02_essay-example/essay-basic.tex

\hypertarget{introduction}{%
\section{Introduction}\label{introduction}}

The preparation of documents always takes our minds to relate the usage
of specialized software like Microsoft-Word, Word-Pad, Pages,
Open-office, and so on. However, many years ago, the preparation of
documents, used to be more relaxed and faster; the plain-text fashion.
Plain-text documents are files with no format nor specialized
information. Instead, plain documents are only text. But, why plain-text
documents are so crucial for the academic area? Why these files remain
useful? And how can we use them to create high-quality documents? Well,
let's start by explaining some special kinds of documents based in
plain-text files; the \emph{Markdown files}.

\hypertarget{formats-for-academic-documents}{%
\section{Formats for academic
documents}\label{formats-for-academic-documents}}

The Markdown format was initially developed by John Gruber in
collaboration with Aaron Swartz, to simplify the writing of HTML.
Instead of coding a file in HTML syntax, the content of a document is
written in \textbf{plain text} and denote with \emph{simple tags the
final formatting}. Subsequently, the MD (Markdown) files are parsed to
generate the final HTML document. With this concept, the source file
remains easily readable, and the \textbf{author can focus on the
contents rather than formatting}.

\hypertarget{why-md-files-are-important-in-academia}{%
\subsection{Why MD files are important in
academia?}\label{why-md-files-are-important-in-academia}}

Despite its original focus on the web, the MD format has been proven to
be great for academic writing. In particular,
\href{http://pandoc.org/}{pandoc-flavored MD} adds several extensions
that facilitate the authoring of academic documents and their conversion
into multiple output formats. The only requirement is to learn the
basics of MD-syntax and install the \emph{pandoc} application to convert
the files. Then, the output file can be defined by using some parameters
in the input file to create a new different output document. Therefore,
it is possible to create tables, bibliography citations, include
figures, code sections, special symbols and characters, and the most
important only using a plain-text file.

\hypertarget{why-these-files-remain-useful-now}{%
\subsection{Why these files remain useful
now?}\label{why-these-files-remain-useful-now}}

A single word can answer this question: Reproducibility. An MD file can
be compiled\ldots, yes compiled; we are talking about programming,
\ldots{} compiled in a different computer, if the pandoc engine is
installed on it. And guess what? We can add one more word: traceability.
Yes, we can follow how a file is changing its content and support old
and new versions. -Hey, check my paper please, this is only a simple
plain text, and you will not have problems of compatibility-, right? In
most of the cases, there should no be a problem

\hypertarget{how-can-we-use-them-to-create-high-quality-documents}{%
\subsection{How can we use them to create high-quality
documents?}\label{how-can-we-use-them-to-create-high-quality-documents}}

By using pandoc there is possible to produce `.tex' files and then
produce a PDF-formated document. When the TeX file is generated, the
document's quality can be improved. Even more, the TeX file can be
basically modified to create an entirely different document by selecting
a new `document class'. Nevertheless, from my point of view, the MD
files can be used for basic and short documents (proposal, drafts,
guides, unformatted articles). In contrast, for more complex documents
(thesis, books, formated-articles), it is better to use LaTeX.

\hypertarget{whats-next}{%
\section{Whats next?}\label{whats-next}}

Pandoc is useful for creating basic and short documents; also is a first
approach to use more powerful engines like pdflatex and xelatex. Also,
the MD files are just plain text files and can be used for controlling
versions. Actually, the MD file's process is commonly used by other IDE
systems like r-studio to create complete environments for data science
reproducibility.