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DM-35 - Logical Data Models

A logical data model is created for the second of three levels of abstraction, conceptual, logical, and physical. A logical data model expresses the meaning context of a conceptual data model, and adds to that detail about data (base) structures, e.g. using topologically-organized records, relational tables, object-oriented classes, or extensible markup language (XML) construct  tags. However, the logical data model formed is independent of a particular database management software product. Nonetheless such a model is often constrained by a class of software language techniques for representation, making implementation with a physical data model easier. Complex entity types of the conceptual data model must be translated into sub-type/super-type hierarchies to clarify data contexts for the entity type, while avoiding duplication of concepts and data. Entities and records should have internal identifiers. Relationships can be used to express the involvement of entity types with activities or associations. A logical schema is formed from the above data organization. A schema diagram depicts the entity, attribute and relationship detail for each application. The resulting logical data models can be synthesized using schema integration to support multi-user database environments, e.g., data warehouses for strategic applications and/or federated databases for tactical/operational business applications.

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).

CP-26 - eScience, the Evolution of Science

Science—and research more broadly—face many challenges as its practitioners struggle to accommodate new challenges around reproducibility and openness.  The current practice of science limits access to knowledge, information and infrastructure, which in turn leads to inefficiencies, frustrations and a lack of rigor.  Many useful research outcomes are never used because they are too difficult to find, or to access, or to understand.

New computational methods and infrastructure provide opportunities to reconceptualize how science is conducted, how it is shared, how it is evaluated and how it is reused.  And new data sources changed what can be known, and how well, and how frequently.  This article describes some of the major themes of eScience/eResearch aimed at improving the process of doing science.

DA-37 - GIS&T and Epidemiology

Location plays an important role in human health. Where we live, work, and spend our time is associated with different exposures, which may influence the risk of developing disease. GIS has been used to answer key research questions in epidemiology, which is the study of the distribution and determinants of disease. These research questions include describing and visualizing spatial patterns of disease and risk factors, exposure modeling of geographically varying environmental variables, and linking georeferenced information to conduct studies testing hypotheses regarding exposure-disease associations. GIS has been particularly instrumental in environmental epidemiology, which focuses on the physical, chemical, biological, social, and economic factors affecting health. Advances in personal exposure monitoring, exposome research, and artificial intelligence are revolutionizing the way GIS can be integrated with epidemiology to study how the environment may impact human health.

DA-10 - GIS&T and Real Estate

Real Estate GIS concerns all dimensions of real estate that can be better understood or operationalized by knowing its geospatial context. Improving real estate decisions via GIS and related geospatial technologies is now expected by management of all industries, as well as home-renters and home-buyers in the residential market. Real Estate GIS Specialists are individuals who have applied knowledge and skills across the disciplines of business geography, the practice of real estate, and the application of geospatial technologies to support decision making in this realm. There is a good reason why the mantra of “location, location, location” is a long-standing tenet within the business of real estate.

AM-23 - Local Measures of Spatial Association

Local measures of spatial association are statistics used to detect variations of a variable of interest across space when the spatial relationship of the variable is not constant across the study region, known as spatial non-stationarity or spatial heterogeneity. Unlike global measures that summarize the overall spatial autocorrelation of the study area in one single value, local measures of spatial association identify local clusters (observations nearby have similar attribute values) or spatial outliers (observations nearby have different attribute values). Like global measures, local indicators of spatial association (LISA), including local Moran’s I and local Geary’s C, incorporate both spatial proximity and attribute similarity. Getis-Ord Gi*another popular local statistic, identifies spatial clusters at various significance levels, known as hot spots (unusually high values) and cold spots (unusually low values). This so-called “hot spot analysis” has been extended to examine spatiotemporal trends in data. Bivariate local Moran’s I describes the statistical relationship between one variable at a location and a spatially lagged second variable at neighboring locations, and geographically weighted regression (GWR) allows regression coefficients to vary at each observation location. Visualization of local measures of spatial association is critical, allowing researchers of various disciplines to easily identify local pockets of interest for future examination.

DA-39 - GIS&T and Recreation Planning and Management

Human interactions with each other and the environment are intrinsically connected to the opportunities and limitations of where we live and where we are able to go. The connections between places of origin, destinations, and travel routes mean that recreation and tourism inherently rely on spatial concepts of place and human-environment interactions. Tourism and recreation are major economic drivers, yet these sectors are constantly evolving as people embrace different ways to travel and recreate and environmental and socio-economic conditions change. Advances in GIS technology and computing ability are shaping the questions asked and tools used by researchers to understand the drivers and impacts of recreation. In this entry, we highlight current research and approaches used to characterize access to green spaces in urban areas, to understand recreational behaviors and tourist preferences through social media, to map landscape aesthetics and cultural ecosystem services, and to quantify the impacts of tourism and recreation on protected areas. Starting with urban areas and local extents and moving to protected areas and regional processes, we summarize scholarship focused on different types of places and occurring across different extents and scales to provide a digest of current research.

PD-10 - Natural Language Processing in GIScience Applications

Natural Language Processing (NLP) has experienced explosive growth in recent years. While the field has been around for decades, recent advances in NLP techniques as well as advanced computational resources have re-engaged academics, industry, and the general public. The field of Geographic Information Science has played a small but important role in the growth of this domain. Combining NLP techniques with existing geographic methodologies and knowledge has contributed substantially to many geospatial applications currently in use today. In this entry, we provide an overview of current application areas for natural language processing in GIScience. We provide some examples and discuss some of the challenges in this area.

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. 

FC-12 - Structured Query Language (SQL) and attribute queries

The structured query language (SQL) for database interrogation is presented and illustrated with a few examples using attribute tables one might find in a common GIS database.  A short background is presented on the history and goals that the creators of the SQL language hoped to achieve, followed by a review of SQL utility for data query, editing, and definition.  While the SQL language is rich in content and breadth, this article attempts to build on a simple SQL and then iteratively add additional complexity to highlight the power that SQL affords to the GIS professional who has limited programming capabilities.  The reader is asked to consider how minor modifications to SQL syntax can add complexity and even create more dynamic mathematical models with simple English-like command statements.  Finally, the reader is challenged to consider how terse SQL statements may be used to replace relatively long and laborious command sequences required by a GIS GUI approach.

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