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training/research-cycle-handbook/01-plan-and-design.qmd

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@@ -612,7 +612,7 @@ A **Data Management Plan (DMP)** documents how you will handle research data thr
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::: {.ms-1}
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- **Decide _before_ data collection whether you will eventually share your data publicly (and where)**, in order to (i) get ethics approval on the right plan, (ii) design consent form for participants, (iii) collect appropriate metadata for the target repository, ect.
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- **Start with what you know, and refine the details as your project develops.** Your DMP is a living document that you will refine to match the reality of your project while ensuring data protection and streamline collaborations (see [2.2. Data Management](02-collect-and-manage.qmd#sec-data-management){.mark}, [3.1. Data Processing & Analysis](03-analyze-and-collaborate.qmd#sec-data-processing-analysis){.mark}, and [4.1. Data Sharing](04-preserve-and-share.qmd#sec-data-sharing){.mark}).
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- **Start with what you know, and refine the details as your project develops.** Your DMP is a living document that you will refine to match the reality of your project while ensuring data protection and streamline collaborations (see [2.2. Data Management](02-collect-and-manage.qmd#sec-data-management){.mark}, [3.1. Data Processing & Analysis](03-analyze-and-collaborate.qmd#sec-data-processing-analysis){.mark}, and [4.1. FAIR Data Sharing](04-preserve-and-share.qmd#sec-fair-data-sharing){.mark}).
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##### <i class="bi bi-list-check"></i> Your DMP will ask:
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- **How will you organize files** (naming conventions, folder structure, versioning)?
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- **Where will you store it** (locations, backups, access controls)?
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- **How will you ensure quality** (validation checks, error-handling)?
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- **How will you share outputs** (repositories, licenses, embargo periods)? See our lecture "[Why share data openly?](https://lmu-osc.github.io/training/data-management/open-data.html)" and [4.1. Data Sharing](04-preserve-and-share.qmd#sec-data-sharing){.mark}
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- **How will you share outputs** (repositories, licenses, embargo periods)? See our lecture "[Why share data openly?](https://lmu-osc.github.io/training/data-management/open-data.html)" and [4.1. FAIR Data Sharing](04-preserve-and-share.qmd#sec-fair-data-sharing){.mark}
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- **What constraints apply** (consent, anonymization, GDPR, data use agreements)? See our lecture "[Maintaining privacy with open data](https://lmu-osc.github.io/training/data-management/maintaining-privacy-with-open-data.html)", [1.2.3. Ethics](#sec-legal-requirements){.mark} and [2.3. Ethics & Privacy](02-collect-and-manage.qmd#sec-ethics-and-privacy){.mark}.
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<br>

training/research-cycle-handbook/03-analyze-and-collaborate.qmd

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@@ -439,7 +439,7 @@ Before publishing your project (see [4. Preserve & share](04-preserve-and-share.
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#### 3.1.4. Documentation
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As with all documentation, your project repository’s documentation should be written early - initially for your near-future self to support efficient re-engagement after interruptions, then revised for internal team review, and ultimately expanded and refined for public sharing (see [4.2. Code Publishing](04-preserve-and-share.qmd#sec-code-publishing){.mark}).
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As with all documentation, your project repository’s documentation should be written early - initially for your near-future self to support efficient re-engagement after interruptions, then revised for internal team review, and ultimately expanded and refined for public sharing (see [4.2. Open Source Code](04-preserve-and-share.qmd#sec-open-source-code){.mark}).
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<br>
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- **Create an analyses report with Quarto.** To make your results reproducible, you should provide the analysis code that creates the results of the manuscript with explanations for each of the steps. Quarto is an ideal tool for such purpose (see [Quarto tutorial](https://lmu-osc.github.io/introduction-to-Quarto/)). Your analysis report should contain your research question, data loading instructions, preprocessing steps, statistical procedures, tables and figures, session info and software versions (in the report itself or in your README).
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This will facilitate your own revisions, code-review by your team, **reproducibility checks** that some journals conduct as part of peer-review, and verification of results reproducibility by other researchers. The code repository can be published with simulated, synthetic, or real data, depending on the project, together with the respective article (see [4.2. Code Publishing](04-preserve-and-share.qmd#sec-code-publishing){.mark}).
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This will facilitate your own revisions, code-review by your team, **reproducibility checks** that some journals conduct as part of peer-review, and verification of results reproducibility by other researchers. The code repository can be published with simulated, synthetic, or real data, depending on the project, together with the respective article (see [4.2. Open Source Code](04-preserve-and-share.qmd#sec-open-source-code){.mark}).
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training/research-cycle-handbook/04-preserve-and-share.qmd

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<details class="orc-details-panel">
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<summary markdown="1"><i class="bi bi-database-up"></i>
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### Data Sharing {#sec-data-sharing}
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### FAIR Data Sharing {#sec-fair-data-sharing}
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</summary>
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<details class="orc-details-panel">
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<summary><i class="bi bi-file-code"></i>
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### Code Publishing {#sec-code-publishing}
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### Open Source Code {#sec-open-source-code}
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</summary>
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#### 4.2.4. Archiving & DOIs
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To publish you code on Zenodo, we recommend to<!-- these instructions contradict https://lmu-osc.github.io/code-publishing/archive.html -->
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To publish you code on Zenodo, we recommend to<!-- these instructions contradict https://lmu-osc.github.io/code-publishing/archive.html but see https://github.com/lmu-osc/code-publishing/issues/86 -->
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- **Push your clean repository to GitHub** (see GitHub tutorial).
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- **Create an account on [Zenodo](https://zenodo.org/).**
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### Materials Sharing {#sec-materials-sharing}
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### Open Materials {#sec-open-materials}
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</summary>
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Review entire git history
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Add simulated data if needed
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Document dependencies clearly -->
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::: {.orc-gradient-box}
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## <i class="bi bi-card-checklist"></i> Preserve & Share Checklist {.unnumbered}
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**Before sharing resources**
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- [ ] Complete metadata, README (with instructions), and documentation (e.g. data dictionary)
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- [ ] No sensitive information in any files to be shared
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- [ ] Data quality validated, code peer-reviewed, materials checked and cleaned
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- [ ] Results reproducible, following reporting guidelines, separated in preregistered vs exploratory
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- [ ] All authors have ORCID
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