Research data management good practice self-assessment tool
Creators: name: Chan, Janice
name: Brown, John
name: Tebo, Molly
Publisher: name: Zenodo
Year: 2021
Subjects: Research Data Management
self assessment
Qualtrics
Research support
Research data management training
Western Australia
FAIR principles
Research reproducibility
data management planning

description: 28 July 2022: Version two of the self-assessment tool was designed to be completed independently by researchers. An objective is to have Research Data Champions (RDC) complete the tool before and after participation and use score changes to demonstrate the effectiveness of the program. Accordingly, responses have been changed from anonymous to confidential to allow linking of data. The answers are now displayed in a random order for each question to encourage careful thought. The tool was also amended to include more detailed feedback using display logic to help RDCs understand their results. Each section is assigned a separate score in the survey flow to facilitate this. The feedback sections include links to suggested resources; these are also emailed to respondents in PDF form after they have completed the survey. *********** The Research Data Management (RDM) good practice self-assessment tool is developed by Curtin University Library for the Research Data Champion (RDC) Program. The program focuses on training, promotion and advocacy for research reproducibility; good research data management practice; data management planning; and FAIR principles. The self-assessment tool was developed to provide RDCs with a model of RDM good practice, which will help the RDCs to identify a path for further training and development. The tool will help the Program Lead to identify deep-dive training topics as well as to measure the effectiveness of the program. It was developed with the intention to complete as a group in a workshop setting. The tool is divided into 5 sections: general knowledge, organisation and retention, analysis and writing, data sharing, and data ethics. Each section contains statements that represent the behaviour or practice at various experience levels. The tool attempts to provide respondent practices at 4 levels of RDM experience: <strong>Newbie</strong>: I do not have a RDM strategy and do not know where to seek help. <strong>Amateur</strong>: I’m aware of the importance of a good RDM strategy but unsure how to develop one. I’m aware of the support available, but do not know who to ask. <strong>Pro</strong>: I have good understanding of RDM and have an effective RDM strategy in place for my own projects, and I know of people who can connect me with someone who can give advice. <strong>Hero</strong>: I’m able to adapt RDM strategies to different contexts and understand the implications of RDM on research outcomes; I’m well-connected with the right people who can give advice. The tool was developed using Qualtrics. For each question, there are 4 statements, each has a score from 1 to 4 representing the 4 experience levels: newbie, amateur, pro, and hero. At the end of the survey, a total score will be presented to the respondent. For areas that may not be relevant to all research, the “N/A” option is available. All questions are optional because respondents are guided by the facilitator in the workshop. The creators have made this tool available in 2 formats. QSF can be imported directly into Qualtrics and DOCX for editing outside of Qualtrics. Please note that the tool contains references to terminology and legislation specific to Curtin University and Western Australia and requires some amendments to be suitable for use elsewhere.