\documentclass{article}

\usepackage[utf8]{inputenc}
\usepackage{Sweave}

\title{Working title: Data Descriptor for HMC Data Set}
\author{Angelica Henestrosa}
\affiliation{Leibniz-Institut für Wissensmedien, T\"ubingen}

\begin{document}
%\SweaveOpts{concordance=TRUE}

\maketitle

\begin{abstract}
  tbd
  % Should not exceed 170 words
\end{abstract}

\section{Background and Summary}

% Overview of Dataset
%
% * Provide a clear overview of the dataset
% * Explain the motivation for creating the dataset
% * Outline the potential reuse value of the dataset
%
% Previous Publications
%
% * Cite any previous publications that utilized these data, in whole or in part
% * Briefly summarize the findings or contributions of those publications
%
% Introductions for Articles and Comments
%
% * Explain the purpose of the work performed
% * Describe the value that the work adds to the field
%
% Citing Prior Art
%
% * Include citations of relevant datasets or outputs in the field for reader
%   interest
% * Avoid subjective claims regarding novelty, impact, or utility


\section{Methods}

% Description of Data Creation
%
% * Describe the steps or procedures used to create the data.
% * Include full descriptions of the experimental design.
% * Detail the data acquisition methods.
% * Explain any computational processing involved.
%
% Input Data for Secondary Datasets
%
% * Provide detailed descriptions of all input data.
% * Use a sub-heading such as 'Input Data' if desired.
% * Ensure details allow readers to source the exact data used (avoid non-specific
%   URLs or homepages).
% * For continuously updated input data, include version numbers or search terms
%   used.
% * Reference input datasets with DOIs or formal metadata using the appropriate
%   citation format.
% * Embed URLs in the text for datasets without formal metadata.
%
% Focus on Practical Tasks
%
% * Avoid including general results or analyses in this section.
% * If data have been analyzed or published elsewhere, cite the experimental
%   methods instead of restating them.
% * Focus on documenting practical tasks and technical or processing steps.
%
% Scientific Process Description
%
% * Describe the full scientific process for generating the output or study.
% * Limit discussion of operational aspects like software development or project
%   management unless relevant to the science.
%
% Consortia and Multi-Stakeholder Projects
%
% * Be mindful of scientific relevance and reader interest when describing
%   administration, management, and funding.
% * State funder details as a practical requirement but avoid excessive focus on
%   organization unless relevant to the science.


\section{Data Records}

% * Explain what the dataset contains.
% * Specify the repository where the dataset is stored.
% * Provide an overview of the data files and their formats.
% * Describe the folder structure of the dataset.
% * Cite each external dataset using the appropriate data citation format.
% * Limit extensive summary statistics to less than half a page.
% * Include 1-2 tables or figures if necessary, but avoid summarizing data that
%   can be generated from the dataset.

\section{Technical Validation}

% * Describe the experiments, analyses, or checks performed to support the
%   technical quality of the dataset.
% * Include any supporting figures and tables as needed.

\section{Usage Notes (optional)}

% * Provide optional information that may assist other researchers in reusing the
%   data.
% * Include additional technical notes on how to access or process the data.
% * Avoid using this section for conclusions, general selling points, or worked
%   case studies.

\section{Code Availability}

% * Include a subheading titled "Code Availability" in the publication.
% * Indicate whether custom code can be accessed.
% * Provide details on how to access the custom code, including any restrictions
% * Include information on the versions of any software used, if relevant.
% * Specify any particular variables or parameters used to generate, test, or
%   process the dataset, if not included in the Methods.
% * Place the code availability statement at the end of the manuscript,
%   immediately before the references.
% * If no custom code has been used, include a statement confirming this.

\section*{References}

\section*{Author Contributions}

\section*{Competing Interests}

\section*{Acknowledgements}


Hier ist ein R-Chunk:

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x <- rnorm(100)
summary(x)
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\end{document}