Journal of Data Science,
Statistics, and Visualisation

Editorial Founding Issue




The Journal of Data Science, Statistics, and Visualisation (JDSSV) is an electronic journal which welcomes contributions to data science, statistics, and visualisation, and in particular, those aspects which link and integrate these subject areas. Articles can cover topics such as machine learning and statistical learning, the visualisation and verbalisation of data, visual analytics, big data infrastructures and analytics, interactive learning, and advanced computing. Articles that
discuss two or more research areas of the journal are favoured. Scientific contributions should be of a high standard.

Articles should be oriented towards a wide scientific audience of statisticians, data scientists, computer scientists, data analysts, etc. The journal welcomes original contributions that are not being considered for publication elsewhere and contain a high level of novelty. Articles with a thorough but concise review of a certain topic with the potential to provide new insights are also welcome. Manuscripts submitted to the journal generally are accompanied by supplementary material containing software code, data, technical derivations or detailed explanations, additional examples, etc. All submitted material will be reviewed by the assigned associate editor and reviewers of the manuscript.




How to Cite

Van Aelst, S., & Groenen, P. J. F. (2021). Editorial Founding Issue. Journal of Data Science, Statistics, and Visualisation, 1(1).
Journal of Data Science,
Statistics, and Visualisation