update readme

Author: lsteinmann

README.md

@@ -11,31 +11,32 @@ Converting date ranges into dating 'steps' eases the visualization of changes in
 
 A rather common problem in archaeology is the fuzzyness of dates assigned to objects. If one wants to visualize overall changes in - let's say - pottery consumption, bar charts often fall short in that regard. If, e.g., the Phases a -- f are employed, then some of the objects can usually be dated to a, c, and f, as an example, but others will by classified as "a to c" or "b to c". But how can these data still be used for examining changes in a large set of objects without completely disregarding the information added by providing multiple phases for one object?
 
-This package proposes a method to prepare archaeological data for the visualization using density plots. An example is shown in /vignettes/. Density plots are easy to understand and are usually aesthetically pleasing. They do omit a some information, such as individual counts, that bar histograms can communicate better. On the other hand, ranges can be incorporated into the visualization as well to regard the variety of timespans archaeological objects may be dated to.
+This package proposes implements the concepts of aoristic analysis to prepare archaeological data for the visualization using density plots. An example is shown in the vignettes, which can be found at
+
+    browseVignettes("datplot")
+
+after installing the package, or on GitHub in the /vignettes/ directory. Density plots are easy to understand and are usually aesthetically pleasing. They do omit a some information, such as individual counts, that bar histograms can communicate better. On the other hand, ranges can be incorporated into the visualization as well to regard the variety of timespans archaeological objects may be dated to.
 
 I imagine this to be mostly useful for surveys and other analysis aimed at the longue duree. 
 
 ![Attic Pottery from BAPD by Date](inst/extdata/demo_readme.png "Attic Pottery from BAPD by Date")
 
-Installation 
--------
-'datplot' can be installed from GitHub directly with devtools:
 
-    devtools::install_github("lsteinmann/datplot")
 
 Recommendation
 -------
-People interested in employing this method should also consider taking a look at [ISAAKiel's package aoristAAR](https://github.com/ISAAKiel/aoristAAR/). 
+People interested in employing this method should also consider taking a look at [ISAAKiel's package aoristAAR](https://github.com/ISAAKiel/aoristAAR/), or at [archSeries](github.com/davidcorton/archSeries), [tabula](github.com/nfrerebeau/tabula/) and [rtefact](github.com/ahb108/rtefact)). 
+
 
 Installation 
 -------
-'datplot' can be installed from GitHub directly with devtools:
+'datplot' is not currently on CRAN. It can be installed from GitHub with devtools:
 
     devtools::install_github("lsteinmann/datplot")
 
-Recommendation
--------
-People interested in employing this method should also consider taking a look at [ISAAKiel's package aoristAAR](https://github.com/ISAAKiel/aoristAAR/). 
+Or via downloading the latest release and installing from the file: 
+
+    install_local(path = "../datplot_0.2.4.tar.gz")
 
 Contact
 -------

vignettes/data_preparation.Rmd

@@ -394,20 +394,13 @@ summary(inscr_clean)
 
 # datplot
 
-We can now begin using the **datplot**-package. Since `datplot` is not on CRAN, it is necessary to either install it from our github repository directly or download the source file and install it. For this, R needs the `devtools`-package to be installed.
+We can now begin using the **datplot**-package... 
 
 ```{r eval = FALSE}
-library(devtools)
-# either
-install_github("lsteinmann/datplot") # (redacted)
-# or 
-install_local(path = "../datplot_x.x.x.tar.gz")
+library(datplot)
 ```
 
-
-# The Output of `datsteps()`
-
-Now we can actually try to use `datsteps()`, first with a `stepsize` of 25 years[^3]:
+...and can actually try to use `datsteps()`, first with a `stepsize` of 25 years[^3]:
 
 ```{r warning=TRUE, out.lines = 13}
 inscr_steps <- inscr_clean %>%