Dalia Varanka

Design and development of linked data from The National Map

The development of linked data on the World-Wide Web provides the opportunity for the U.S. Geological Survey USGS to supply its extensive volumes of geospatial data, information, and knowledge in a machine interpretable form and reach users and applications that heretofore have been unavailable. To pilot a process to take advantage of this opportunity, the USGS is developing an ontology for The National Map and converting selected data from nine research test areas to a Semantic Web format to support machine processing and linked data access. In a case study, the USGS has developed initial methods for legacy vector and raster formatted geometry, attributes, and spatial relationships to be accessed in a linked data environment maintaining the capability to generate graphic or image output from semantic queries. The description of an initial USGS approach to developing ontology, linked data, and initial query capability from The National Map databases is presented.

An ontology design pattern for surface water features

Surface water is a primary concept of human experience but concepts are captured in cultures and languages in many different ways. Still, many commonalities exist due to the physical basis of many of the properties and categories. An abstract ontology of surface water features based only on those physical properties of landscape features has the best potential for serving as a foundational domain ontology for other more context-dependent ontologies. The Surface Water ontology design pattern was developed both for domain knowledge distillation and to serve as a conceptual building-block for more complex or specialized surface water ontologies. A fundamental distinction is made in this ontology between landscape features that act as containers (e.g., stream channels, basins) and the bodies of water (e.g., rivers, lakes) that occupy those containers. Concave (container) landforms semantics are specified in a Dry module and the semantics of contained bodies of water in a Wet module. The pattern is implemented in OWL, but Description Logic axioms and a detailed explanation is provided in this paper. The OWL ontology will be an important contribution to Semantic Web vocabulary for annotating surface water feature datasets. Also provided is a discussion of why there is a need to complement the pattern with other ontologies, especially the previously developed Surface Network pattern. Finally, the practical value of the pattern in semantic querying of surface water datasets is illustrated through an annotated geospatial dataset and sample queries using the classes of the Surface Water pattern.

Topographic Mapping Data Semantics Through Data Conversion and Enhancement

This paper presents research on the semantics of topographic data for triples and ontologies to blend the capabilities of the Semantic Web and The National Map of the U.S. Geological Survey. Automated conversion of relational topographic data of several geographic sample areas to the triple data model standard resulted in relatively poor semantic associations. Further research employed vocabularies of feature type and spatial relation terms. A user interface was designed to model the capture of non-standard terms relevant to public users and to map those terms to existing data models of The National Map through the use of ontology. Server access for the study area triple stores was made publicly available, illustrating how the development of linked data may transform institutional policies to open government data resources to the public. This paper presents these data conversion and research techniques that were tested as open linked data concepts leveraged through a user-centered interface and open USGS server access to the public.

Spatial Relation Predicates in Topographic Feature Semantics

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

The Use of U.S. Geological Survey Digital Geospatial Data Products for Science Research

The development of geographic information system (GIS) transformed the practice of geographic science research. The availability of low-cost, reliable data by the U.S. Geological Survey (USGS) supported the advance of GIS in the early stages of the transition to digital technology. To estimate the extent of the scientific use of USGS digital geospatial data products, a search of science literature databases yielded numbers of articles citing USGS products. Though this method requires careful consideration to avoid false positives, these citation numbers of three types of products (vector, land-use/land-cover, and elevation data) were graphed, and the frequency trends were examined. Trends indicated that the use of several, but not all, products increased with time. The use of some products declined and reasons for these declines are offered. To better understand how these data affected the design and outcomes of research projects, the study begins to build a context for the data by discussing digital cartographic research preceding the production of mass-produced products. The data distribution methods used various media for different system types and were supported by instructional material. The findings are an initial assessment of the affect of USGS products on GIS-enabled science research. A brief examination of the specific papers indicates that USGS data were used for science and GIS conceptual research, advanced education, and problem analysis and solution applications.

