Topical Collection: Interdisciplinary - Data-Enabled Discovery and Applications
This special collection continues to provide avenues of dissemination for researchers using the increased availability of extensive data sets to quantitatively model real-world systems, and seek new discoveries, innovations and applications, often across the boundaries of traditional disciplines. Especially sought are contributions investigating novel research strategies so as to enable scientific discoveries, engineering innovations, or advances in medical diagnosis, prognosis, and treatment.
- Balances general solution techniques with problem-specific results
- Offers a forum for sharing methods and best practices that reveal patterns and associations embedded in data
- Highlights data-centric tools created or cross-utilized to solve discipline-specific problems, and include suggestions for broader applications
- Prof. Alan A. Barhorst
- Prof. Gang (Gary) Qi
Papers must describe original research and must not be simultaneously submitted to a journal or a conference with proceedings.
All submissions should follow the instructions available at: https://www.springer.com/journal/42452/submission-guidelines
Authors can directly submit their papers at https://www.editorialmanager.com/snas During the submission procedure, please select the title of this Topical Collection from the section/category (drop down menu) in Editorial Manager.