Color is the result of the visual perception of an energy source. It is described by its physical characteristics, mainly as a tridimensional variable modeled into a color space. Online tools exist to facilitate the use of color schemes to design a color palette, for artists, web designers, statisticians, etc. Colors in maps and visualizations must be combined to promote the visual hierarchy and harmony, balancing legibility, perceptual processing, and aesthetics. Color is a powerful visual variable and requires understanding the perception of color relationships. Existing color schemes are very useful to select a suitable color palette. As color is not experienced similarly across all map readers, issues about real-world connotations, conventions, specific color contrasts, and adaptation to color visual deficiencies and devices, are also to be taken into account when designing a color palette. This entry describes the main guidelines regarding color theory and related design practices as applied to map or geovisualization design.

Thematic maps cover a wide variety of mapping solutions, and include choropleth, proportional symbol, isoline, dot density, dasymetric, and flow maps as well as cartograms, among others. Each thematic map type requires a different data processing method and employs different visual variables, resulting in representations that are either continuous or discrete and smooth or abrupt. As a result, each solution highlights different aspects of the mapped phenomena and shapes the message for the map readers differently. Thematic maps are tools for understanding spatial patterns, and the choice of thematic map type should support this understanding. Therefore, the main consideration when selecting a thematic map type is the purpose of the map and the nature of the underlying spatial patterns.

This entry reviews the common types of thematic maps, describes the visual variables that are applied in them, and provides design considerations for each thematic map type, including their legends. It also provides an overview of the relative strengths and limitations of each thematic map type.

“Competence” is a word that rolls off the tongues of instructional designers, education administrators, and HR people. Others find it hard to swallow. For some GIS&T educators, competence connotes an emphasis on vocational instruction that’s unworthy of the academy. This entry challenges skeptical educators to rethink competence not just as readiness for an occupation, but first and foremost as the readiness to live life to the fullest, and to contribute to a sustainable future. The entry considers the OECD’s “Key Competencies for a Successful Life and Well-Functioning Society,” as well as the specialized GIS&T competencies specified in the U.S. Department of Labor’s Geospatial Technology Competency Model. It presents findings of a survey in which 226 self-selected members of Esri’s Young Professionals Network observe that competencies related to the GTCM’s Software and App Development Segment were under-developed in their university studies. Looking ahead, in the context of an uncertain future in which, some say, many workers are at risk of “technological unemployment,” the entry considers which GIS&T competencies are likely to be of lasting value.

Within an initial phase of database design, a conceptual data model is created as a technology-independent specification of the data to be stored within a database. This specification often times takes the form of a formalized diagram.  The process of conceptual data modeling is meant to foster shared understanding among data modelers and stakeholders when creating the specification.  As such, a conceptual data model should be easily readable by people with little or no technical-computer-based expertise because a comprehensive view of information is more important than a detailed view. In a conceptual data model, entity classes are categories of things (person, place, thing, etc.) that have attributes for describing the characteristics of the things.  Relationships can exist between the entity classes.  Entity-relationship diagrams have been and are likely to continue to be a popular way of characterizing entity classes, attributes and relationships.  Various notations for diagrams have been used over the years. The main intent about a conceptual data model and its corresponding entity-relationship diagram is that they should highlight the content and meaning of data within stakeholder information contexts, while postponing the specification of logical structure to the second phase of database design called logical data modeling.