Countries where authors publish in Data Science Journal
Since Specialization
Citations
This map shows the geographic impact of research published in Data Science Journal. 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 Journal 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 Journal more than expected).
Fields of papers published in Data Science Journal
This network shows the impact of papers published in Data Science Journal. 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 Journal.
About Data Science Journal
The 799 papers published in Data Science Journal in the last decades have received a total of 9.3k indexed citations . Papers published in Data Science Journal usually cover Information Systems (470 papers), Information Systems and Management (85 papers), Geology (53 papers), Conservation (14 papers) and Artificial Intelligence (84 papers) specifically the topics of Research Data Management Practices (421 papers), Scientific Computing and Data Management (58 papers), Environmental Monitoring and Data Management (49 papers), Semantic Web and Ontologies (39 papers), Geomagnetism and Paleomagnetism Studies (29 papers), Data Analysis and Archiving (17 papers), Big Data Technologies and Applications (16 papers) and Digital and Traditional Archives Management (14 papers). The most active scholars publishing in Data Science Journal are Yangyong Zhu, Li Cai, Mark A. Parsons, Stephanie Russo Carroll, Desi Rodriguez-Lonebear, Dirk Pilat, Paul F. Uhlir, Norman Paskin, Jianhui Li and Andrew O. Martinez.
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.