-Yes, this dataset is the basis for a published article.
In “Related works”, a link to a github repo is provided and when going there it is stated in the README.
Yes, but it is not obvious. In “Related works”, a link to a github repo is provided and when going there it is stated in the README.
Yes.
As separate section before “Code availability” and the Reference section.
diff --git a/search.json b/search.json
index b1f4921..f7fa63b 100644
--- a/search.json
+++ b/search.json
@@ -26,7 +26,7 @@
"href": "publication.html#data-availability-statement",
"title": "1) Publication",
"section": "Data Availability Statement",
- "text": "Data Availability Statement\nA Data Availability Statement (as well as a Code Availability Statement) is a special section in an article that states whether the authors have made the evidence supporting their findings available, and if so, where readers may access it. They are usually placed somewhere towards the end of the article, mostly before the Reference section. As part of their commitment to supporting open research, some journals now require all manuscripts to include a Data Availability Statement in order to be accepted for publication. Even if a journal does not require such a statement, it is highly recommendable to include it and make transparent that the data underlying the article’s findings are available1!\n\n\n\n\n\n\nDouble-blind peer review process\n\n\n\nWhen submitting to a journal that uses a double-blind peer review process, it’s important to ensure that the information in the Data Availability Statement doesn’t compromise the anonymity of you or your co-authors. If there is information in your Data Availability Statement that could be used to identify the manuscript authors (e.g., by linking to a repository that reveals author information), make sure to ask the journal what they would like you to do2.\n\n\n\n\n\n\n\n\nTask 1.1:\n\n\n\n\nIs your dataset the basis for a published article?\nHow did you find out?\nIf so, does the article include a Data Availability Statement?\nWhere did you find it?\n\n\n\n\n\n\n\n\n\nSolution: Example 1 (~ 5 minutes)\n\n\n\n\n\n\nYes, this dataset is the basis for a published article.\nIn the meta data field “Related Publication”.\nYes, it does but without linking it to the data on Edmond. You should rather contact one coauthor without providing contact details.\nBefore the Appendices.\n\n\n\n\n\n\n\n\n\n\nSolution: Example 2 (~ 5 minutes)\n\n\n\n\n\n\nYes, this dataset is the basis for a published article.\nAs part of the title.\nYes.\nIn the very beginning following Abstract and Figures. However, no special section therefore not very intuitive to find.\n\n\n\n\n\n\n\n\n\n\nSolution: Example 3 (~ 5 minutes)\n\n\n\n\n\n\nYes, this dataset is the basis for a published article.\nIt is stated in the README.\nYes.\nIn the “Open Research” section before the Reference section.\n\n\n\n\n\n\n\n\n\n\nSolution: Example 4 (~ 5 minutes)\n\n\n\n\n\n\nYes, this dataset is the basis for a published article.\nIn “Related works”, a link to a github repo is provided and when going there it is stated in the README.\nYes.\nAs separate section before “Code availability” and the Reference section.",
+ "text": "Data Availability Statement\nA Data Availability Statement (as well as a Code Availability Statement) is a special section in an article that states whether the authors have made the evidence supporting their findings available, and if so, where readers may access it. They are usually placed somewhere towards the end of the article, mostly before the Reference section. As part of their commitment to supporting open research, some journals now require all manuscripts to include a Data Availability Statement in order to be accepted for publication. Even if a journal does not require such a statement, it is highly recommendable to include it and make transparent that the data underlying the article’s findings are available1!\n\n\n\n\n\n\nDouble-blind peer review process\n\n\n\nWhen submitting to a journal that uses a double-blind peer review process, it’s important to ensure that the information in the Data Availability Statement doesn’t compromise the anonymity of you or your co-authors. If there is information in your Data Availability Statement that could be used to identify the manuscript authors (e.g., by linking to a repository that reveals author information), make sure to ask the journal what they would like you to do2.\n\n\n\n\n\n\n\n\nTask 1.1:\n\n\n\n\nOnly looking at the dataset, would you be able to tell whether the dataset is the basis for a published article?\nIf so, does the article include a Data Availability Statement?\nWhere did you find it?\n\n\n\n\n\n\n\n\n\nSolution: Example 1 (~ 5 minutes)\n\n\n\n\n\n\nYes, there is a meta data field “Related Publication”.\nYes, it does but without linking it to the data on Edmond. You should rather contact one coauthor without providing contact details.\nBefore the Appendices.\n\n\n\n\n\n\n\n\n\n\nSolution: Example 2 (~ 5 minutes)\n\n\n\n\n\n\nYes, part of the title reveals it.\nYes.\nIn the very beginning following Abstract and Figures. However, no special section therefore not very intuitive to find.\n\n\n\n\n\n\n\n\n\n\nSolution: Example 3 (~ 5 minutes)\n\n\n\n\n\n\nYes, but it is not obvious. It is stated in the README.\nYes.\nIn the “Open Research” section before the Reference section.\n\n\n\n\n\n\n\n\n\n\nSolution: Example 4 (~ 5 minutes)\n\n\n\n\n\n\nYes, but it is not obvious. In “Related works”, a link to a github repo is provided and when going there it is stated in the README.\nYes.\nAs separate section before “Code availability” and the Reference section.",
