The 2nd issue of IASSIST Quarterly

01. 10. 2021

You are invited to read the 2nd issue of IASSIST Quarterly!

In the new issue, the central point of the articles is data management, which, for IASSIST members, is as vital as breathing. The importance of transferring knowledge about data management is especially well illustrated by the first two articles, while the third prepares a new territory for future data management.

In the first article, titled Outside the R1: Equitable data management at the undergraduate level, author Elizabeth Blackwood describes the benefits of data management education at a university where research is not as highly developed and consequently professors and students are lacking in the field of data management. To help them, the author organised workshops where they could learn basic data management skills. Due to the success, workshops and student assignments were included in the permanent part of the undergraduate study program. The workshop proved to be particularly useful when the entire study process had to be transferred online.

The second article is titled Better data management, one nudge at a time, in which members of the Urbana-Champaign group from the University of Illinois described a lack of data management knowledge among researchers. The solution was found in the publication of a monthly Data Nudge email and what they soon found was that researchers became much more attentive to new practices and methodological approaches. The success of the project is also evident in many positive reviews from users. If you are also interested in the topics covered, you can find them here.

The third article, titled DATABOOK: a standardised framework for dynamic documentation of algorithm design during Data Science projects, is a comprehensive description of the tried and tested system to secure documentation and reproduction, which are fundamental concepts in data management. Anna Nesvijevskaia proposes a framework called Databook for Data Science, which is based on points of critique of other platforms, as it identifies many inconsistencies in traditional and modern tools, which also stem from differences between business goals and data skills.

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