Discover Journal Series
- A new series of fully open access journals
- Focusing on speed, service and integrity
- Covering hot topics from across all disciplines
Our series of Discover Journals is a collection of fully open access journals committed to providing all authors a streamlined submission process, rapid review and publication, and a high level of author service at every stage. The series will consist of up to 40 new titles covering hot topics from across the full range of applied science, physical, life, medical and social disciplines.
Discover Analytics is an international, open access journal that publishes papers on all areas of analytics research, management science/operations research, and related fields. Papers should describe work that adds to the understanding of analytical theory, detail research on new or existing analytical methodologies, or report on the application of analytical techniques for the discovery, interpretation, and communication of meaningful patterns of data across multidisciplinary areas.
Discover Health Systems is a fully open access interdisciplinary journal, publishing research across all fields relevant to health systems research. The journal welcomes work that addresses systems-level research and discussions relating to health systems, services and informatics.
Discover Data is a fully open access interdisciplinary journal, publishing theory and applications of data science and data analytics across all fields of research. The journal welcomes content covering the application of existing data science-driven techniques to novel problems in science, industry and society, as well as primary research into data theory, management and analysis.
Discover Mechanical Engineering is a multi-disciplinary, open access, community-focused journal publishing research from across all fields relevant to mechanical engineering. The journal welcomes experimental, theoretical, analytical, modeling, and applied approaches that advance the study and practice of mechanical engineering. It particularly welcomes research that contributes to achieving the global aims of the United Nations Sustainable Development Goals, such as Goal 9: to Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation.
Discover Education is an open access community-focused journal publishing research results from a broad range of education fields with the potential to impact social and academic development. The journal covers a broad range of areas related to education in schools, universities, vocational institutions, early childhood settings and the community. It aims to support the United Nations Sustainable Development Goal of ensuring inclusive and equitable quality education and promoting lifelong learning opportunities for all.
|Editor-in-Chief Professor Constantin Zopounidis about Discover Analytics|
“Discover Analytics aims to create a peer-reviewed forum where analytics research, management science/operations research and related fields can gather to discuss, debate, identify and evaluate satisfied ways that achieve efficient solutions in private and public organizations. With a rigorous and streamlined review process, the journal seeks to provide a forum for the rapid evaluation of methodologies and solutions to this critical challenge facing the scientific and professional communities today”
Editors-in-Chief, Dr. Vanni Agnoletti and Dr Rodolfo Catena, about Discover Health Systems
“Covid-19 has shown us the limits of health systems globally. Costs are soaring worldwide and there is an increasing pressure on healthcare professionals to deliver care with tighter budgets. This journal is a place where professionals from different disciplines can communicate with each other. The goal of this journal is to promote change at different levels in the health system and in different domains.''
Editor-in-Chief, Prof. Nitesh V. Chawla, about Discover Data
“It is an exciting and timely opportunity to envision a journal that is at the intersection of data and society. As the applications of data science / machine learning / artificial intelligence become more pervasive and ubiquitous, it becomes increasingly important to look at all aspects from data collection to applications, especially from a social contract perspective. To truly reap the benefits of innovations stemming from data science, there will also have to be a framework that demonstrates alignment with societal needs and grand challenge problems, algorithmic and data responsibility, and knowledge of and
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