U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2012–1109

Introduction to Geospatial Semantics and Technology

Workshop Handbook

1649

Quarry

Building

Control Station

Mine Shaft

'Crater Road'

Well

Water

Sand

Road

1652

9763

1497

1523

1529

'Meteor Crater'

Meteoric Crater

instanceOf inverse

hasProduct

locatedIn

nearbyFeature

'Meteor Crater

Museum'

'USGS Benchmark

BM5723'

'USGS Benchmark

BM5706'

'USGS Benchmark

BM5123'
Cover photograph. Meteor Crater, Arizona (http://en.wikipedia.org/wiki/File:Meteor_Crater_-_Arizona.jpg).
Introduction to Geospatial Semantics and 

Technology Workshop Handbook

Edited by Dalia E. Varanka

Open-File Report 2012–1109

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, 

visit http://www.usgs.gov/pubprod

To order this and other USGS information products, visit http://store.usgs.gov

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Varanka, D.E., ed., 2012, Introduction to geospatial semantics and technology workshop handbook: U.S. Geological 

Survey Open-File Report 2012–1109, 107 p.
iii

Contents

Workshop Agenda .........................................................................................................................................2

Workshop Summary and Slides ..................................................................................................................4

Overview.................................................................................................................................................4

An Introduction to Semantic Web and Technology Concepts ......................................................9

Accessing Linked Data Over the Internet ......................................................................................33

The USGS Approach to the Geospatial Semantic Web................................................................44

Accessing Topographic Data Triples...............................................................................................68

The SOCoP Open Ontology Repository (OOR)................................................................................92

Meteor Crater Ontology.....................................................................................................................92

Internet Resources......................................................................................................................................99

Standards and Shared Vocabularies...............................................................................................99

Software and Technology Products ................................................................................................99

Ontologies and Linked Data ............................................................................................................100

Online Tutorials..................................................................................................................................100

Ontology Communities, Professional Organizations, and Workshop Events .........................101

Research Groups and Programs of Study ....................................................................................101

Blogs ...................................................................................................................................................101

Suggested Literature.................................................................................................................................102

Semantic and Geospatial Semantic Web.....................................................................................102

Geospatial Semantics and Ontology .............................................................................................102

Taxomony, Mereotopology and Other Relations .........................................................................103

Linked Data and Social Networking ..............................................................................................103

Application Engineering ..................................................................................................................103

Geography, GIScience, and GeoInformatics................................................................................103

Land Cover.........................................................................................................................................104

Ecology and Environmental Monitoring........................................................................................104

Terrain.................................................................................................................................................104

Ontology of Rasters and Images ....................................................................................................105

Similarity and Interoperability ........................................................................................................105

Logic and Knowledge Representation and Reasoning ..............................................................105

USGS Resources...............................................................................................................................106

Edited Journal Issues and Proceedings from Scholarly Meetings..........................................106

Workshop Review Form............................................................................................................................107

Introduction to Geospatial Semantics and Technology 

Workshop Handbook

University Consortium for Geographic Information Science

May 29, 2012

Washington D.C.

The workshop is a tutorial on introductory geospatial semantics with hands-on exercises using standard Web browsers. 

The workshop is divided into two sections, general semantics on the Web and specific examples of geospatial semantics using 

data from The National Map of the U.S. Geological Survey and the Open Ontology Repository. The general semantics section 

includes information and access to publicly available semantic archives. The specific session includes information on geospatial 

semantics with access to semantically enhanced data for hydrography, transportation, boundaries, and names. The Open Ontology Repository offers open-source ontologies for public use. 

Dalia E. Varanka, Editor

USGS Center of Excellence for Geospatial Information Science (CEGIS)

http://cegis.usgs.gov/ontology.html

Spatial Ontology Community of Practice (SOCoP)

http://www.socop.org
2 Introduction to Geospatial Semantics and Technology Workshop Handbook

Workshop Agenda

12:00 – 1:00 pm Introduction to the workshop and to semantic technology concepts

Topics: Semantic Web standards and implementation examples, ontologies, and geospatial Semantic Web adaptations

1:00 – 2:00 pm Hands-on exercise: Accessing Linked Data over the Internet

Using the following URLs:

FOAF-A-MATIC

• http://ldodds.com/foaf/foaf-a-matic

Tim Berners-Lee’s FOAF page.

• http://www.w3.org/People/Berners-Lee/

Start page for the GeoNames map

• http://www.geonames.org/6295630/

Download page for GeoNames

• http://www.geonames.org/ontology/documentation.html

Start page for the Faceted Search

• http://dbpedia.neofonie.de/browse

URL for Virtuoso RDF Browser

• http://dbpedia.org/fct/

DBpedia download page

• http://wiki.dbpedia.org/Downloads37
Workshop Agenda 3

2:00 – 3:00 pm USGS Approach to the Geospatial Semantic Web

Topics: Topographic data creation, ontology for The National Map, data retrieval, research needs in geospatial semantics 

3:00 – 4:00 pm Hands-on exercises: Accessing topographic data triples 

Executing queries with SPARQL Protocol and RDF Query Language (SPARQL) and GeoSPARQL, displaying results as URIs, 

and creating mapped output. URLS to use:

http://usgs-ybother.srv.mst.edu:8890/parliament/

http://usgs-ybother.srv.mst.edu/viz/

4:00 – 5:00 pm The Spatial Ontology Community of Practice (SOCoP) Open Ontology Repository

http://socop.oor.net/

Summary topics and wrap-up, discussion

Workshop Instructors: E. Lynn Usery, Dalia Varanka, Gary Berg-Cross

Workshop hands-on leads and support: David Mattli, Brian Collinge, Wayne Viers

Breaktimes will be scheduled during the workshop.
4 Introduction to Geospatial Semantics and Technology Workshop Handbook

Workshop Summary and Slides

Overview

UCGIS/USGS

Geospatial Semantics Workshop

Doubletree Hotel, Washington, D.C.

