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International Journal of Data Science and Analytics

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Int. J. Data Science and Analytics
DisciplineData Science / Statistics / Machine Learning
LanguageEnglish
Edited byLongbing Cao
Publication details
History2015–present
Publisher
Frequency8 issues per year
Standard abbreviations
ISO 4Int. J. Data Sci. Anal.
Indexing
ISSN2364-415X (print)
2364-4168 (web)
Links

The International Journal of Data Science and Analytics (JDSA) is the first scientific journal in data science and analytics science. JDSA publishes original, fundamental and applied research outcomes in data science and analytics theories, technologies and applications. It promotes new scientific and technological approaches to strategic value creation in data-rich applications.

JSDA is a peer-reviewed scientific journal, published since 2015. JDSA is with the Springer-Nature publisher. The inaugural Editor-in-Chief is Longbing Cao (University of Technology Sydney, Australia).

JDSA is indexed by Web of Science, Scopus, and EI Compendex. It sits in the top-20 publications in Google Metrics: Data Mining & Analysis [1].

Selected articles

  • Longbing Cao (2016). Data science and analytics: a new era [2]
  • Claus Weihs, Katja Ickstadt (2018). Data Science: the impact of statistics [3]
  • Valerio Grossi, Fosca Giannotti, Dino Pedreschi, Paolo Manghi, Pasquale Pagano, Massimiliano Assante (2021). Data science: a game changer for science and innovation [4]
  • Longbing Cao, Qiang Yang, Philip S. Yu (2021). Data science and AI in FinTech: an overview [5]
  • Ruth M. Pfeiffer, Daniel B. Kapla, Efstathia Bura (2021). Least squares and maximum likelihood estimation of sufficient reductions in regressions with matrix-valued predictors [6]
  • Sofie De Cnudde, David Martens, Theodoros Evgeniou, Foster J. Provost (2020). A benchmarking study of classification techniques for behavioral data [7]
  • Ioanna Tsalouchidou, Ricardo Baeza-Yates, Francesco Bonchi , Kewen Liao , Timos Sellis (2020). Temporal betweenness centrality in dynamic graphs [8]
  • Daniel Berrar, Werner Dubitzky (2019): Should significance testing be abandoned in machine learning? [9]
  • Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu (2019): Multi-task network embedding [10]
  • Peter A. Flach, Myra Spiliopoulou, Serge Allegrezza, Matthias Böhmer, Burkhard Hess, Berthold Lausen (2018). Introduction to the special issue on Data Science in Europe [11]
  • Longbing Cao, Jae-Gil Lee, Xuemin Lin (2018). Introduction to the special issue on Data Science in Asia [12]
  • Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti (2017). Exposing the probabilistic causal structure of discrimination [13]
  • Frederick Eberhardt (2017). Introduction to the foundations of causal discovery [14]
  • Salman Salloum, Ruslan Dautov, Xiaojun Chen, Patrick Xiaogang Peng, Joshua Zhexue Huang (2016). Big data analytics on Apache Spark [15]
  • Huan Liu, Fred Morstatter, Jiliang Tang, Reza Zafarani (2016). The good, the bad, and the ugly: uncovering novel research opportunities in social media mining [16]

References

  1. ^ "Data Mining & Analysis - Google Scholar Metrics". scholar.google.com. Retrieved 2022-02-10.
  2. ^ Cao, Longbing (2016). "Data science and analytics: a new era". International Journal of Data Science and Analytics. 1 (1): 1–2. doi:10.1007/s41060-016-0006-1.
  3. ^ Weihs, Claus; Ickstadt, Katja (2018). "Data Science: the impact of statistics". International Journal of Data Science and Analytics. 6 (3): 189–194. doi:10.1007/s41060-018-0102-5.
  4. ^ Grossi, Valerio; Giannotti, Fosca; Pedreschi, Dino; Manghi, Paolo; Pagano, Pasquale; Assante, Massimiliano (2021). "Data science: a game changer for science and innovation". International Journal of Data Science and Analytics. 11 (4): 263–278. doi:10.1007/s41060-020-00240-2.
  5. ^ Cao, Longbing; Yang, Qiang; Yu, Philip S. (2021). "Data science and AI in FinTech: an overview". International Journal of Data Science and Analytics. 12 (2): 81–99. doi:10.1007/s41060-021-00278-w.
  6. ^ Pfeiffer, Ruth M.; Kapla, Daniel B.; Bura, Efstathia (2021). "Least squares and maximum likelihood estimation of sufficient reductions in regressions with matrix-valued predictors". International Journal of Data Science and Analytics. 11 (1): 11–26. doi:10.1007/s41060-020-00228-y.
  7. ^ De Cnudde, Sofie; Martens, David; Evgeniou, Theodoros; Provost, Foster (2020). "A benchmarking study of classification techniques for behavioral data". International Journal of Data Science and Analytics. 9 (2): 131–173. doi:10.1007/s41060-019-00185-1.
  8. ^ Tsalouchidou, Ioanna; Baeza-Yates, Ricardo; Bonchi, Francesco; Liao, Kewen; Sellis, Timos (2020). "Temporal betweenness centrality in dynamic graphs". International Journal of Data Science and Analytics. 9 (3): 257–272. doi:10.1007/s41060-019-00189-x.
  9. ^ Berrar, Daniel; Dubitzky, Werner (2019). "Should significance testing be abandoned in machine learning?". International Journal of Data Science and Analytics. 7 (4): 247–257. doi:10.1007/s41060-018-0148-4.
  10. ^ Xu, Linchuan; Wei, Xiaokai; Cao, Jiannong; Yu, Philip S. (2019). "Multi-task network embedding". International Journal of Data Science and Analytics. 8 (2): 183–198. doi:10.1007/s41060-018-0166-2.
  11. ^ Flach, Peter; Spiliopoulou, Myra; Allegrezza, Serge; Böhmer, Matthias; Hess, Burkhard; Lausen, Berthold (2018). "Introduction to the special issue on Data Science in Europe". International Journal of Data Science and Analytics. 6 (3): 163–165. doi:10.1007/s41060-018-0153-7.
  12. ^ Cao, Longbing; Lee, Jae-Gil; Lin, Xuemin (2018). "Introduction to the special issue on Data Science in Asia (with PAKDD'2017)". International Journal of Data Science and Analytics. 6 (4): 271–272. doi:10.1007/s41060-018-0157-3.
  13. ^ Bonchi, Francesco; Hajian, Sara; Mishra, Bud; Ramazzotti, Daniele (2020). "Correction to: Exposing the probabilistic causal structure of discrimination". International Journal of Data Science and Analytics. 9 (3): 373–373. doi:10.1007/s41060-019-00184-2.
  14. ^ Eberhardt, Frederick (2017). "Introduction to the foundations of causal discovery". International Journal of Data Science and Analytics. 3 (2): 81–91. doi:10.1007/s41060-016-0038-6.
  15. ^ Salloum, Salman; Dautov, Ruslan; Chen, Xiaojun; Peng, Patrick Xiaogang; Huang, Joshua Zhexue (2016). "Big data analytics on Apache Spark". International Journal of Data Science and Analytics. 1 (3–4): 145–164. doi:10.1007/s41060-016-0027-9.
  16. ^ Liu, Huan; Morstatter, Fred; Tang, Jiliang; Zafarani, Reza (2016). "The good, the bad, and the ugly: uncovering novel research opportunities in social media mining". International Journal of Data Science and Analytics. 1 (3–4): 137–143. doi:10.1007/s41060-016-0023-0.
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