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Mapping is creating graphic representations of information using spatial relationships within the graphic to represent some relationships within the data. The common and original practice of mapping is the scaled portrayal of geographical features, that is, cartography. In the contemporary sense of data visualization, it includes metaphorical extensions of geographical map conventions and literacies to other kinds of data, as well as innovative ways of visualizing data not clearly related to the geographical archetype. In popular vernacular, mapping can just mean organizing or systematizing information.
Contemporary maps of non-geographical data sets make use of and extend the familiar ways of organizing information in geographical maps to other kinds of data not necessarily concerned with spacial relationships per se. The foundational notion is that an arrangement of elements in a synthetic space can help to organize or clarify. Space in these maps may represent affinity rather than proximity, can represent set groupings, or, as is often the case, can use space a medium through which to diagram connecting networks. Spatial area can indicate magnitude or quantity. These kinds of parameters can be usefully applied in the visualizing of data, revealing a variety of relationships at a glance.
Mapping, when referring to map-making, is often used interchangeably with cartography. Traditionally, a geographic map is created through cartographic protocols (i.e. determining the scale/level of detail and content of geographic or cartographic database, map projection and coordinate system selection and transformations, entry criteria and symbol specification for geospatial objects, generalization, layout design etc.). The term is also sometimes used for hi-tech geospatial data collection, e.g. LIDAR mapping. The acquisition of data with geographic coordinates directly from terrain or imagery is more properly referred to as surveying.
The designation "science map" normally refers to the content of the map rather than the methodology, though there is not a clear distinction between science maps and scientific diagrams such as graphs of experimental results projected into a Cartesian coordinate system. Science maps show a visual rendering of a dataset. Maps can be abstract, geographical, or feature-based, but are typically richer than simple x-y plots. Data can be used to generate a reference system over which other data—e.g., career trajectories—are overlaid. Data can also be projected onto an existing reference system (e.g., a map of the world).
The proliferation of Science maps owes a lot to the data processing and visualizing capabilities of computers, particularly the ability to correlate visual representations with algorithmic functions.
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