[PLEASE DELETE] This document is a data description template (README.txt) that enables the reader of your data package to understand and reuse your data. Ideally, it should also contain information on the reliability and quality of the data.
Please keep in mind that your data package should be a self-contained unit that can be understood and reused independently of additional materials (e.g., academic paper). As a generic research data repository, KonDATA (RADAR) only provides a basic set of metadata fields to register a Digital Object Identifier (DOI) for your dataset at DataCite. Therefore, this README.txt file is the place where discipline-specific metadata should be recorded.
Aligning your data and metadata to the FAIR principles (https://www.go-fair.org/fair-principles/) will significantly increase the findability, accessibility, interoperability and reusability of your data. It also increases the visibility of both your data and yourself as an  academic.
Below you will find a list of important criteria that should help you create the README.txt. Text passages in “quotation marks” serve as placeholders and should be deleted before publication. [PLEASE DELETE]



“THE TITLE OF YOUR DATA PACKAGE”

DESCRIPTION OF THE DATA PACKAGE
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-	What kind of data does your data package contain?
-	Is the data package part of a parent data package (a data package one hierarchy level higher)?
-	Is the data used in academic publications? (If yes, which one(s)?)
-	What was the academic context from which your data emerged?
-	What are the data types and data formats (e.g. image data, text data, measurement data) in the package
-	What are place and period of data collection?
-	What is the structure of the data and their relationships to each other (e.g., how is the data structured and what does it contain; language; if there are several data sets: how do they relate to each other and what data is needed to interpret the data beyond this package correctly)?

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STUDIED OBJECT(s)
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-	What was investigated (e.g., soil, humans, literature, etc.)?
-	How did you take your samples/collect your data (e.g., grab samples, time averaged samples, random samples, data collection, etc.)?
-	How did you prepare your samples (e.g., extraction, etc.)?
-	If applicable: What treatments have you carried out on your samples (e.g., positive control, negative control, solvent control, etc.)?
-	Please provide all information on the studied object(s) that would be needed to recreate your data.
-	If applicable, you can insert a citation of the respective section of an academic publication here.

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METHOD(s)
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-	What academic method did you use to examine your studied object (e.g., interview, microscope, mass spectrometry, used hard and software, etc.)?
-	How did you process or analyse your data (e.g., calculations, simulations, statistics, used hard and software, etc.)?
-	Please provide all information on the method(s) that would be needed to recreate your data.
-	If applicable, you can insert a citation of the respective section of an academic publication here.

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ADDITIONAL INFORMATION
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-	Please add information that is relevant to understand, reuse or recreate your data (meaning of variables mentioned in your data files, etc.)
-	Did you use discipline-specific ontologies?
-	Information on access, terms of use and confidentiality (e.g., anonymization of the data, information on data protection, etc.)
-	Secondary data sources (citation according to the source!)

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