In collaboration with ESIP and participants at the 2016 Data Fair during the AGU Fall Meeting, listed below are several resources, tools, and guidelines to help researchers, authors, and journals in managing data throughout the data lifecycle.

Guiding principles for data and software citation:

COPDESS Best Practices for Journals: http://www.copdess.org/copdess-suggested-author-instructions-and-best-practices-for-journals/

Including data citations in talks: http://www.copdess.org/agu-best-practices-for-data-in-oral-presentations/

Best Practices For Repositories: http://biorxiv.org/content/early/2016/12/28/097196 A new article on “A Data Citation Roadmap for Scholarly Data Repositories” by Martin Fenner et al.

Guidelines and help for creating reproducible papers

Data Management Training

Data Management Plan information and tools

Podcasts

In person courses and training resources:

Tools to organize and link your data, code, notes, and more across your research workflow:

  • Recordr – tracks provenance and publishes software, inputs, and outputs–package for R https://github.com/NCEAS/recordr and matlab https://github.com/DataONEorg/matlab-dataone
  • Project Jupyter – The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more. Works across 40 programming languages.
  • org – Turn a GitHub repo into a collection of interactive notebooks
  • Open Science Framework: https://osf.io/ and http://help.osf.io/ – A scholarly commons to connect the entire research cycle

Information on ID’s