May 29, 2012 

U.S. Department of the Interior

U.S. Geological Survey
Workshop Summary and Slides 5

Motivation – Why host a Workshop

Geospatial semantics are future research and 

operational modes for GIS data

Lack of assimilation of semantics in GIScience 

community – e.g., Semantic Web appeared in 

2001; not many GIScientists use it even now

Potential to expose USGS approach and data to 

public audience; outreach to gain feedback on 

USGS efforts

Basic tutorial on semantics is needed in GIScience 

community

Introductory Level Tutorial

The Workshop is an introductory tutorial on 

geospatial semantics

Introduces the Semantic Web and some general 

applications

Includes specific details of USGS data conversion, 

availability and access

This workshop assumes little prior knowledge, 

only an ability to work with computers and 

Web browsers
6 Introduction to Geospatial Semantics and Technology Workshop Handbook

Goals of the Workshop

Introduce semantic data on the Web

Introduce examples of Semantic Web applications

Introduce geospatial semantics

Provide USGS approach to semantics for geospatial 

data

Provide access to sample geospatial Resource 

Description Framework (RDF) data

What you will learn

Basic vocabulary and operation of Semantic 

Web

How geospatial data are structured as RDF

How to build new RDF data

How to convert existing legacy geospatial data

How to query RDF triplestores with SPARQL and 

GeoSPARQL
Workshop Summary and Slides 7

Some Topics Not Included

Specific software packages

The SPARQL query language and syntax

Reasoning logic used in semantic applications

Specific ontological applications

Instructors

Dalia Varanka, Research Geographer, USGS

E. Lynn Usery, Research Geographer, USGS

David Mattli, Computer Scientist, USGS

Wayne Viers, Computer Scientist, USGS

Brian Collinge, Geographer, USGS

Gary Berg-Cross, Spatial Ontology Community of 

Practice
8 Introduction to Geospatial Semantics and Technology Workshop Handbook

Workshop Organization

Overview lecture on semantic concepts – Dalia 

Varanka

Hands-on exercise with Facebook, DBpedia, Geonames – Wayne Viers

Overview of USGS approach and geospatial 

semantics – E. Lynn Usery

Building ontology with Protégé – Brian Collinge

Hands-on exercises with USGS geospatial semantic 

data --- David Mattli

Open Ontology Repository – Gary Berg-Cross
Workshop Summary and Slides 9

An Introduction to Semantic Web and Technology Concepts

The first section of the workshop introduces background concepts from geospatial semantics and ontology technology, including the triple data model, controlled vocabularies, standards, along with processes such as linking data for federated graphs, logical inference for automated knowledge creation, and information querying using SPARQL and GeoSPARQL 

protocols. 

Geospatial Semantics 

An Introduction to the Basics

Dalia E. Varanka

Research Geographer

http://cegis.usgs.gov/ontology.html
10 Introduction to Geospatial Semantics and Technology Workshop Handbook

Why the Semantic Web?

Our world and particularly our cities form complex sociotechnical-natural systems, meta-systems, and systems of systems

More intelligence, instrumentation, application, integration 

Big Data (volume, variety, velocity, value) driving new 

paradigms in science 

Semantics

Semantics, the study of how humans derive meaning from 

representations, is a central approach for the design of new 

scales of systems and data

Growing area of technical research since 2001

Rooted in artificial intelligence

Ontology: the structural framework for organizing meaningful 

information

Broadly based research field; 

philosophy, linguistics, social science, engineering
Workshop Summary and Slides 11

Topics of this Introduction

Semantic Web standards 

Semantic technology implementation 

Designing ontology patterns

Geosemantic adaptations

GeoSPARQL standard

Presentation, Office, or Program Name

Internet Today

Web page URLs and keywords

pull out snippets of information; lack context

Linked data using tags

self-driven interaction with the media

Data scarcity, generalization, and representation 

can all cause ambiguous information 

interpretations
12 Introduction to Geospatial Semantics and Technology Workshop Handbook

A web of data forms the context that specifies

the meaning of a concept

Koivunen, M-R., and Miller, E.

W3C Semantic Web Activity

http://www.w3.org/2001/12/semweb-fin/w3csw

SPARQL 

Query

Graph

Triplestore

Inference

Reasoner

Results

URI Vocabulary

Semantic System

Ontology Design Software

Java/Jena Endpoint

Text/Graphic
Workshop Summary and Slides 13

W3C Standards 

 Semantic specification of each datum

 Uniform Resource Identifiers (URI)

 Vocabulary 

 Simple Knowledge Organization System (SKOS)

 Web Ontology Language (OWL)

 Linking data

 Resource Description Framework (RDF)

 Extensible Markup Language (XML) 

 Query and Reasoning

 SPARQL Protocol And RDF Query Language (SPARQL)

 Rule Interchange Format (RIF)

Semantic Specification

Vocabulary subject – predicate – object

Triple Resources node – edge – node 

Uniform Resource Identifier (URI):

http://cegis.usgs.gov/ontology/topovocab/1.0/terrain#

Prefix: usgsTopo

usgs:_7945 rdf:type usgsTopo:Crater
14 Introduction to Geospatial Semantics and Technology Workshop Handbook

Identifiers

Uniform Resource Identifier (URI)

Uniform Resource Locator (URL)

Uniform Resource Name (URN)

Internationalized Resource Identifier (IRI)

URI can be 

a lexical word

Random alpha-numeric unique identifier

Examples of Standard and Controlled 

Vocabularies

Philosophy terms (DOLCE)

Information content (NASA SWEET)

Metadata (Dublin Core Metadata Initiative)

Web Services (OGC Web Service Common)

Project terms (function, capability, role, 

purpose, objective, goal, etc.)

Task terms(map, compute, display)
Workshop Summary and Slides 15

USGS:Road 

CB:Address CB:Block geo:within 

USGS:Network 

USGS:Road Geometry 

hasGeometry 

USGS:Roa

d 

CB:Address CB:Block geo:within 

USGS:Network 

USGS:Road 

Geometry hasGeometry 

Text Definition

Census Bureau 

workstation

usgsTopo:

<vocabulary term>

Census Bureau

triplestore

usgsTopo:

<vocabulary term>

USGS endpoint

triplestore

rdf

Vocabulary

is accessed 

through the 

Internet

html
16 Introduction to Geospatial Semantics and Technology Workshop Handbook

Knowledge Representation and 

Reasoning (KRR)

Simulates cognition 

Language and interpretation

Reasoning forms

Logical

Experience and practice 

Signs and semiotics

Logic Rules as Predicates in OWL 

 ogc:intersects rdf:type owl:SymmetricProperty . 

usgsTopo:RoadA ogc:intersects usgsTopo:Road . 

 usgs:woodland owl:equivalentClass 

usgsTopo:woodedArea
Workshop Summary and Slides 17

Inference and Logic Rules

Information can be inferred based on logical rules

Inference Properties

 RDF Schema (RDFS) inference 

 Selected elements of OWL 

 equivalent classes and properties

 inverse properties

 symmetric properties

 functional properties

 inverse functional properties

 transitive properties 
18 Introduction to Geospatial Semantics and Technology Workshop Handbook

