Best Research Article Award
Domingos Filipe de Oliveira – Lamar University
The Best Research Article Award recognizes scholarly publications demonstrating originality, methodological rigor, and meaningful contributions to research. This article presents a profile of Domingos Filipe de Oliveira in the field of data science, outlining the supplied bibliometric information, research profile, potential contributions, and relevance to academic recognition. The information should be verified against authoritative records before publication. [1]
Abstract
This article outlines an academic recognition profile for Domingos Filipe de Oliveira, whose supplied research information identifies Data Science as the subject area. The provided bibliometric figures include eight documents, 28 citations, and an h-index of three. These indicators offer a preliminary overview but cannot independently establish research quality or award eligibility. [2]
Keywords
Domingos Filipe de Oliveira, Best Research Article Award, Data Science, Research Evaluation, Bibliometrics, Scholarly Publications, Citation Analysis, Research Impact, Academic Recognition, Research Excellence.
Introduction
Data science supports research through statistical analysis, computational methods, and evidence-based interpretation. Recognizing strong research articles encourages methodological transparency, originality, and reproducibility. The Best Research Article Award provides a framework for celebrating scholarly contributions while considering publication quality, relevance, and documented impact. Evaluation should combine expert assessment with verifiable research evidence. [3]
Research Profile
Domingos Filipe de Oliveira is presented as a researcher associated with Data Science. The supplied bibliometric details list eight documents, 28 citations, and an h-index of three under Scopus author identifier 57427542700. Institutional affiliations and profile metrics should be checked against current authoritative records before publication to ensure the accuracy of this academic profile.[2]
Research Contributions
Research contributions in data science may include developing analytical methods, interpreting complex datasets, improving computational workflows, and producing reproducible findings. Assessing this researcher’s specific contributions requires reviewing verified publications, methodologies, and documented results. Each work should be evaluated for originality, scientific validity, practical relevance, and its relationship to existing scholarly literature. [3]
Publications
The supplied Scopus information reports eight documents associated with the researcher’s author identifier. A complete publication assessment should examine article titles, journal or conference details, publication dates, co-authors, and available digital object identifiers. Individual publication records have not been independently verified for this article; therefore, specific titles and DOI numbers are not listed. [1]
Research Impact
The supplied metrics report 28 citations and an h-index of three, offering an initial view of citation activity. However, citation counts vary by database, publication age, and discipline. A balanced impact assessment should also consider methodological influence, reproducibility, practical applications, and contributions to subsequent research rather than relying exclusively on quantitative indicators.[3]
Award Suitability
The Best Research Article Award may be relevant to work demonstrating originality, methodological rigor, clear reporting, and meaningful scholarly contributions. Determining the researcher’s eligibility requires reviewing the nominated article, publication status, supporting evidence, and official award criteria. The available profile metrics alone cannot confirm nomination eligibility, selection, or receipt of an award. [3]
Conclusion
This profile summarizes the supplied academic information for Domingos Filipe de Oliveira within Data Science. The reported publication and citation metrics provide a starting point for further evaluation, not a definitive measure of scholarly merit. Verified institutional details, confirmed publications, and transparent assessment criteria are essential for accurate academic recognition and responsible award-related communication. [1]
External Links
References
- Integrating PDCA and CRISP-DM: A Design Science Framework for Quality Assurance and Control in Data Science Projects.
https://link.springer.com/chapter/10.1007/978-3-032-21147-7_26
- Active Learning in the Detection of Anomalies in Cryptocurrency Transactions.
https://www.mdpi.com/2504-4990/5/4/84
- Performance of Machine Learning Algorithms for IT Incident Management
https://www.researchgate.net/publication/348641478