Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update in-practice.md Added link and some formatting #173

Merged
merged 1 commit into from
Jan 3, 2025
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
20 changes: 10 additions & 10 deletions content/about/in-practice.md
Original file line number Diff line number Diff line change
Expand Up @@ -21,9 +21,9 @@ references to them (by NUMBER.LETTER) on other pages.
<!-- proposed abbreviated principles are in comments (like this one) -->

<!-- 1: Study planning -->
1. Study planning
1. **Study planning**
<!-- 1a: Implement good science -->
1. Implement good science basics (power analysis, statistical consults, etc.).
1. Implement good science basics ([power analysis, statistical consults, etc.](https://www.repronim.org/module-stats/)).
<!-- 1b: Use pre-existing data -->
2. Use pre-existing data for planning and/or analysis.
<!-- 1c: Create a DSMP -->
Expand All @@ -34,7 +34,7 @@ references to them (by NUMBER.LETTER) on other pages.
5. [Pre-register](https://www.cos.io/initiatives/prereg) your study.

<!-- 2: Data and metadata management -->
2. Data and metadata management
2. **Data and metadata management**
<!-- 2a: Use standard data formats -->
1. Use standard data formats and extend them to meet your needs.
<!-- 2b: Use data version control -->
Expand All @@ -43,7 +43,7 @@ references to them (by NUMBER.LETTER) on other pages.
3. Annotate data using standard, reproducible procedures.

<!-- 3: Software management -->
3. Software management
3. **Software management**
<!-- 3a: Use released open source software -->
1. Use released versions of open source software.
<!-- 3b: Use software version control -->
Expand All @@ -58,7 +58,7 @@ references to them (by NUMBER.LETTER) on other pages.
6. Use containers where reasonable.

<!-- 4: Publishing everything -->
4. Publishing everything (publishing re-executable publications)
4. **Publishing everything** (publishing re-executable publications)
<!-- 4a: Share research plans -->
1. Share plans (pre-registration).
<!-- 4b: Share software -->
Expand All @@ -72,15 +72,15 @@ references to them (by NUMBER.LETTER) on other pages.

As indicated by the blue highlights in the figure below, four core actions are key to implementing the above principles.

1. Use of standards.
1. **Use of standards**

Using standard data formats and extending them to meet specific research needs is important for data and metadata management (Principle 2) in reproducible neuroimaging.
Using standard data formats and extending them to meet specific research needs is important for data and metadata management (Principle 2) in reproducible neuroimaging.

2. Annotation and provenance.
3. **Annotation and provenance**

Annotating data using standard, reproducible procedures ensures clarity and transparency in data management (Principle 2). _Provenance_ refers to the origin and history of data and processes, enabling researchers to track how data was generated, modified, and analyzed (Principles 2, 3, and 4). This is essential for understanding the context of data and ensuring reproducibility.

3. Implementation of version control.
4. **Implementation of version control**

Version control is crucial for both data and software management. It allows researchers to track changes over time, revert to previous versions if necessary, and collaborate effectively.

Expand All @@ -90,7 +90,7 @@ As indicated by the blue highlights in the figure below, four core actions are k

And even publications can be versioned (Principle 4).

4. Use of containers.
5. **Use of containers**

Containers provide a portable and self-contained environment for running software, ensuring that the analysis can be executed consistently across different computing environments (Principle 3). Containers encapsulate all of the software dependencies needed to run an analysis, making it easier to share software (Principle 4) and reproduce results.

Expand Down
Loading