Interpolating a consumption variable for scaling and generalizing potential population pressure on urbanizing natural areas

Measures of population pressure, referring in general to the stress upon the environment by human consumption of resources, are imperative for environmental sustainability studies and management. Development based on resource consumption is the predominant factor of population pressure. This paper presents a spatial model of population pressure by linking consumption associated with regional urbanism and ecosystem services. Maps representing relative geographic degree and extent of natural resource consumption and degree and extent of impacts on surrounding areas are new, and this research represents the theoretical research toward this goal. With development, such maps offer a visualization tool for planners of various services, amenities for people, and conservation planning for ecologist. Urbanization is commonly generalized by census numbers or impervious surface area. The potential geographical extent of urbanism encompasses the environmental resources of the surrounding region that sustain cities. This extent is interpolated using kriging of a variable based on population wealth data from the U.S. Census Bureau. When overlayed with land-use/land-cover data, the results indicate that the greatest estimates of population pressure fall within mixed forest areas. Mixed forest areas result from the spread of cedar woods in previously disturbed areas where further disturbance is then suppressed. Low density areas, such as suburbanization and abandoned farmland are characteristic of mixed forest areas.

Ontological Issues for National Topographic Mapping

The articles in this special section of Cartographica are the result of a meeting of invited specialists titled ‘‘Building an Ontology for The National Map,’’ held on 3–4 February 2009 in Washington, DC. Sponsored by the University Consortium for Geographic Information Science on behalf of the US Geological Survey (USGS), this meeting was intended to solicit ideas on the development of an ontology for the USGS’s National Map (TNM). Academic, industry, and government participants were selected based on reviewed position papers. Though the immediate aim of the workshop was to further the goals of TNM as a trusted, free, and responsive user tool, the workshop also aimed to benefit the broader geo-semantic research community.

GNIS-LD: Serving and Visualizing the Geographic Names Information System Gazetteer as Linked Data

In this dataset description paper we introduce the GNIS-LD, an authoritative and public domain Linked Dataset derived from the Geographic Names Information System (GNIS) which was developed by the U.S. Geological Survey (USGS) and the U.S. Board on Geographic Names. GNIS provides data about current, as well as historical, physical, and cultural geographic features in the United States. We describe the dataset, introduce an ontology for geographic feature types, and demonstrate the utility of recent linked geographic data contributions made in conjunction with the development of this resource. Co-reference resolution links to GeoNames.org and DBpedia are provided in the form of owl:sameAs relations. Finally, we point out how the adapted workflow is foundational for complex Digital Line Graph (DLG) data from the USGS National Map and how the GNIS-LD data can be integrated with DLG and other data sources such as sensor observations.

The map as knowledge base

ABSTRACT This paper examines the concept and implementation of a map as a knowledge base. A map as a knowledge base means that the visual map is not only the descriptive compilation of data and design principles, but also involves a compilation of semantic propositions and logical predicates that create a body of knowledge organized as a map. The digital product of a map as knowledge base can be interpreted by machines, as well as humans, and can provide access to the knowledge base through interfaces to select features and other information from the map. The design of maps as a knowledge base involves technical approaches and a system architecture to support a knowledge base. This paper clarifies how a map as a knowledge base differs from earlier map theory models by investigating the knowledge-based concepts of implementation through logical modelling, a knowledge repository, user interfaces for information access, and cartographic visualization. The paper ends with proof of concepts for two types of cartographic data query.

Adapting the U.S. National Hydrography Dataset to Linked Open Data

A controlled vocabulary for the National Hydrography Dataset (NHD) of the United States was developed as Linked Open Data (LOD). The vocabulary has two main parts: a glossary and a set of triples reflecting the NHD data model as it is organized in geographic information systems (GIS). The glossary consists of a feature type label and a comment consisting of a definition that is linked to a hydrographic feature type standard. The ontology of the data model consists of classes and properties that group and relate sets of individual features. The objective of the project is to draw on the glossary and the “triplified” data model to build formal semantics for a basic form of NHD as LOD. Modifications were made primarily to the specification of feature types for the data.