All Topics

A B C D E F G H I K L M N O P R S T U V W
DM-67 - NoSQL Databases

NoSQL databases are open-source, schema-less, horizontally scalable and high-performance databases. These characteristics make them very different from relational databases, the traditional choice for spatial data. The four types of data stores in NoSQL databases (key-value store, document store, column store, and graph store) contribute to significant flexibility for a range of applications. NoSQL databases are well suited to handle typical challenges of big data, including volume, variety, and velocity. For these reasons, they are increasingly adopted by private industries and used in research. They have gained tremendous popularity in the last decade due to their ability to manage unstructured data (e.g. social media data).

FC-35 - Openness

The philosophy of Openness and its use in diverse areas is attracting increasing attention from users, developers, businesses, governments, educators, and researchers around the world. The technological, socio-cultural, economic, legal, institutional, and philosophical issues related to its principles, applications, benefits, and barriers for its use are growing areas of research. The word “Open” is commonly used to denote adherence to the principles of Openness. Several fields are incorporating the use of Openness in their activities, some of them are of particular relevance to GIS&T (Geographic Information Science and Technology) such as: Open Data, Free and Open Source Software; and Open Standards for geospatial data, information, and technologies. This entry presents a definition of Openness, its importance in the area of GISc&T is introduced through a list of its benefits in the fields of Open Data, Open Source Software, and Open Standards. Then some of the barriers, myths, or inhibitors to Openness are presented using the case of Free and Open Source Software (FOSS) and FOSS for Geospatial Applications (FOSS4G).

KE-33 - Organizational Models for GIS Management

Organizational structures and management practices for GIS programs are numerous and complex. This topic begins with an explanation of organizational and management concepts and context that are particularly relevant to GIS program and project management, including strategic planning and stakeholders. Specific types of organizations that typically use GIS technology are described and organizational structure types are explained. For GIS Program management, organizational placement, organizational components, and management control and policies are covered in depth. Multi-organizational GIS Programs are also discussed. Additional topics include management roles and technology trends that affect organizational structure. It concludes with a general description of GIS Project management. 

DM-36 - Physical Data Models

Constructs within a particular implementation of database management software guide the development of a physical data model, which is a product of a physical database design process. A physical data model documents how data are to be stored and accessed on storage media of computer hardware.  A physical data model is dependent on specific data types and indexing mechanisms used within database management system software.  Data types such as integers, reals, character strings, plus many others can lead to different storage structures. Indexing mechanisms such as region-trees and hash functions and others lead to differences in access performance.  Physical data modeling choices about data types and indexing mechanisms related to storage structures refine details of a physical database design. Data types associated with field, record and file storage structures together with the access mechanisms to those structures foster (constrain) performance of a database design. Since all software runs using an operating system, field, record, and file storage structures must be translated into operating system constructs to be implemented.  As such, all storage structures are contingent on the operating system and particular hardware that host data management software. 

FC-26 - Problems of Scale and Zoning

Spatial data are often encoded within a set of spatial units that exhaustively partition a region, where individual level data are aggregated, or continuous data are summarized, over a set of spatial units. Such is the case with census data aggregated to enumeration units for public dissemination. Partitioning schemes can vary by scale, where one partitioning scheme spatially nests within another, or by zoning, where two partitioning schemes have the same number of units but the unit shapes and boundaries differ. The Modifiable Areal Unit Problem (MAUP) refers to the fact the nature of spatial partitioning can affect the interpretation and results of visualization and statistical analysis. Generally, coarser scales of data aggregation tend to have stronger observed statistical associations among variables. The ecological fallacy refers to the assumption that an individual has the same attributes as the aggregate group to which it belongs. Combining spatial data with different partitioning schemes to facilitate analysis is often problematic. Areal interpolation may be used to estimate data over small areas or ecological inference may be used to infer individual behaviors from aggregate data. Researchers may also perform analyses at multiple scales as a point of comparison.

GS-11 - Professional and Practical Ethics of GIS&T

Geospatial technologies are often and rightly described as “powerful.” With power comes the ability to cause harm – intentionally or unintentionally - as well as to do good. In the context of GIS&T, Practical Ethics is the set of knowledge, skills and abilities needed to make reasoned decisions in light of the risks posed by geospatial technologies and methods in a wide variety of use cases. Ethics have been considered from different viewpoints in the GIS&T field. A practitioner's perspective may be based on a combination of "ordinary morality," institutional ethics policies, and professional ethics codes. By contrast, an academic scholar's perspective may be grounded in social or critical theory. What these perspectives have in common is reliance on reason to respond with integrity to ethical challenges. This entry focuses on the special obligations of GIS professionals, and on a method that educators can use to help students develop moral reasoning skills that GIS professionals need. The important related issues of Critical GIS and Spatial Law and Policy are to be considered elsewhere.  

KE-31 - Professional Certification

Professional Certification has been a part of the GIS enterprise for over two decades. There are several different certification programs and related activities now in operation within GIS, though there has been much debate over its merits, how it should be done and by whom. 

DC-01 - Professional Land Surveying

Professional Land Surveyors are the only profession that create the legal description of land parcels, which are then officially recorded to show ownership and rights pertaining to each and every land parcel within a jurisdiction. The Surveyor is skilled at undertaking the physical measurements that are needed to locate accurately land parcels on the ground and to write the unambiguous legal description of the land to create legal title in real estate. These land ownership records are critical for the transfer of ownership in the real estate market. The legal land description provided by Surveyors forms the foundation, and the real estate market provides the mechanism, for real estate to become the largest store of tangible wealth in any free market economy.

PD-11 - Python for GIS

Figure 1. PySAL within QGIS Processing Toolbox: Hot-spot analysis of Homicide Rates in Southern US Counties.

 

Python is a popular language for geospatial programming and application development. This entry provides an overview of the different development modes that can be adopted for GIS programming with Python and discusses the history of Python adoption in the GIS community. The different layers of the geospatial development stack in Python are examined giving the reader an understanding of the breadth that Python offers to the GIS developer. Future developments and broader issues related to interoperability and programming ecosystems are identified.

PD-15 - R for Geospatial Analysis and Mapping

R is a programming language as well as a computing environment to perform a wide variety of data analysis, statistics, and visualization. One of the reasons for the popularity of R is that it embraces open, transparent scholarship and reproducible research. It is possible to combine content and code in one document, so data, analysis, and graphs are tied together into one narrative, which can be shared with others to recreate analyses and reevaluate interpretations. Different from tools like ArcGIS or QGIS that are specifically built for spatial data, GIS functionality is just one of many things R offers. And while users of dedicated GIS tools typically interact with the software via a point-and-click graphical interface, R requires command-line scripting. Many R users today rely on RStudio, an integrated development environment (IDE) that facilitates the writing of R code and comes with a series of convenient features, like integrated help, data viewer, code completion, and syntax coloring. By using R Markdown, a particular flavor of the Markdown language, RStudio also makes it particularly easy to create documents that embed and execute R code snippets within a text and to render both, static documents (like PDF), as well as interactive html pages, a feature particularly useful for exploratory GIS work and mapping.

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