Control elements on the page
• Map select list – lets you select a map for the basic or primary layer, it is always being selected for any sort of map.
• Question 1 select list – lets you select a variable from the survey data for the primary map layer.
• Transparent map select list – lets you select a map for the secondary transparent or semi-transparent layer, that should be selected either for visualization of borders of some larger than for the first map entity, or for visualization of the second variable.
• Question 2 select list – lets you select a variable from the survey data for the secondary map layer for visualizing of two variables at once.
• Use approximation checkbox – is available only if the Rayon option from the basic map is selected. If it is checked – all rayons where survey was not conducted will have values that equal to an average value for an oblast, otherwise all such rayons will have 0 and no color.
• Use pattern radio button – if checked produces hatching for coloring the secondary transparent layer.
• Use colour radio button – if checked produces half-transparent color for coloring the second layer.
• Show button – press this to generate a map.
• Export to Excel – press this link to save Table of values for the selected regional cut to Excel spreadsheet.
• Save map – press this link to save a map as the image with the opportunity to edit it in the programs-editors.
• Hover over a region area – shows the frequency for the ground map if only ground map is selected, and for the Transparent map if selected.
General look of the map presents four main tabs 2013, 2015, Both and Change. Correspondingly, one can obtain the visualization of the data of 2013, 2015 surveys, questions that were asked only in one of the surveys in one map – Both tab, and to visualization of the change in one question in 2013-2015 period.
The DMHRU allows to visualize one and two variables at time. Second variable can be visualized as a semi-transparent colour or pattern. Second variable could be selected from the same data set (2013 or 2015 tabs) and one question could be selected from two different dataset (Both tab). Below there the examples of the maps and the types of explanations that can be obtained with the help of DMHRU.
Examples of building maps and the types of inferences they allow to make
Example 1
To visualize one variable set a variable from the Question 1 select list (Russian nationality in percent, q6.2, in our example) and the administrative unit (rayons in our example). Press Show button. The inference could be like The population of ethnical Russians is the most numerous in Crimea (between 54 and 68%), and in the Eastern-Southern oblasts 6-48%. However, the East-South is highly heterogeneous in ethnic composition, so is each particular oblast of this region. Thus, the north of Odessa oblast has 6%, while south – 23% of Russians; north of Zaporizhzhia – 17%, south -33%; north of Luhansk oblast – 34%, south – 48%”.
Or, if historical region is selected, then, the interpretation will be like following: Out of 8 historical region of the Cossack state period, the most dense population of Russians live in the former Ottoman empire (52%), followed by Crimean Khanate (23%) and by Zaporizhzhia Cossacks and the Sloboda Ukraine (16-18%). In all other parts of Ukraine Russian population does not exceed 5%.
Examples of building maps and the types of inferences they allow to make
Example 2
To put the borders of one region over the other: pick up a map of a smaller region from the Map select list, one variable from the Question 1 select list, and a Transparent map. General rule – transparent map should have larger scale than the basic map. The interpretation is: The territories of early historical formations – Polish Lithuanian Kingdom and Hetmanat – have more homogenious, Ukrainian, ethnic composition nowadays, while in the former Dyke pole areas and the former Crimean Khanat more Russians live here now. Presence of Russians varies, however, varies from 11% in Dnipropetrovsk oblast to 56% in Crimea.
Examples of building maps and the types of inferences they allow to make
Example 3
As another version of the visualization of one variable with the help of two maps we can pick the same variables from the two lists (Question 1 and Question 2) and two different maps from the two boxes – smaller – rayons, and larger for transparent map – macroregions. The interpretations will be like the following: Although the south of Ukraine is the most densely populated by Russians (32%) there is a sharp contrast between the Crimea (56%) and the continental south (18-20%). Eastern region is inner heterogeneous as between some rayons of Luhansk oblast and Zaporizhzhia oblasts there is difference at the level of 14-15% between rayons. Presumably, in the most urbanized parts more ethnic Russians live.
Note: In this case we should ignore the white spots: these are not low values of variable but the rayons for which the data are absent. To see more coherent picture check the Use approximation checkbox.
Examples of building maps and the types of inferences they allow to make
Example 4
Visualization of the two variables, version 1: please, select a map from the Map select list (we selected oblast), one variable from
the Question 1 select list, the same map from the Transparent map select list and the question from the Question 2 (53.2 for example).
The interpretation is: Generally, the farther to the east, the higher is the share of Russians in population and the more people consider Russian
language as their mother tongue. However, there are obvious inconsistencies between the two pair of oblasts: although in Mykolaiv oblasts there
are less ethnic Russians, more population considers Russian as native (38 against 29% in Odessa. On the other hand, although the share of ethnic
Russian is approximately the same in Kharkiv and Donetsk oblasts 18 and 20% respectively), Donetsk oblasts inhabitants more often considers
Russian as their native (47 against 38).
Depending on whether you use the Use color or Use pattern radio buttons, you will get first or second variant of a map.
Examples of building maps and the types of inferences they allow to make
Example 5
If you select different maps from the two map selects you will get two levels of visualization. Please, pick up maps from the both select lists and two different variables. In our example the ground map is for the language variable (53.2) and the transparent for the nationality variable (6.2). The interpretation is like follows: Though Russian are more widely distributed in the South and East of Ukraine, the choice of Russian as a mother tongue shows high variation depending on the place of living. In the largest urban units – Mykolaiv, Kharkiv, Zaporizhzhia it is selected a way more often, than in the surrounding living units.
Examples of building maps and the types of inferences they allow to make
Example 6
Visualization of the two variables with the help of hatch over the first colored level; produced with the help of Use pattern radio button. The interpretation is the same as with the semi-transparent visualization.
