Journal of Data Science,
Statistics, and Visualisation

“We welcome contributions to data science, statistics, and visualisation, and in particular those aspects which link and integrate these subject areas.”

About the Journal

The journal welcomes contributions to practical aspects of data science, statistics and visualisation, and in particular those which are linking and integrating these subject areas. Papers should thus be oriented towards a very wide scientific audience, and can cover topics such as machine learning and statistical learning, the visualisation and verbalisation of data, big data infrastructures and analytics, interactive learning, advanced computing, and other important themes. JDSSV is an open access journal that charges no author fees. The journal now has a new review process aimed at reducing the turnaround time between initial submission and publication of accepted papers to three months.

2024-03-20
Ying Chen, Patrick Groenen, Kwan-Liu Ma, Stefan Van Aelst
2024-02-07
Alan Inglis, Andrew Parnell, Catherine Hurley
2022-11-28
Shih-Hsiung Chou, Philip Turk, Marc Kowalkowski, James Kearns, Jason Roberge, Jennifer Priem, Yhenneko Taylor, Ryan Burns, Pooja Palmer, Andrew McWilliams
2022-11-28
Inger Fabris-Rotelli, Jenny Holloway, Zaid Kimmie, Sally Archibald, Pravesh Debba, Raeesa Manjoo-Docrat, Alize le Roux, Nontembeko Dudeni-Tlhone, Charl Janse van Rensburg, Renate Thiede, Nada Abdelatif, Sibusisiwe Makhanya, Arminn Potgieter
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Journal of Data Science,
Statistics, and Visualisation
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