SPARQL

First part defines prefixes of URI namespaces

SELECT clause identifies the variables to be 

returned

SELECT ?feature

WHERE clause gives the triple patterns defining a 

basic graph pattern

 WHERE {?feature gnis:name ‘#name#’}

Solution and Results

Graph pattern given in the WHERE clause is 

matched against the triple store

An exact match to the pattern is required

Matching variables bind together to form the 

query solution

The values of the variables are the query results
Workshop Summary and Slides 19

Implementations

Converting Table Information 

to Triples

Rows are subjects, columns are predicates, and 

cells are objects 

Mountain Range hasProcess Tectonics

Delta hasProcess Deposition

Peak hasProcess Erosion

Volcano hasProcess Tectonics

Arch hasProcess Erosion
20 Introduction to Geospatial Semantics and Technology Workshop Handbook

Ontology to Database Interface

Challenges

Legacy resources are ambiguous

Triple stores quickly become volumetrically large

Is scaling up to the entire web possible?

Input data must be formatted -

Standardization vs. bottom-up information 

Concept commitments vs. multiple perspectives
Workshop Summary and Slides 21

Limited Applications

Semantic technology to resolve a specific 

problem

Metadata indexing for discovery, access, and 

management

Oak Ridge National Laboratory MERCURY

Vocabulary sharing

USGS Integrated Taxonomic Information System 

(ITIS) resolves Life Science ID (LSID) formats to RDF

Hybrid Applications

Content management

Drupal

Social networking data

Facebook Open Graph

Statistics

Gene Ontology (GO)

Mathematical functions

A large body of literature
22 Introduction to Geospatial Semantics and Technology Workshop Handbook

Ontology Design Pattern 

An ontology pattern is 

a modeling solution for a recurrent ontology designing 

problem

a template that represents the necessary and sufficient 

conditions as a base for specific design solutions

a set of “prototypical” ontology entities that constitute 

the “abstract form” of a pattern or schema

ODP for Place

http://ontologydesignpatterns.org
Workshop Summary and Slides 23

Method—Concept Mapping

Narrative and vocabulary are analyzed and 

converted to logical diagrams and computer 

applications

Begin With Reuseable Vocabularies

@prefix geonames: <http://www.geonames.org/ontology#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix owl: <http://www.w3.org/2002/07/owl#> .

@prefix dcterms: <http://purl.org/dc/terms/>

@prefix dbpedia: <http://dbpedia.org/ontology/>

@prefix geo: <http://www.opengis.net/ont/OGC-GeoSPARQL/1.0/>

@prefix usgsTopo: <http://cegis.usgs.gov/TopoVocab/1.0/Terrain#> .

@prefix usgs: <http://cegis.usgs.gov/ontology/instances#> .
24 Introduction to Geospatial Semantics and Technology Workshop Handbook

Construct a Taxonomy

Semantics of the relation

is-a, class inclusion, or subsumption

Different kinds of relations

Generalization, subsets, specialization

Structural similarities between descriptions

Semantic similarity measurement

Geosemantic Adaptations
Workshop Summary and Slides 25

Topographic Data Semantics

Wide appeal for participatory mapping

Basic categories 

Category theory

A physical ‘real world’ 

Helps disambiguate cognitive/cultural differences

Geospatial RDF Standards

W3C: 

Basic Geo Vocabulary (2003)

Location points combined with other ontology

GeoRSS (2006)

Location points with Really Simple Syndication 

GeoOWL ontology (2005)

Expanded the geosemantic vocabulary to include 

toponyms, spatial relations, coordinate reference 

systems, metadata, and web services
26 Introduction to Geospatial Semantics and Technology Workshop Handbook

Geospatial Features as Triples

<http://cegis.usgs.gov/ontology/instances> a owl:ontology

usgs:_7945 a usgsTopo:crater;

a geo:Feature ;

geo:hasGeometry usgs:_7945geo ;

geoname:name “Meteor Crater"

rdfs:comment "A meteor crater";

usgsTopo:hasBenchmark usgs:_5723 ;

usgsTopo:hasBenchmark usgs:_e5706 ;

dcterms:identifier "7945" ;

dcterms:description "Circular-shaped depression on the surface of the land caused by the impact of a meteorite"

usgs:_7945geoa geo:Geometry ;

usgsTopo:hasShape "circular" ;

usgsTopo:width "0.2km" ;

usgsTopo:innerDiameter "833m" ;

usgsTopo:outerDiameter "1250m" ;

usgsTopo:hasUTM "E 497959.94m N 3876020.68m Zone 12";

usgsTopo:hasPLSS "T 19 N, R 12 1/2 E, Section 13 and 24";

usgsTopo:hasMBR "Max E 489536.79m Min E 497317.62m Max N 3876632.29m Min N 3875479.58m";

dbpedia:MaximumElevation "5723ft";

dbpedia:MinimumElevation "5123ft";

dbpedia:MaximumDepth "600ft" .

Topological Relations

Relations based on interior, boundary, and 

exterior contact between two features

OGC Simple Feature 

Terms

•Equals

•Disjoint

•Intersects

•Touches

•Within

•Contains

•Overlaps

•Crosses
Workshop Summary and Slides 27

GIS vs. Geosemantic Topology

 GIS topology is not converted

 Topology is calculated with

 Well Known Text (WKT)

 Geography Markup Language (GML)

GeoSPARQL Ontology

geo:SpatialObject

geo:Feature geo:hasGeometry geo:Geometry

geo:defaultGeometry

geo:asWKT / sf:wktLiteral for values

geo:asGML / gml:gmlLiteral for values
28 Introduction to Geospatial Semantics and Technology Workshop Handbook

?type

USGSfid:_102217454

fidn ?feature

ogc:hasGeometry

ogc:touches

ogc:hasGeometry

rdf:type

geom

geom

GeoSPARQL Filter Functions

Operator functions take multiple geometries as 

predicates and produce either a new geometry 

or another datatype as a result

• ogcf:intersection returns a geometry produced by 

the spatial intersection of two geometries

• ogcf:distance produces xsd:double

Boolean topological tests of geometries 
Workshop Summary and Slides 29

SPARQL Query Results with Uniform 

Resource Identifiers (URI)

SPARQL Query –

Data Converted from The National Map

Geographic test areas from The National 

Map loaded as Semantic Web graphs.

