The New England Journal of Statistics in Data Science (NEJSDS)
Fast, Accessible, Cutting-edge, Top-quality
The NEJSDS is the official journal of the New England Statistical Society (NESS). The aims of the journal are to serve as an interface between statistics and other disciplines in data science, to encourage researchers to exchange innovative ideas, and to promote data science methods to the general scientific community. The journal publishes high quality original research, novel applications, and timely review articles in all aspects of data science, including (but not limited to) all areas of statistical methodology, methods of machine learning, and artificial intelligence, novel algorithms, computational methods, data management and manipulation, applications of data science methods, among others. We encourage authors to submit collaborative work driven by real life problems posed by researchers, administrators, educators, or other stakeholders, and which require original and innovative solutions from data scientists.
Our mission is to harness the power of statistics and data science to contribute to society through the advancement of scientific research and the creation of long-term collaborations, which includes:
- Posing research questions, subject-matter expert hypotheses or aims, and suggestions for data sources and collection methods.
- Proposed designs and methods based on past research, or new methodologies when existing ones are shown to be inadequate.
- Data analysis - application of the proposed methods, introducing new software tools, proposing insightful and effective visualization methods, addressing computational challenges, and providing innovative solutions.
- Discussions - conclusions and refinements of the research aims or hypotheses, highlighting policy or societal implications, and critiques of the proposed methods.
NEJSDS is proud to be a pioneer to reform the peer review process. In addition to the traditional process (Track I), NEJSDS is committed to implementing a new hybrid two-step journal review process (Track II) that allows authors’ involvement.
This new process (Track II) provides an option for authors to select whether they would like to participate the review process. This new track includes:
Step 1: An author-led open review step to facilitate instant discussions and dissemination of submitted work. In this step, the authors can solicitate review reports (or scientific feedback) of their article from the research community, and share the reports with our editorial board. The author(s) have up to six-weeks to complete this step.
Step 2: An editor-led closed-door peer review process to ensure quality of accepted articles. A decision on the article is expected to be reached within 4-8 weeks time frame after author-led open review reports is provided. The final decision on the manuscript will be based on the reports both from Step 1 and Step 2.
The author-led peer review reports in Step 1 are unblinded and they are open to both the authors and the editorial board. The peer review reports in the second step are anonymous.
Call for a Special Issue on “Pushing the Boundary of Data Science through Statistical Modelling and Inference”
Submission deadline: March 15, 2024.