How to visualise multidimensional categorical data with additional time dimension I am trying to visualize a dataset that registers the career of people in an organisation and their backgrounds before starting in that particular organisation. I 'd like to show how individuals are positioned in the space based on their background areas and show the evolution through time in the beginning of each decade. I have seen the answers here but my data are much more categorical and also, ideally, I 'd like to display all three background categories (see below) at the same time

A sample of my data follows:

Person  BkgArea1    BkgArea2    BkgArea3    TotalSize   YearFrom    YearTo
P1  3   2   0   5   1959    1965
P2  0   2   1   3   1959    1967
P3  3   0   2   5   1991    2008
P4  3   0   0   3   1959    1980
P5  3   0   0   3   1981    1998
P6  0   2   1   3   2006    2014
P7  2   2   2   6   2008    2014
P8  0   0   3   3   1991    1996
P9  3   3   1   7   1966    1972
P10 3   0   2   5   1975    1991
P11 3   2   0   5   1998    2013
P12 3   1   0   4   2004    2013
P13 0   2   0   2   1998    2010
P14 0   3   0   3   2003    2008
P15 1   2   3   6   1998    2008
P16 3   0   2   5   1973    1977
P17 1   3   0   4   1998    2012
P18 3   0   2   5   1996    2008
P19 0   3   1   4   1998    2011
P20 3   2   0   5   1998    2006
P21 3   0   0   3   1986    1989
P22 0   3   2   5   1996    2014
P23 3   2   3   8   1959    1976
P24 3   2   0   5   1998    2001
P25 0   0   3   3   1998    2011
P26 3   3   2   8   1965    1992
P27 2   3   2   7   2010    2014
P28 3   2   2   7   1986    1998
P29 3   3   0   6   2013    2014
P30 0   3   2   5   1976    1977
P31 3   3   0   6   1986    1987
P32 0   2   2   4   1980    1990
P33 3   0   2   5   1975    1986
P34 0   3   3   6   1977    1991
P35 3   2   2   7   1963    1974
P36 3   3   0   6   1998    2001
P37 0   2   3   5   1998    2004
P38 0   3   2   5   1974    1980
P39 3   2   3   8   1989    1998
P40 0   3   3   6   1991    1998
P41 0   1   2   3   1998    2001
P42 0   2   0   2   2003    2012
P43 3   3   3   9   1973    1986
P44 3   2   1   6   1978    1986
P45 0   2   0   2   2002    2012
P46 0   3   3   6   1982    1988
P47 0   3   0   3   1992    1998
P48 3   2   2   7   1998    2004
P49 2   2   0   4   2012    2014
P50 3   2   2   7   2008    2014


The values in columns BkgArea1-3 are essentially categorical values, that indicate the strength of an individual in a specific category. It is thus
0: no background, 1: weak background, 2: average background, 3: strong background. The TotalSize column is the sum of the scores of the individuals

The initial idea was to assign basic colors to BkgAreas 1-3, namely Red, Green, Blue, and then colour the individuals according to the mixture of their backgrounds, weighing each color with the strength of each area, i.e. 2/3 * Red if an individual has score 2 in BkgArea1, etc. I then tried to display the area as 3d scatter plot but it looks very complicated and hard to interpret.

I also tried to apply Multiple Correspondence Analysis but I haven't got very satisfying results. Do you have any ideas as of how to represent this dataset?

UPDATE

After people having posted various useful answers but not 100% covering the representation needs, I summarize what I would like to achieve:


Group/cluster the individuals according to their backgrounds and relative to the three background areas. if someone has scores in more than one of them, they should be displayed somewhere in the middle.
Show, visually if possible, the number of individuals and the TotalSize of the individuals. This could be a cloud 
Show the development of the organization. I think this might be easy to do with stacked column charts or histograms


RadViz can be a method to solve 1 and 2, or at least I am inclined toward that representation. The problem in my data is that individuals under RadViz will be placed at very specific points so we lose somewhat the track of how many individuals have specific background characteristics
This is something you can get in Tableau in 10 minutes.



What you need is year binning, skills weights and length(year_end - year_start) for Gannt chart: