Support for the ECS Data Sciences Hack Day

Abstract

Dataset sharing and open source software have transformed many Òbig scienceÓ areas such as astronomy, particle physics, synchrotron science, protein and genomic sciences, as well as computational sciences. These fields have been supported by, and actively developed, cloud-based computing and storage tools such as Github, Zenodo, FigShare, etc. Data science tools and approaches also have the potential to transform bench-science like electrochemistry. The critical need is to build a community of electrochemical data scientists, the people who will contribute to a growing library of shared experimental and computational datasets, and who develop and adapt open source software tools. ARO funding will be used to defray travel expenses for participants at the ECS Data Sciences Hack events at meetings of the Electrochemical Society (ECS). The ECS seeks to meet its mission to accelerate scientific and technical progress in electrochemical and solid state science through an initiative called ÒFree the ScienceÓ. Hack Day is a new vehicle to build an electrochemical data science community from the ground up, and will be followed every six months with Hack events at ECS meetings that support community building through education and software development sprints. Hack events will generate electrochemical open source software and open data sets with digital object identifiers that are available for other scientists and engineers to reuse and build from. In short, Hack events are part of an ambitious program by ECS to transform the kinds of research products that they support as open access, open source, and shared resources.

Document Details

Document Type
DoD Grant Award
Publication Date
Oct 25, 2018
Source ID
W911NF1710550

Entities

People

  • Daniel Schwartz

Organizations

  • Army Contracting Command
  • United States Army
  • University of Washington

Tags

Readers

  • Academic Conference Management
  • Distributed Systems and Data Platform Development
  • Marine Ecological Systems Migration

Technology Areas

  • AI & ML