Graphs currently available for 

query. 

Actual query text in SPARQL translated from 

“Find all tributaries of West Hunter Creek from 

the National Hydrography Dataset.”

Select one graph URI against which to run 

query.
30 Introduction to Geospatial Semantics and Technology Workshop Handbook

http://cegis.usgs.gov/rdf/nhd/featureID#_102216320

http://cegis.usgs.gov/rdf/nhd/featureID#_102216358

http://cegis.usgs.gov/rdf/nhd/featureID#_102217454

http://cegis.usgs.gov/rdf/nhd/featureID#_102216276

http://cegis.usgs.gov/rdf/nhd/featureID#_102216340

http://cegis.usgs.gov/rdf/nhd/featureID#_102216432

http://cegis.usgs.gov/rdf/nhd/featureID#_102216448

Query Result

Summary: Ontology is Expressed at 

Multiple Levels

Formalized logical structures of knowledge

Cognitive world views

Narratives and vocabularies of commonly 

shared words and meanings

Discourses about things

Applied representations based on concepts and 

their relations to each other 

A map is an ontology
Workshop Summary and Slides 31

On-line Demonstrations 

of Semantic Web sites

 Semantic Web ontology example

 File formats handle triples in various ways

 Geonames.org toponym ontology

 Basic Geo point coordinates

 DBpedia

 At the center of linkeddata.org

The USGS Project

Data Conversion from The National Map

Reuseable ODP for base data

Graphical output for topographic mapping
32 Introduction to Geospatial Semantics and Technology Workshop Handbook

Publicly Contributed Approaches

 GeoVoCamp

 Community-based approaches to controlled 

vocabulary development

 Communities of Practice

 Spatial Ontology Community of Practice (SOCoP)

 Open Ontology Repository Initiative
Workshop Summary and Slides 33

Accessing Linked Data Over the Internet 

Concepts introduced in the first hour are illustrated with examples using interactive data search, access, and download sites 

on the Internet. Sites to be visited are the Friend-of-a-Friend ontology, Geonames.org, and DBpedia, the Semantic Web version 

of Wikipedia. 

Applications of Semantic 

Technology

Wayne Viers

U.S. Department of the Interior

U.S. Geological Survey
34 Introduction to Geospatial Semantics and Technology Workshop Handbook

Outline

 Three organizations that effectively use RDF 

 FOAF: Example of RDF/XML generation

 Geonames: Example of Semantic Web

 DBpedia: Example of semantic querying 

Friend of a Friend

Goal: Create a web of machine readable pages 

describing people and the links between them

An ontology designed to allow portability of 

information between Web sites
Workshop Summary and Slides 35

Exercise 

 http://www.ldodds.com/foaf/foaf-a-matic

 We will use FOAF-a-Matic to show how one 

can easily create a FOAF RDF page 

 The triples are generated in RDF/XML, which 

is a syntax for representing RDF in XML 

 In this exercise, all triples have a common 

subject (you!) 

 This RDF/XML file can be added to your 

website to contribute to the Semantic Web 

Example FOAF Page

 A good example of a FOAF page is Tim 

Berners-Lee's

 Web page as seen in your browser

 http://www.w3.org/People/Berners-Lee/

 Embedded RDF/XML (Can be viewed as XML 

or using your browser’s View Source option.)

 http://www.w3.org/People/BernersLee/card.rdf
36 Introduction to Geospatial Semantics and Technology Workshop Handbook

Web page as seen in your browser

Embedded RDF/XML 
Workshop Summary and Slides 37

Geonames

Contains more than 10 million geographical 

names and more than 8 million unique 

features

More than 6.2 million Geonames toponyms

have a unique URL

Has a map service that can display the semantic 

information of displayed features

Exercise

 We will traverse Geonames semantic web to 

find the Washington Monument’s Wikipedia 

page starting from the National Mall’s 

semantic page.

 To do this we will be using an online 

application called XMLGrid
38 Introduction to Geospatial Semantics and Technology Workshop Handbook

xmlgrid.net

http://xmlgrid.net/

We will use the sites XML Viewer to look at 

RDF/XML embedded in the Geonames map

http://www.w3.org/People/BernersLee/card.rdf

Click the “By URL” box

Paste this link into the text box

Click submit, then “TextView”

Geonames Map

 http://www.geonames.org/6295630/

 Search for “National Mall” in the search bar in 

the top right

 Click the purple “S” symbol next to the 

National Mall in the list below the map

 Adjust your zoom level so that you have a 

good view of the National Mall and the 

Washington Monument.
Workshop Summary and Slides 39

 Click the National Mall marker on the map 

then click “semantic web rdf”

 Copy and paste the “nearbyFeatures” URL’s 

into xmlgrid as shown previously, until you 

find the Washington Monument’s RDF page.

 Finally find the link to the Wikipedia article 

(making sure you select the one with 

en.wikipedia for English)

Solution

Download Links

http://www.geonames.org/ontology/document

ation.html

Can download the entire RDF dataset but the 

file is very large (2.19 Gigabytes)
40 Introduction to Geospatial Semantics and Technology Workshop Handbook

Faceted Search 

DBpedia uses the semantic information from 

Wikipedia pages to perform faceted searches 

A facet is an aspect of a feature (elevation for 

example) 

Very useful for finding sets of data with specific 

qualities 

http://dbpedia.neofonie.de/browse

DBpedia

 DBpedia is a community effort to extract info 

from Wikipedia and make sophisticated 

queries against it.

 Dataset contains 3.64 million “things” and 

over 1 billion triples

 Triples built from info boxes in Wikipedia
Workshop Summary and Slides 41

Exercise

We will perform a spatial query using the 

faceted search to find... 

Cities 

With population between 40,000 and 65,000

And an elevation of 330 meters to 453 meters

Solution

Since city is not one of the visible facets, type 

city into the item type field on the left

Type 330 and 453 into the appropriate fields 

under the elevation facet

Finally enter 40000 and 65000 into the fields 

under the population total facet 
42 Introduction to Geospatial Semantics and Technology Workshop Handbook

RDF Web Browser

 OpenLink Virtuoso built-in Faceted Browser

 Virtuoso is a database engine made by 

OpenLink Software 

 The Virtuoso data base contains all the triples 

the browser searches over

 DBpedia’s triples can also be displayed in a 

browser in addition to being queried

 http://dbpedia.org/fct/
Workshop Summary and Slides 43

Download Links

 http://wiki.dbpedia.org/Downloads37

 Can download the DBpedia ontology in the 

OWL format (Web Ontology Language)

 Can be viewed in an ontology editor like 

Protégé.
44 Introduction to Geospatial Semantics and Technology Workshop Handbook

The USGS Approach to the Geospatial Semantic Web

In the second half of the workshop, the motivation for the USGS geospatial applications, including data integration and 

information retrieval lead to a discussion of approaches for enabling The National Map topographic data on the geospatial 

semantic web. A discussion of raster-based data semantics will be included.