"crumbs": [
"About",
"1) Publication"
@@ -125,7 +125,7 @@
"href": "index.html#how-to",
"title": "Welcome",
"section": "How to?",
- "text": "How to?\nSetting out this workshop, we quickly agreed that data management is best understood through learning by doing in a realistic setting: Imagine finding an article relevant to your research in a repository. Alongside the article, you find the associated data that you want to inspect further. Starting from this perspective, we look at publication aspects first and then move on to data documentation and organization.\nThe whole workshop evolves around four published datasets:\n\nExample 1: https://edmond.mpg.de/dataset.xhtml?persistentId=doi:10.17617/3.1STIJV\nExample 2: https://data.ub.uni-muenchen.de/288/\nExample 3: https://osf.io/6p9bf/\nExample 4: https://zenodo.org/records/10650333\n\nIt is your job to investigate one of these datasets with a special focus on publication, documentation and data organization aspects. We will conclude with an introduction to data management plans, a helpful planning tool to comply with the FAIR principles. In this section, we will also introduce important aspects of data storage.\nThe topics are accompanied by distinct boxes that are color-coded for their content:\n\n\n\n\n\n\nOrange boxes contain information crucial for that topic\n\n\n\n\n\n\n\n\n\n\n\n\nBlue boxes contain excursions to related topics\n\n\n\n\n\n\n\n\n\n\n\n\nGreen boxes contain hands-on exercises\n\n\n\n\n\n\n\n\n\n\n\n\nRed boxes contain the solutions and are collapsed\n\n\n\n\n\nOnly open the box if you want to see the solution!\n\n\n\nWe recommend that you look at the hands-on exercises first and see whether you already know their solutions. If things are unclear, you may return to the text anytime, but be aware that it is not necessary (and time will probably not permit) to read every paragraph and every box very carefully. The materials will, however, remain available, so you can always go back and reread more carefully!",
+ "text": "How to?\nSetting out this workshop, we quickly agreed that data management is best understood through learning by doing in a realistic setting: Imagine finding an article relevant to your research in a repository. Alongside the article, you find the associated data that you want to inspect further. Starting from this perspective, we look at publication aspects first and then move on to data documentation and organization.\nThe whole workshop evolves around four published articles and their datasets:\n\nExample 1: https://edmond.mpg.de/dataset.xhtml?persistentId=doi:10.17617/3.1STIJV\nExample 2: https://data.ub.uni-muenchen.de/288/\nExample 3: https://osf.io/6p9bf/\nExample 4: https://zenodo.org/records/10650333\n\nIt is your job to investigate one of these datasets with a special focus on publication, documentation and data organization aspects. We will conclude with an introduction to data management plans, a helpful planning tool to comply with the FAIR principles. In this section, we will also introduce important aspects of data storage.\nThe topics are accompanied by distinct boxes that are color-coded for their content:\n\n\n\n\n\n\nOrange boxes contain information crucial for that topic\n\n\n\n\n\n\n\n\n\n\n\n\nBlue boxes contain excursions to related topics\n\n\n\n\n\n\n\n\n\n\n\n\nGreen boxes contain hands-on exercises\n\n\n\n\n\n\n\n\n\n\n\n\nRed boxes contain the solutions and are collapsed\n\n\n\n\n\nOnly open the box if you want to see the solution!\n\n\n\nWe recommend that you look at the hands-on exercises first and see whether you already know their solutions. If things are unclear, you may return to the text anytime, but be aware that it is not necessary (and time will probably not permit) to read every paragraph and every box very carefully. The materials will, however, remain available, so you can always go back and reread more carefully!",
"crumbs": [
"About",
"Welcome"
diff --git a/sitemap.xml b/sitemap.xml
index ee1c7de..97aa99a 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -2,11 +2,11 @@
https://MPDL.github.io/FAIR-Data-Management/publication.html
- 2024-10-16T13:07:55.338Z
+ 2024-10-31T13:18:56.292Z
https://MPDL.github.io/FAIR-Data-Management/index.html
- 2024-10-16T13:07:55.321Z
+ 2024-10-31T13:18:56.290Z
https://MPDL.github.io/FAIR-Data-Management/Example3_READMETemplate.html