Scatterplot: The MAA Journal of Data Science serves the mathematics community by providing research and expository content at the intersection of mathematics, data science and educational practice. Suggested topics include pedagogy and teaching practice, development of curricula that combine mathematics and data science at the course or program level, intersections with other disciplines, social justice and ethics, and exposition of mathematical ideas used in data science applications. Teaching approaches that help grow and diversify the population of students in these fields are especially encouraged, as are contributions describing the experience of current students or recent graduates in applications and careers.
The journal publishes the following broad areas and article types:
Curricular innovation & Evidence-based teaching practice:
• Research Articles
• Review Articles
• Notes
• Target Articles
Case studies:
(These should include peer reviewed teaching notes to make them more likely to be adopted for classroom use)
• Data Notes (if brief and with focus on teaching)
• Case Reports (if longer and with focus on outcomes/application)
Conversations with mathematicians and data scientists in the workforce:
• Interviews (can include video or audio files)
• Multimedia Articles (can include video, audio, or other visual or interactive media alongside text)
Explanations of data science tools or software packages for mathematicians:
• Book Reviews
• Product reviews
• Notes
Ethics and equity issues in mathematics and data science:
• Research Articles
• Review Articles
• Editorials (Invited only or at Editor’s discretion. These are opinion pieces, policy statements, or general commentaries, and should take a point of view encouraging specific practice).
• Article Commentaries
If you are unsure about the article type for your manuscript, please contact Editor-in-Chief Rick Cleary at [email protected].
Proposals for high-quality special issues are welcome and should be discussed with the Editor-in-Chief in the first instance.
The Journal encourages submissions from all backgrounds regardless of career stage, geography, gender, or any other defining characteristic. Scatterplot aims to be a truly inclusive journal.
Peer Review Policy
All submitted manuscripts are subject to Crossref similarity checks and initial appraisal by the Editor-in-Chief and/or one of the Associate Editors. If found suitable for further consideration, the following peer review policies will be carried out:
• Research Articles, Review Articles, and Target Articles will be subject to peer review by at least two anonymous independent expert referees.
• Article Commentaries, Case Reports, Data Notes, Interviews, Multimedia Articles, and Notes will be subject to peer review by at least one independent, anonymous expert referee in addition to that of the Editor.
• Book Reviews, Editorials, and Product Reviews will be subject to peer review by the Editor.
Consistent with MAA policy, all peer reviews will be double blind.
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