Geospatial Semantic Technology 

A Case Study with USGS Data

U.S. Department of the Interior

U.S. Geological Survey
Workshop Summary and Slides 45

Outline

USGS Data Issues and Examples

The National Map

Semantics as a Solution

Building Semantics for Geospatial Data

Creating New Data with Semantics

Converting Legacy Data

Data Archive and Access

USGS Sample Data as RDF

Ontology for The National Map

Taxonomy of Domains

Topographic Vocabulary

Querying USGS Sample Data with SPARQL and GeoSPARQL

Using USGS Data with Other Data Sources

Linked Open Data

USGS Research Needs in Geosemantics

Future of Semantic Data at USGS

USGS Data Issues

Volume – multiple nationwide datasets at high resolution

Structure – variety of structures, vector and raster, 

many different formats

Semantics – various attribution and relation schemes, some 

feature-based, some layers

Integration of multiple datasets – for maximum utility all 

datasets should be able to be integrated to produce 

new data and information

Integration with data from users – users require the ability 

to add their data to USGS base datasets 
46 Introduction to Geospatial Semantics and Technology Workshop Handbook

Dataset Geometry/ 

Format

Attribution/ 

Scaling URL

National Hydrography Dataset (NHD) Vector Discrete/nominal http://viewer.nationalmap.gov/viewer/nhd.html?p=nhd

National Transportation Dataset Vector; tables Discrete/nominal http://viewer.nationalmap.gov/viewer/

http://gisdata.usgs.net/website/MRLC/viewer.htm

National Boundaries Dataset Vector Discrete/nominal http://viewer.nationalmap.gov/viewer/

National Structures Dataset Vector Discrete/nominal http://viewer.nationalmap.gov/viewer/

Geographic Names Information System (GNIS) Vector Discrete/nominal http://geonames.usgs.gov/domestic/download_data.htm

National Elevation Dataset (NED) Raster Continuous/ratio http://viewer.nationalmap.gov/viewer/

http://seamless.usgs.gov/website/seamless/viewer.htm

National Digital Orthophotos Raster Continuous/

 interval

http://www.ndop.gov/data.html; http://viewer.nationalmap.gov/viewer/

http://gisdata.usgs.net/website/MRLC/viewer.htm

National Land Cover Dataset (NLCD) Raster Discrete/nominal http://viewer.nationalmap.gov/viewer/

http://gisdata.usgs.net/website/MRLC/viewer.htm

Global Land Cover Dataset Raster Discrete/nominal http://landcover.usgs.gov/landcoverdata.php

LiDAR Point Continuous/ratio http://viewer.nationalmap.gov/viewer/

Satellite images Raster Continuous/interval http://earthexplorer.usgs.gov//; http://glovis.usgs.gov/

Hazards (Earthquakes, Volcanoes) Graphics Multiple forms http://earthquake.usgs.gov/hazards/; 

http://volcanoes.usgs.gov/activity/status.php

Minerals Vector; text Discrete/nominal http://mrdata.usgs.gov/; http://tin.er.usgs.gov/mrds/

http://tin.er.usgs.gov/geochem/; http://crustal.usgs.gov/geophysics/index.html

Energy Vector; databases Multiple forms http://energy.usgs.gov/search.html

Landscapes and Coasts Reports Discrete/nominal http://geochange.er.usgs.gov/info/holdings.html

Astrogeology Databases Discrete/nominal http://astrogeology.usgs.gov/DataAndInformation/

Geologic Map Database Vector; maps; text Discrete/nominal http://ngmdb.usgs.gov/

Geologic Data Digital Data Series Maps; tables Discrete/nominal http://pubs.usgs.gov/dds/dds-060/

National Water Information System Graphics; tables Continuous/ratio http://wdr.water.usgs.gov/nwisgmap/

Floods and High Flow Graphics; tables Continuous/ratio http://waterwatch.usgs.gov/new/index.php?id=ww

Drought Graphics; tables Continuous/ratio http://waterwatch.usgs.gov/new/index.php?id=ww

Monthly Stream Flow Graphics; tables Continuous/ratio http://waterwatch.usgs.gov/new/index.php?id=ww

Ground Water Vector; tables; Continuous/ratio http://waterdata.usgs.gov/nwis/gw/; http://groundwaterwatch.usgs.gov/

Water Quality Graphics Continuous/ratio http://waterdata.usgs.gov/nwis/qw/; http://waterwatch.usgs.gov/wqwatch/

Vegetation Characterization Vector; databases Multiple forms http://biology.usgs.gov/npsveg/

Wildlife Vector; text; 

video

Multiple forms http://www.nwhc.usgs.gov/

Examples of USGS Datasets

The National Map is a collaborative effort to 

improve and deliver topographic information for 

the Nation

The goal of The National Map is to become the 

Nation’s source for trusted, nationally consistent, 

integrated and current topographic information 

available online for a broad range of uses 

The National Map – http://nationalmap.gov/
Workshop Summary and Slides 47

The 8 Layers of The National Map

Datasets of The National Map

National Land Cover Dataset (1992, 2000, 2006)

National Elevation Dataset (1,1/3,1/9 arc-sec)

National Digital Orthophoto Dataset (multiple dates, multiple 

resolutions, 1 m, 1/3 m urban areas) 

National Hydrography Dataset (NHD) (Medium, High, Local 

resolution)

Geographic Names Information System (GNIS)

National Structures Dataset

National Boundaries Dataset (US, state, county, minor civil 

divisions, governmental units)

National Transportation Dataset (TIGER and others)
48 Introduction to Geospatial Semantics and Technology Workshop Handbook

Products of The National Map

Data display through The National Map viewer

http://viewer.nationalmap.gov/viewer/

Palanterra, joint development – National 

Geospacial-Intelligence Agency, ESRI, 

USGS

Display user selected The National Map data

Data download of eight layers

Mashups with other data using Keyhole 

Markup Language (KML)

