Everybody who is author of a data set suitable for pmird (see next section) and has the agreement of any co-authors to share the data and to make them co-authors can contribute data.
Regarding sample types, different organic materials, ranging from peat to peat forming vegetation, litter, and dissolved organic matter are suitable.
The minimum data available has to be a mid infrared spectra (MIR) for each sample, whereby this could be FTIR and ATR spectra.
In addition to this, I am interested in any accessory data available, for example: peat ages, radionucleide activities, element contents, descriptors of organic fractions (e.g. polysaccharide content), bulk density, loss on ignition, pore volume, … . A full list of variables can be found in the data dictionary.
All data have to be licensed under a CC-BY 4.0 license (or comparative) because only under the conditions of this license, it is possible to use the data in a data compendium and to openly share the data compendium.
Go to the project’s GitHub repository and download the zip folder data_template.zip. This folder contains a set of csv/docx templates where you can enter your data and the data policy agreement for pmird. A detailed manual to fill in the data is provided below. Note that any data contributor must agree to the authorship guidelines for the data compendium
If you have questions, don’t hesitate to contact me!
If you submit your data before January 31, 2021, you send a request to become co-author of the data paper and you agree to the authorship guidelines for the data paper, you will not only of the data compendium, but also of the corresponding data paper.
For organising the data collection and developing the technical infrastructure, as well as providing some data, and because I need to include it into my PhD, I will be the first author. My supervisors will become last authors. All other contributors will be sorted in alphabetical order.
I will draft the paper and consider your data description during this process. Finally, I will request you to review the manuscript before submission.
Go to the project’s GitHub repository and download the zip folder data_template.zip. This folder contains a detailed manual and a set of csv/docx templates where you can enter your data.
The zip folder contains the following csv/docx/pdf files:
| file | description |
|---|---|
| general_info.csv | data set title, license, URL (if from a web source), DOI (if available), version (if available), year of creation, a statement how to cite the data, acknowledgments that have to be considered, keywords, abstract. |
| authors.csv | author information (names, affiliation, contact author). |
| description.docx | textual description of the site, methods, experimental manipulations, … |
| site_info.csv | Information on sampling sites (name, coordinates). |
| sample_data.csv | Additional data on peat properties (for example peat age, N content, …). |
| sample_mir.csv | The mid infrared spectra (MIR/ATR/FTIR). |
| sample_mir_error.csv | Optionally: infrared spectra errors. |
| data_policy.pdf | The data policy agreement for this project. This is required since we collect your name, mail address and affiliation. |
Fill in the data policy agreement with your personal data. This is needed since we store your name and affiliation to generate the author list for the data compendium and to contact you. Note that as a data contributor, you also agree to the authorship guidelines for the data compendium.
Fill in the data! For the csv files, there is a detailed description of what the fields mean, what to enter and which measurement units to use (data dictionary):
Fill in general information regarding the data set you want to submit (general_info.csv).
Fill in information regarding all co-authors (authors.csv). This data will be used to create the author list and to contact each co-author.
Provide a description on the sample and data collection, handling and processing (description.docx). description.docx contains a detailed list of information you may provide. Please describe as many details as possible. The more information you provide the more useful the data will be in the future! You may also add figures, graphs, maps, … .
Enter data on the sampling sites where samples were collected (site_info.csv).
Enter metadata and measurement data on the samples that are not mid infrared spectra (sample_data.csv). Don’t be scared by the many fields, I just want to encourage to provide as much information as possible. If you don’t have data for a specific field, skip it. For example if you want to enter a present aboveground vegetation sample, you probably will not enter any sampling depth or radiocarbon dating data. If you have data that does not fit in any field, you can provide it in an additional csv file with a separate description (for example paleovegetation data that is not considered in the template file).
Enter your mid infrared spectra (sample_mir.csv). There is only one field in the csv file (wavenumber) where you should enter the wavenumber values for the spectra.
For each sample for which you have a mid infrared spectra, use the value in the field “sample_id” from sample_data.csv as column name and append a column for each mid infrared spectrum you want to add.
I prefer raw data that has not been baseline corrected yet. If your data has been preprocessed, describe this in detail in description.docx.
If you have spetra with differing wavenumber values you can copy sample_mir.csv to sample_mir2.csv and enter the non-matching data in the duplicate. If this happens another time, create another copy.
If you have raw data in a specific file format, please put this in a folder “mir” and include this in the final zip folder you send me (see below).
Enter data on errors of the mid infrared spectra intensity values (sample_mir_error.csv). The procedure is the same as for sample_mir.csv. If you have information on wavenumber errors, too, you can send this in a separate file (there is no template for this).
Put all files created or collected during steps 3.a to 3.g into a zip archive and send it to henning.teickner@uni-muenster.de. In the e-mail, indicate if you want to be also co-author of the data paper or only the data compendium. Make sure that you agree to the authorship guidelines for the data paper if you want to become co-author of it. That’s it!