantic infrastructures in scholarly communication. Scientometrics, 128(2), 1159–1180. https://doi.org/10.1007/s11192-023-04726-8

Li, Y., Zhang, H., & Chen, J. (2023). Digital libraries in the era of big data and AI: Opportunities and challenges. Information Processing & Management, 60(2), 103148. https://doi.org/10.1016/j.ipm.2022.103148

Wu, Y., Xu, J., & Wang, X. (2022). Biomedical knowledge graphs: Construction, applications, and challenges. Briefings in Bioinformatics, 23(1), bbab457. https://doi.org/10.1093/bib/bbab457

AbouZahr, C., & Boerma, T. (2005). Health information systems: The foundations of public health. Bulletin of the World Health Organization, 83(8), 578–583.

Ammar, W., Groeneveld, D., Bhagavatula, C., Beltagy, I., Crawford, M., Downey, D., ... & Etzioni, O. (2018). Construction of the Semantic Scholar research corpus. Proceedings of LREC 2018.

Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., ... & Sherlock, G. (2000). Gene Ontology: Tool for the unification of biology. Nature Genetics, 25(1), 25–29.

Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American, 284(5), 34–43.

Bodenreider, O. (2004). The Unified Medical Language System (UMLS): Integrating biomedical terminology. Nucleic Acids Research, 32(suppl_1), D267–D270.

Bollacker, K., Evans, C., Paritosh, P., Sturge, T., & Taylor, J. (2008). Freebase: A collaboratively created graph database. Proceedings of SIGMOD 2008, 1247–1250.

Borgman, C. L. (2000). From Gutenberg to the Global Information Infrastructure: Access to Information in the Networked World. MIT Press.

Candela, L., Castelli, D., & Pagano, P. (2007). On-demand virtual research environments and digital libraries. D-Lib Magazine, 13(3/4).

Foulonneau, M., & Cole, T. W. (2005). Strategies for reprocessing aggregated metadata to improve quality. Journal of Digital Information, 6(2).

Greenberg, J. (2009). Metadata and digital information. Annual Review of Information Science and Technology, 45(1), 247–286.

Himmelstein, D. S., Lizee, A., Hessler, C., Brueggeman, L., Chen, S. L., Hadley, D., ... & Baranzini, S. E. (2017). Systematic integration of biomedical knowledge for drug repurposing. Nature Biotechnology, 35(6), 530–536.

Hogan, A., Blomqvist, E., Cochez, M., D'Amato, C., de Melo, G., Gutiérrez, C., ... & Zimmermann, A. (2021). Knowledge graphs. ACM Computing Surveys, 54(4), 1–37.

Hyvönen, E. (2012). Publishing and Using Cultural Heritage Linked Data on the Semantic Web. Synthesis Lectures on the Semantic Web: Theory and Technology, 2(1), 1–159.

Kellermann, A. L., & Jones, S. S. (2013). What it will take to achieve the as-yet-unfulfilled promises of health information technology. Health Affairs, 32(1), 63–68.

Mungall, C. J., McMurry, J. A., Köhler, S., Balhoff, J. P., Borromeo, C., Brush, M., ... & Haendel, M. A. (2017). The Monarch Initiative: An integrative data and analytic platform connecting phenotypes to genotypes across species. Nucleic Acids Research, 45(D1), D712–D722.

Rector, A. L. (1999). Clinical terminology: Why is it so hard? Methods of Information in Medicine, 38(4/5), 239–252.

Simpao, A. F., Ahumada, L. M., Desai, B. R., & Bonafide, C. P. (2014). Realtime analytics: A new clinical frontier. Pediatric Anesthesia, 24(1), 7–14.

Wang, Q., Li, M., Wang, X., Parulian, N., Han, G., Ma, J., ... & Wei, C. H. (2020). COVID-19 literature knowledge graph construction and drug repurposing report generation. Proceedings of ACL 2020.

Zhang, R., Simon, G., & Yu, F. (2019). Advancing clinical research through semantic integration of EHR data. Journal of Biomedical Informatics, 94, 103188.

Gregor, S. (2006). The nature of theory in information systems. MIS Quarterly, 30(3), 611–642. https://doi.org/10.2307/25148742


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