Develop and use the dmdScheme

dmdScheme_0.9.9

Rainer M Krug Rainer.Krug@uzh.ch

2020-06-12

Using the dmdScheme

The functionality for using the dmdScheme is available either via the online app (which is identical to being housed at an inhouse shiny server), the local running app, or via the R command line. The simplest method is using the online app, as no additional software needs to be installed locally. To be able to use the dmdScheme functionality locally, either via the app or via the R command line, it is necessary to install R [@RCoreTeam2019] and the dmdScheme package [@Krug2019a] in R.

In the following section, I will go through the different stages of using the dmdScheme web app, a local app or from the R prompt. The detailed commands which have to be used can be found in Figure 1.

**Figure 1**: Workflow of using `dmdScheme` (A) via the web app, (B) via the app locally, (C) via the R prompt. Square boxes indicate steps which are not common to all three, rounded boxes indicate steps identical to the different ways, although how they are executed can differ.**Figure 1**: Workflow of using `dmdScheme` (A) via the web app, (B) via the app locally, (C) via the R prompt. Square boxes indicate steps which are not common to all three, rounded boxes indicate steps identical to the different ways, although how they are executed can differ.**Figure 1**: Workflow of using `dmdScheme` (A) via the web app, (B) via the app locally, (C) via the R prompt. Square boxes indicate steps which are not common to all three, rounded boxes indicate steps identical to the different ways, although how they are executed can differ.

Figure 1: Workflow of using dmdScheme (A) via the web app, (B) via the app locally, (C) via the R prompt. Square boxes indicate steps which are not common to all three, rounded boxes indicate steps identical to the different ways, although how they are executed can differ.

Preparation

The app (Figure 2) can be accessed either via the internet as a web app at https://rmkrug.shinyapps.io/dmd_app/, or locally. To run it locally, you need R installed and the dmdScheme package installed, preferably from CRAN. After loading the dmdScheme package, you can start the app locally by running run_app() at the R prompt. After these steps, the usage of the two apps is identical.

When using the dmdScheme from the command line, the initial setup is the same as running the app locally, only that it is not necessary to start the app.

**Figure 2**: Screenshot of the dmdScheme app.

Figure 2: Screenshot of the dmdScheme app.

Select scheme

The package dmdScheme does not come with a specific scheme, and installs upon loading a generic dmdScheme from the dmdScheme scheme repository at https://github.com/Exp-Micro-Ecol-Hub/dmdSchemeRepository. In nearly all circumstances, a specific scheme needs to be installed, together with the accompanying R package. In the app, this is done via selecting a theme in the section “Available dmdSchemes”. This list is generated automatically upon starting of the app from the schemes available in the scheme repository. The selection of the scheme will download the scheme definition package, install any accompanying R package as specified in the scheme definition package, load the accompanying R package, and activate the scheme definition.

To do this from the R prompt, one has do these steps manually and install the scheme, install the accompanying R package, load the accompanying R package, and activate the scheme itself (see Figure 1 C for the commands).

Download new scheme

The spreadsheet to enter the metadata can be obtained from the app via the “Empty scheme spreadsheet” bottom. This will download an .xlsx spreadsheet containing the definition of the scheme and fields which need to be filled in.

In R, the spreadsheet can be obtained by using the open_new_spreadsheet() command.

Figure 3 shows two screenshots of the spreadsheet as opened in Excel.

**Figure 3**: Some example tabs from the `emeScheme` spreadsheet. The first to contains bibliometric metadata modelled along the requirements by DataCite and the authors in the second tab. The third one contains metadata about the Species used in the experiment. The complete spreadsheet can be found in the supplemental material `emeScheme.xlsx`.