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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# requal
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[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[](https://github.com/RE-QDA/requal/actions)
[](https://github.com/RE-QDA/requal/actions/workflows/R-CMD-check.yaml)
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The goal of `requal` is to provide reproducibility support for qualitative coding.
```{r screenshot, echo=FALSE}
knitr::include_graphics("https://owncloud.cesnet.cz/index.php/s/mQcxC998RC6qwVP/download")
```
## Installation
### Prerequisites
To use `requal`, you need to have the [R language](https://www.r-project.org) installed and running on your machine. You can download and install R from [here](https://cloud.r-project.org)). You will also need a web browser with JavaScript support (i.e. any of the standard issue browsers like Firefox, Chrome, or Safari).
### Package
You can install `requal` from [GitHub](https://github.com/) by following these steps (assuming you have R installed on your machine):
1. Download the current release of `requal` from [Releases](https://github.com/RE-QDA/requal/releases).
2. Install the `remotes` package by running `install.packages("remotes")` command in R console.
3. Install the `requal` package by running `remotes::install_local(file.choose())` and selecting the downloaded release file on your hard-drive.
#### Development version
The development version contains the latest features, but might be less stable than a [released version](https://github.com/RE-QDA/requal/releases).
You can install the development version of `requal` from [GitHub](https://github.com/) by running this code in R:
```
install.packages("devtools")
devtools::install_github("RE-QDA/requal")
```
## Usage
The `requal` app can be launched from the R console with the following command:
```{r example, eval=FALSE}
requal::run_app(options = list("launch.browser"))
```
On the first launch of the app, use the "Create" menu to set up a new project by providing a name and selecting a folder for your project. The app will create an SQLite database file with the `.requal` extension and start up the project.
`requal` is a `shiny` application that runs in your browser and provides basic functionality for annotating documents in plain text with user-defined codes. The annotated text segments can be filtered and exported. More functions are coming up.
### Collaborative usage
`requal` is designed with reproducibility, openness, and transparency in mind, and these values are most evident when it's used collaboratively. You can achieve this by self-hosting `requal` on your own server. A server instance of `requal` can support multiple users and offers fine-grained permission settings, making it easier to form diverse teams and collaborate in real time. With `requal`, you can discuss codes, evaluate agreement on codes, and estimate the sensitivity of coding to the attributes of your team members.
However, setting up a server instance is not a simple task. It requires a basic level of system administration experience. If you need assistance, the IT department at your institution should be able to help set up an `requal` server instance by following these [instructions](https://github.com/RE-QDA/requal/wiki/Server-setup). To get a sense of how `requal` operates in server mode, take a look at the public demo available on the [requal project website](https://requal.fsv.cuni.cz/).
>NOTE: It is crucial to prioritize __data security__ when hosting your `requal` instance publicly over the internet. At the very least, enabling the TLS protocol is a necessary precaution. However, be aware that this measure alone will not fully protect you from knowledgeable attackers. Consequently, it is important that you only analyze public, GDPR-compliant, and non-confidential data via `requal` in server mode. If you intend to use `requal` for collaborative work involving confidential or sensitive data, ensure this is done behind adequate firewalls or on internal networks established in secure locations. Always consult with your data stewards and/or research ethics committee to determine the appropriate level of security control for your dataset. In the future, we plan to provide support for data de-identification. This will allow you to perform de-identification locally and collaboratively analyze the de-identified dataset online.
## Acknowledgement
The application development has been supported by The Technology Agency of the Czech Republic, project n. TL05000054, and CLS INFRA Fellowship Programme.