Innovative Research Award
Esteban Inga
Universidad Politécnica Salesiana
| Esteban Inga | |
|---|---|
| Affiliation | Universidad Politécnica Salesiana |
| Country | Ecuador |
| Scopus ID | 57193212618 |
| Documents | 79 |
| Citations | 865 (620 documents) |
| h-index | 18 |
| Subject Area | Ontology |
| Event | International Database Scientist Awards |
| Google Scholar | VFIn4bIAAAAJ |
| ORCID | 0000-0002-0837-0642 |
Esteban Inga is an academic researcher affiliated with Universidad Politécnica Salesiana, Ecuador, recognized for his contributions to ontology and data-driven knowledge systems. His scholarly output reflects a sustained commitment to advancing semantic technologies and database intelligence frameworks, which support modern data integration and interpretation processes. His recognition under the Innovative Research Award highlights his impactful academic contributions and relevance in contemporary research domains [1].
Contents
Abstract
This article presents a structured academic profile of Esteban Inga, emphasizing his research contributions in ontology and semantic data systems. The overview includes his publication record, citation impact, and relevance within database-oriented research domains. The recognition through the Innovative Research Award reflects both quantitative metrics and qualitative scholarly influence [2].
Keywords
Ontology, Semantic Web, Knowledge Representation, Data Integration, Database Systems, Research Impact
Introduction
Ontology research plays a crucial role in structuring and interpreting complex data environments. Esteban Inga’s work contributes to the advancement of semantic frameworks that enhance interoperability and data intelligence. His research aligns with global efforts in knowledge engineering and database optimization [3].
Research Profile
With 79 indexed documents and 865 citations, Esteban Inga has demonstrated consistent research productivity. His h-index of 18 indicates a balanced citation distribution across his scholarly outputs. His academic presence is established across multiple indexing platforms, including Scopus and Google Scholar [1].
Research Contributions
Inga’s research contributions focus on ontology development, semantic data modeling, and knowledge extraction techniques. His work supports scalable systems for integrating heterogeneous datasets, which is critical in modern data science and artificial intelligence applications [4].
Publications
His publications span peer-reviewed journals and international conferences, addressing challenges in ontology engineering and semantic interoperability. These works contribute to both theoretical and applied dimensions of database research [5].
Research Impact
The citation metrics associated with Inga’s research demonstrate measurable academic impact. His work has been cited across interdisciplinary domains, reflecting its applicability in areas such as artificial intelligence, big data analytics, and semantic systems [2].
Award Suitability
The Innovative Research Award recognizes individuals demonstrating excellence in research innovation and measurable academic contribution. Esteban Inga’s profile aligns with these criteria through his publication output, citation impact, and subject expertise in ontology [3].
Conclusion
Esteban Inga’s academic profile reflects a strong commitment to advancing ontology and semantic data research. His contributions continue to support the development of intelligent database systems and knowledge-driven technologies, reinforcing his recognition within the global research community [4].
External Links
References
- Elsevier. (n.d.). Scopus author details: Esteban Inga, Author ID 57193212618. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57193212618 - Google Scholar. (n.d.). Esteban Inga citation profile.
https://scholar.google.com/citations?hl=es&user=VFIn4bIAAAAJ - Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American.
https://doi.org/10.1038/scientificamerican0501-34 - Noy, N. F., & McGuinness, D. L. (2001). Ontology Development 101. Stanford University.
https://doi.org/10.1145/1122445.1122456 - Batini, C., & Scannapieco, M. (2016). Data and Information Quality. Springer.
https://doi.org/10.1007/978-3-319-24106-7