Data Science and Engineering

249 papers and 2.6k indexed citations i.

About

The 249 papers published in Data Science and Engineering in the last decades have received a total of 2.6k indexed citations. Papers published in Data Science and Engineering usually cover Artificial Intelligence (137 papers), Information Systems (75 papers) and Computer Networks and Communications (66 papers) specifically the topics of Data Management and Algorithms (42 papers), Advanced Graph Neural Networks (41 papers) and Complex Network Analysis Techniques (34 papers). The most active scholars publishing in Data Science and Engineering are Guoliang Li, Haitao Yuan, Yanchun Zhang, Siuly Siuly, Kaiyu Li, Josep Domingo‐Ferrer, Liwei Wang, Prem Prakash Jayaraman, Zhiyong Peng and Xingquan Zhu.

In The Last Decade

Fields of papers published in Data Science and Engineering

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Data Science and Engineering. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Data Science and Engineering.

Countries where authors publish in Data Science and Engineering

Since Specialization
Citations

This map shows the geographic impact of research published in Data Science and Engineering. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Data Science and Engineering with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Data Science and Engineering more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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2025