The required library for this plot are ggplot2, dplyr, knitr, stringr, rmarkdown and data.table.

Populate some dummy datasets.

data = data.frame(
        'l1' = sample(LETTERS[1:4], 20, T), 
        'l2' = sample(LETTERS[5:10], 20, T),
        'l3' = sample(LETTERS[15:18], 20, T), 
        'cluster' = sample(1:4, 20, T))

# a helper function to convert an object name into literal string
var_to_name <- function(x){
  deparse(substitute(x))
}

# print out the data frame
kable(data, caption = var_to_name(data))

data

l1	l2	l3	cluster
B	G	Q	1
B	H	Q	1
B	E	P	3
A	F	Q	4
D	J	O	3
C	E	P	4
A	J	O	4
D	J	O	3
C	G	O	2
B	J	O	4
A	E	O	4
C	I	R	2
B	H	Q	4
D	F	R	1
A	E	P	4
B	I	R	2
C	I	P	2
D	G	Q	1
D	H	R	1
B	G	P	1

Next we do some massaging on the datasets

# generate id for each row so that we can group the row in line plot
data$id <- seq(nrow(data))

# melt the data frame by keeping id and cluster only
data.melt <- melt(data, id.vars = c('id', 'cluster'))

## Warning: attributes are not identical across measure variables; they will
## be dropped

# the value column is actually the label value in each column, so we rename it as 'label'
names(data.melt)[grepl('value', names(data.melt), fixed = T) %>% which] = 'label'

# change the label to numeric type so that we can plot it in y-axis, it would be our data label
data.melt$value <- as.factor(data.melt$label) %>% as.numeric

dt <- data.table(data.melt)

dt[, variable.x:=as.factor(variable)]

kable(head(dt), caption = var_to_name(dt))

dt

id	cluster	variable	label	value	variable.x
1	1	l1	B	2	l1
2	1	l1	B	2	l1
3	3	l1	B	2	l1
4	4	l1	A	1	l1
5	3	l1	D	4	l1
6	4	l1	C	3	l1

# scale the value group by its column name and use a new column 'scaled' to store it
dt[, scaled.y:=scale(value), variable]

# create the dataset for text labelling
data.label <- dt[, .(variable.x, label, scaled.y)] %>% distinct

Start to plot the graph.

g = ggplot(dt, aes(x = variable.x, y = scaled.y)) + geom_point(
      aes(color = as.factor(cluster))) + geom_line(aes(group = id, color = as.factor(cluster)))

# vectorize str_wrap function so that we can wrap the text in label column if its too long
wraptxt <- Vectorize(str_wrap, vectorize.args = 'string')

# plot the label
g1 = g + geom_text(data = data.label, aes(x = variable.x, y = scaled.y, label = wraptxt(label, width = 10)), 
                                          family = 'Panton', hjust = 'left', nudge_x = .02, size = 3)

g1 + scale_color_discrete(name = 'cluster') + theme_bw() + theme(legend.key = element_rect(color = NA))