Products of The National Map

US Topo – New 1:24,000-scale topographic maps in 

GeoPDF; Complete United States coverage 2009-

2011; available for free download from USGS 

Map Store, beginning revision on 3-year cycle –

Produce more than 100 maps per day

http://nationalmap.gov/ustopo/index.html

Digital, georeferenced versions of all previous 

topographic maps for a specified 7.5-minute area; 

more than 140,000 of the 180,000 total available

http://nationalmap.gov/historical/
Workshop Summary and Slides 49

Semantics as a Solution

Allows mapping of vocabularies among datasets

For example, vocabulary of USGS Digital Line 

Graph (DLG), DLG-Enhanced, Spatial Data 

Transfer Standard (SDTS), and others were 

used in building our semantic vocabulary

Allows data integration for query and mapping 

without reformatting data from various sources 

to a common format

Allows data use and applications not supported by 

GIS and GIS data models

Building Semantics for Geospatial Data

From scratch

Ontology

Collect data as RDF according to ontology

From Existing Data

Ontology

Convert existing data

Match data to ontology
50 Introduction to Geospatial Semantics and Technology Workshop Handbook

Creating New Data with Semantics

Develop ontology

Taxonomy of all features

Vocabulary with complete definitions

Make compatible with existing systems

Use standard vocabularies, if they exist

Compilation of all attributes and relations as 

RDF triples, i.e., attributes and relations 

become predicates 

Create data instances with geometry and 

ontology references

New Data Example using Protégé 

Create Turtle (.ttl) file in text editor including prefixes 

and OWL geometry and WKT properties (use 

template)

Open the .ttl file in Protégé and create classes

Add individuals (instances) and geometry

Add coordinates to annotations

Link feature instances to geometry objects
Workshop Summary and Slides 51

Converting Legacy Data 

Conversion possibilities and methods depend on 

 content and format of legacy data 

Feature-based data are usually converted easily 

 Features become subjects and objects, attributes 

 and relations become predicates 

Relational data can be used to automatically form 

 RDF triples 

 Rows are subjects 

 Columns are predicates 

 Cell values are objects

 Tables are classes

Conversion Example – Hydrography

## NHD feature

@prefix geo: <http://www.opengis.net/def/geosparql/> .

@prefix gnis: <http://cegis.usgs.gov/rdf/gnis/> .

@prefix nhd: <http://cegis.usgs.gov/rdf/nhd/> .

<http://cegis.usgs.gov/rdf/nhd/Features/flowline/166450429> a nhd:flowline;

 gnis:id <http://cegis.usgs.gov/rdf/gnis/Features/737907>;

 nhd:enabled "1";

 nhd:fCode <http://cegis.usgs.gov/rdf/nhd/fCode/46006>;

 nhd:fDate "Wed Oct 22 21:51:03 CDT 2008";

 nhd:fType <http://cegis.usgs.gov/rdf/nhd/fType/460>;

 nhd:flowDir <http://cegis.usgs.gov/rdf/nhd/flowDir/1>;

 nhd:lengthKM 0.044;

 nhd:reachCode <http://cegis.usgs.gov/rdf/nhd/reachCode/10290107000164>;

 nhd:resolution 2;

 nhd:shapeLength <0>;

 geo:hasGeometry <http://cegis.usgs.gov/rdf/nhd/Geometries/166450429> .

<http://cegis.usgs.gov/rdf/nhd/Geometries/166450429> a geo:Geometry;

 geo:asWKT "LINESTRING (-93.257456099019123 37.784990808016801 0,-

93.257691232352101 37.785210608016428 0,-93.25770129901872 

37.785318474682924 0)"^^<http://www.opengis.net/def/sf/wktLiteral> .

Define Prefixes

List predicates for 

nhd:flowline

Assign geometry 

as WKT
52 Introduction to Geospatial Semantics and Technology Workshop Handbook

Conversion Example – Transportation

## Transportation Feature

@prefix trans: <http://cegis.usgs.gov/rdf/trans/> .

@prefix transf: <http://cegis.usgs.gov/rdf/trans/Features/> .

@prefix transg: <http://cegis.usgs.gov/rdf/trans/Geometries/> .

@prefix geo: <http://www.opengis.net/def/geosparql/> .

<http://cegis.usgs.gov/rdf/trans/Features/22609575> a trans:roadSegment;

 trans:cffcCode "A31";

 trans:countyRoute "2-83";

 trans:dataSecurity "5";

 trans:distributionPolicy "E4";

 trans:fullStreetName "State Hwy N";

 trans:isOneWay false;

 trans:loadDate "Fri Jan 16 10:06:34 CST 2009“, "Sat Mar 28 10:33:21 CDT 2009";

 trans:roadClass <http://cegis.usgs.gov/rdf/trans/roadClass/10002>;

 trans:shapeLength 0.0126977422205;

 trans:sourceDataDesc "Attribute update from 2008 TIGER/Line Shapefiles Release";

 trans:sourceDatasetID "{1B7B3B39-5C38-4115-B429-5B0DD3DE0006}";

 trans:sourceOriginator "US Census Bureau";

 trans:stCoFIPSCode "29015“, "29085";

 trans:stateRoute "82,N";

 geo:hasGeometry <http://cegis.usgs.gov/rdf/trans/Geometries/22609575> .

<http://cegis.usgs.gov/rdf/trans/Geometries/22609575> a geo:Geometry;

 geo:asWKT "LINESTRING (-93.466183999736813 38.071580000280335,-93.478876999717102 

38.0719270002798)"^^<http://www.opengis.net/def/sf/wktLiteral> .

Define Prefixes

List predicates for 

trans:roadSegment

Assign geometry 

as WKT

Conversion Example – Raster Data

Requires identification of feature, attributes, 

and relationships in raster dataset

Create new feature with supporting 

characteristics in RDF

Attach geometry from raster image

Currently using WKT of minimum bounding 

rectangle (MBR) since GML only supports full 

coverage and MBR of raster objects
Workshop Summary and Slides 53

Meteor Crater

Example Feature from Raster Data

Meteor Crater – Shaded Relief Image
54 Introduction to Geospatial Semantics and Technology Workshop Handbook

Meteor Crater Attributes and Relationships

Feature Crater

Definition Circular-shaped depression at the summit of a volcanic cone or 

 on the surface of the land caused by the impact of a meteorite; 

 a manmade depression caused by an explosion (caldera, lua). 

