Selected Canadian Research Data Management Resources
DataONE Webinar Series
Cutting-edge discussions in research data management. Monthly discussions on open science, the role of the data lifecycle, and achieving innovative science through shared data and ground-breaking tools.
As the research data management landscape continues to evolve, it is crucial that researchers and data professionals have the information and training they need to stay up-to-date with the latest developments and best practices. The Training Expert Group (TEG) oversees a range of specific projects that collaboratively develop and deliver both training and training resources to support all aspects of RDM skill development for a variety of stakeholders across Canada. Current areas of interest include developing and implementing a national RDM training strategy, supporting initiatives such as webinars and “workshops in a box”, and working with Portage’s Expert and Working Groups to develop domain-specific, researcher-focused training.
Excerpt: The ESIP Federation, in cooperation with NOAA and the Data Conservancy, seeks to share the community's knowledge with scientists who increasingly need to be better data managers, as well as to support workforce development for new data management professionals. Over the next several years, the ESIP Federation expects to evolve training courses which seeks to improve the understanding of scientific data management among scientists, emerging scientists, and data professionals of all sorts. All courses are available under a Creative Commons Attribution 3.0 license that allows you to share and adapt the work as long as you cite the work according to the citation provided.
What is a Data Journal? "Data journals consist of data articles that describe how, why and when a dataset was collected and any derived data product. Rather than presenting any analysis or conclusions, a data article may present arguments about the value of the data for future analysis. "Such publishing mechanism both give credit that is recognizable within the scientific ecosystem, and also ensure the quality of the published data and metadata through the peer review process"
Definition for data journals taken from "Whyte, A. (2015). ‘Where to keep research data: DCC checklist for evaluating data repositories’ v.1.1 Edinburgh: Digital Curation Centre. Available online: https://www.dcc.ac.uk/guidance/how-guides/where-keep-research-data"
Examples of Data Journals:
While there are many ways of looking at the data life cycle, this particular image emphasizes the repurposing and re-use of data, which is a driving force behind the success of data intensive science and the reason why data management has been deemed so important.
Source: Humphrey, Charles. (2006). “e-Science and the life cycle of research.” Retrieved 23 January 2011 from http://datalib.library.ualberta.ca/~humphrey/lifecycle-science060308.doc
On older video, but still relevant: A data management snafu-story by Karen Hanson, Alisa Surkis and Karen Yacobucci.