Data Visualization


Linked Topics


Subject: Data Visualization




In an earlier post, I investigated about mapping and its usability in visualising geographic information systems, today, quite am after a similar discipline, where data are the concern, and more scatter among earth corners, and have more than our known 3 dimensions, additionally,  it has the time dimension.

Data Visualization

Data Visualization is an area of knowledge concerned with representing the data either textual or numerical or geographical in the means of graphics. there are many ways to represent the data, mainly, either as its original real form and location or in abstract shapes and schematic forms, for both cases in a way that feature the attributes and variables of the data structure.

the aim of the process of data visualisation is to communicate information in a clear way, that make it useful and easy to understand, it help the viewer to understand the bigger picture, and also to pay attention to details and so, interact accordingly. and the most important, it makes data look beautiful, and make the preview process entertaining and a bring a state of enjoyment.

there are many fields of knowledge related directly or in need of data visualisation, e.g. data acquisition; which related with converting measurements out of sensors and electronic devices into digital signals. data analysis is another area, where data are collected, analysed, summarised and then extracted information and findings used to produce conclusions, similarly, to the data mining, with small differences in the amount of data; it’s more of statistics, where logic used to detect patterns and extract information useful for decision making.


there are many forms of data visualisation purposes, it’s not easy to cover them all, but I will try to categorise;

maps: location of an activity and its magnitude, sometimes, the ranking of specific value, and its distribution.

Internet Activities, such like connections, digital attacks and messages.

paths and routes of people, transport, natural phenomenon and data, also the weather changes.

the natural disasters and its impacts, such as flooding, volcanoes, hurricanes and earthquakes.

any statistics showing differences between activity among spaces, or indicate pattern changes among quit longer time, such like historical changes or even seasonal changes.

I will try my best in the near future to cover more types and make as many examples as possible.


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