Instance Meteor Crater 

Identifier GNIS ID 7945 

Attributes

Location UTM E 497,959.94 m N 3,876,020.68 m Zone 12

PLSS T 19 N, R 12 1/2 E, Section 13 and 24

MBR Max E 498,536.79 m Min E 497,317.62 m

Max N 3,876,632.29 m Min N 3,875,479.58

Elevation High 5,723 ft

Low 5,123 ft

Depth 600 ft

Shape Circular

Inner Diameter 0.50 mi (0.833 km)

Outer Diameter 0.75 mi (1.25 km)

Rim width 0.125 mi (0.2 km)

Contour at outer perimeter 5,600 ft

Contour at inner perimeter 5,180 ft

Relationships

Surrounded by roads

Adjacent to Museum Museum Name: Meteor Crater Museum

Near sand pits

Near well

Benchmarks on crater BM 5723 BM East 5706

Example of Meteor Crater in RDF/OWL
Workshop Summary and Slides 55

USGS Sample Data as RDF

Availability

Nine test areas – converted with precomputed spatial relations

New conversions of the nine areas with 

supporting ontology

Access to Pomme de Terre, MO watershed for 

this workshop

Data Archive and Access

Data are archived as RDF triplestore

Usually text-based (ASCII) triples (.ttl, RDF/XML, NTriples, ...)

Generates large data volumes, e.g., for Pomme de Terre 452,577 

triples, 43 Mb

Can be optimized by making binary, e.g., Parliament Triple Store

Data can be accessed by:

Query of SPARQL Endpoint (using SPARQL or GeoSPARQL)

Downloaded (remember large data volumes)

Accessed by URI for mashups with other data

Application access (concept of Open Linked Data)

DBpedia, browsing RDF data but not as queries

Access by URI from one dataset to another
56 Introduction to Geospatial Semantics and Technology Workshop Handbook

Ontology for The National Map

Taxonomy – hierarchy of feature classes

Vocabulary – feature names and definitions

Predicates – attributes and relationships

Instances – actual features with coordinates

All defined as OWL/RDF triples
Workshop Summary and Slides 57

Taxonomy of Feature Domains

Events

Divisions

Built-up areas

Ecological regime

Surface water

Terrain

Domains derived from ground surveys incorporated 

in DLG standards

Events

Risk Legacy

Hazard Hazard zone Military history

Archeological 

site 

Earthquake Incident

Historical 

marker Cliff dwelling

Flood Fire Tree Ruins

Area to be 

submerged Restricted area Wreck Pictograph
58 Introduction to Geospatial Semantics and Technology Workshop Handbook

Built up 

Built-up Category

Number of features 

in Category

Transportation and warehousing 60

Entertainment and recreation 26

Utilities 16

Resource extraction 13

Structure 12

Agriculture and fishing 11

Military 10

Communication 7

Waste management 7

Real estate 6

Place of worship 6

Manufacturing 4

Institutions 3

Burial grounds 3

Disturbed surface 3

Trade 3

Divisions

Civil Units Boundaries

Cadastral Nation Fenceline

Parcel Territory Hedge

Public Land Survey System Reservation Place

Land grant State Region

Homestead entry County Locale

Survey line Census Boundary line

Principle meridian State Boundary point

Baseline County Hydrologic unit

Survey point Census county division

Point monument Block group Shipping

Survey corner Block Lane

Government unit Tract Traffic separation scheme area

Municipality Special use zone Pilot water

City Time zone Roundabout

Town Nature reserve Inshore trafic zone

Villiage Survey line Exclusive Economic Zone
Workshop Summary and Slides 59

Natural/Artificial

hasPart: Bottom

Channel

Pond

Basin

Natural Artificial

Marine/Estuarine Freshwater Impounded Diked Channel Flow Control

Cove Watercourse Waterbody Reservoir Levee Siphon Weir

Foreshore Stream Lake Fish ladder Embankment Aqueduct Lock

Flat hasPart: Mouth Ice cap (regional) hasPart: Revetment Canal hasPart:Lock chamber

Ice field (regional) hasPart: Source Snow field (regional) Dam Flume Spillway

Marine Estuarine hasPart: Streambed Sastrugi (regional) Masonry shore Turning basin Jetty

Ocean Estuary hasPart: Streambanks Area of Complex Crib Breakwater

Sea Bay hasPart: Crossing Channels Pump

Gulf Inlet hasPart: Ford Backwater Gut

Submerged River Headwaters

Stream Creek Ice Mass

Shore Brook Lagoon

hasPart: Shingle Arroyo Rise

Shoreline Rapids Sink

Beach Bend

Ice flow (regional) Falls

Polyna (regional) Cascade

Breakers Waterfall

Reef Pool Innundation area

Spring

Mud pot

Geyser

Slope spring

Ice berg (regional)

hasPart: Iceberg tongue

Glacier (regional)

Crevasse (regional)

Wetland

Marsh

Swamp

Bog

Surface Water

Ecological Regime

Tundra

Desert

Grassland

Scrubland

Forest

Pasture

Agricultural land

Transition area

Nature reserve

Wetland
60 Introduction to Geospatial Semantics and Technology Workshop Handbook

Topographic Vocabulary

Examples from:

Events

Divisions

Built up

Ecological regime

Surface water

Terrain

Available from Ontology Project Webpage:

http://cegis.usgs.gov/ontology.html

Terrain includes 57 USGS landform features

Arch Divide Isthmus Ridge

Bar Drainage basin Karst Ridge line

Basin Dunes Lava Rock

Beach Fault Mineral pile Salt pan

Bench Flat Moraine Shaft

Cape Floodplain Mount Sink

Catchment Fracture Mountain range Summit

Cave Fumarole Peak Talus

Chimney Gap Peneplain Terrace

Cirque Glacial Peninsula Valley

Cliff Ground surface Pinnacle Volcano

Coast Hill Plain Wash

Continent Incline Plateau

Crater Island Quicksand

Delta Island cluster Reef
Workshop Summary and Slides 61

Ontologies –

Reuseable Vocabularies

@prefix geonames: <http://www.geonames.org/ontology#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix owl: <http://www.w3.org/2002/07/owl#> .

@prefix dcterms: <http://purl.org/dc/terms/>

@prefix dbpedia: <http://dbpedia.org/ontology/>

@prefix geo: <http://www.opengis.net/ont/OGC-GeoSPARQL/1.0/>

@prefix usgsTopo: <http://cegis.usgs.gov/TopoVocab/1.0/Terrain#> .

