Guidelines for the Open Science Challenge 2024
1. Material Accessibility:
- Make materials accessible 2 weeks before the meeting (deadline 23 February) on a suitable platform, such as GitHub or OpenNeuro.
- Materials may be kept non-public, until official publication of the results (in that case we ask to make the read-me already available) but must be shared for evaluation.
- Ensure comprehensive documentation for installation, running, and usage of the materials.
2. Submission Process:
- Complete and submit a form on the ISMRM Benelux website with the following personal details:
- Name
- Institute (if applicable)
- Current position and start date
- And the follow submission details:
- Title of the abstract
- Type of submission
- Method or Study
- Impact Statement (max 200. Words)
- Describe the target audience for your materials and how they will benefit from them.
- Link to the material (with password if required)
- Specific commit hash or tag (where applicable)
- Statement when you expect the data or code will be publicly available and where
Participant Expectations
- Make materials available:
- Privately, at least 2 weeks (February 23) prior to the meeting to the jury.
- Publicly at least after publication (mandatory in case you win the challenge).
- Include a QR code in your poster or presentation that links to your materials
- Be prepared to deliver a 1-minute power-pitch of your submission in a plenary session if awarded.
- Notification of pre-selection will be communicated one week prior (1st of March) to the meeting.
Jury and Evaluation Criteria:
- Clear README with enough information how to use the tool/software/data (e.g. installation, requirements and visualization tools).
- Impact and benefit to the community.
- Flexibility and applicability of the materials (e.g. is the tool also useful for other experiments or can the data be used for additional analysis).
- Novelty and originality.
- Quality of documentation (e.g. 1. Method: are there enough comments or is there an example dataset available; 2. Study: data is arranged logically, with structured metadata).