@prefix usgs: <http://cegis.usgs.gov/ontology/instances#> .

Built-up Vocabulary
62 Introduction to Geospatial Semantics and Technology Workshop Handbook

Terrain Vocabulary

Querying USGS Sample Data with 

SPARQL and GeoSPARQL
Workshop Summary and Slides 63

SPARQL Endpoint

A URL that allows access to an RDF triplestore

USGS SPARQL Endpoint for Topographic Data

http://usgs-ybother.srv.mst.edu:8890/parliament

Triplestore of USGS Data

Collection of RDF triples for our 9 research test 

areas.

Data will include names, hydrography, 

transportation, boundaries, structures, land 

cover, geomorphic features (from elevation) 

Accessible from SPARQL Endpoint

SPARQL queries use the ontology
64 Introduction to Geospatial Semantics and Technology Workshop Handbook

SPARQL Query Example

## SPARQL Query

PREFIX gnis: <http://cegis.usgs.gov/rdf/gnis/> .

PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

SELECT ?name ?mapName

WHERE

{

 ?x a gnis:gnisFeature .

 ?x rdfs:label ?name .

 ?x gnis:mapName ?mapName . 

}

Prefixes defining shorthand 

notation for URIs

Select clause defining variables 

(name and mapName in this 

case)

Match features and bind to variables

GeoSPARQL Query Example

## GeoSPARQL Query

 PREFIX gu: <http://cegis.usgs.gov/rdf/gu/>

 PREFIX geo: <http://www.opengis.net/def/geosparql/>

 PREFIX geof: <http://www.opengis.net/def/geosparql/function/>

 PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

 SELECT DISTINCT

 ?feature ?label

 WHERE {

 GRAPH <http://cegis.usgs.gov/rdf/> {

 

 # Find the WKT of Polk County

 ?polkCounty a gu:countyOrEquivalent ;

 gu:countyName "Polk" .

 ?polkCounty geo:hasGeometry ?polkGeo .

 ?polkGeo geo:asWKT ?polkWKT .

 # Match features that have a label, geo:Geometry and corresponding WKT

 ?feature geo:hasGeometry ?featGeo .

 ?featGeo geo:asWKT ?featWKT .

 ?feature rdfs:label ?label .

 

 # Find features contained by Polk County

 FILTER (geof:sfContains(?polkWKT, ?featWKT))

 }

 } LIMIT 50

Prefixes defining shorthand 

notation for URIs

Select clause defining variables 

(feature and label in this case)

Graph to be searched

Item to be searched for as Well 

Known Text, i.e., coordinates

Match features and bind to variables

Find features in Polk County
Workshop Summary and Slides 65

Using USGS Data with Other Data

Use of URIs in USGS data and URIs from other 

data provide access

User (computer program that does linking) must 

determine if data are compatible and make 

sense

USGS data join the Open Linked Data community

Linking Data

Data are linked across triplestores by URIs

USGS data

Geonames

URI

URI

Mashup
66 Introduction to Geospatial Semantics and Technology Workshop Handbook

Open Linked Data 

With more than 38 billion triples, the Open Linked Data cloud presents difficulties for visualization, use, and analysis. 

In this visualization, colors distinguish different themes (Dadzie and Rowe, 2011). 

USGS Research Needs in Geosemantics

Gazetteer access to geospatial features and data

Geospatial operators and ontology-driven processes that 

work with RDF

Direction, distance, overlay, buffer, generalization, 

mapping and display, geospatial analysis, visualization

terrain analysis, map algebra

Automated feature identification in raster data including 

unnamed features, e.g., using ontology design patterns 

and feature identification software 
Workshop Summary and Slides 67

Future of Semantic Data at USGS

Convert all data for the nine test areas

Build raster features, e.g., geomorphic named 

and unnamed

Design and build gazetteer interface

Design and build operators for semantic data

Convert all data for The National Map to 

semantics

Geospatial Semantic Technology 

A Case Study with USGS Data

U.S. Department of the Interior

U.S. Geological Survey
68 Introduction to Geospatial Semantics and Technology Workshop Handbook

Accessing Topographic Data Triples

The building of ontology for The National Map topographic data will be reviewed. Demonstrations of data from The 

National Map in triple format, accessible through the triple store endpoint and custom interface, will be shown by designing 

some commonly used SPARQL and GeoSPARQL types of queries. 

Geospatial Semantic Technology 

Hands-on with RDF and SPARQL

David Mattli <dmattli@usgs.gov>

U.S. Department of the Interior

U.S. Geological Survey
Workshop Summary and Slides 69

Outline

- Resource Description Framework

- Syntax

- RDF query examples

David Mattli <dmattli@usgs.gov>

Resource Description Framework

RDF models data using triples:

Subject-Predicate-Object
70 Introduction to Geospatial Semantics and Technology Workshop Handbook

The sky is blue.

 If we want to store the idea of a blue sky we 

choose a subject to represent “the sky”

 We select a predicate to represent “has the 

color”

 And we choose an object that represents the 

concept of “blue”

Triple Example

 “The sky is blue” in triple form might look like this:

<http://example.com/sky> <http://example.com/hasColor> <http://example.com/blue> .

 Each part is called an “RDF term”

 Each RDF term is separated by (at least) a space

 The triple ends with a period

Subject Predicate Object
Workshop Summary and Slides 71

URIs vs URLs

 Each of the terms from this example

<http://example.com/sky> <http://example.com/hasColor> <http://example.com/blue> .

are URIs. 

 They look very similar to URLs but the URIs used in 

RDF triples do not necessarily specify locations on the 

web

 URIs are used as unique names

Another example

@prefix gu: <http://cegis.usgs.gov/rdf/gu/> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdf:type gu:countyOrEquivalent .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdfs:label "Polk" .

Subjects Predicates Objects

 The first three lines declare “prefixes”

 A prefix is simply a shorthand for specifying 

URIs
72 Introduction to Geospatial Semantics and Technology Workshop Handbook

Another example

@prefix gu: <http://cegis.usgs.gov/rdf/gu/> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdf:type gu:countyOrEquivalent .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdfs:label "Polk" .

Subjects Predicates Objects

 Subjects are URIs

 URIs are enclosed by '<' and '>'

Another example

@prefix gu: <http://cegis.usgs.gov/rdf/gu/> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdf:type gu:countyOrEquivalent .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdfs:label "Polk" .

Subjects Predicates Objects

 Same “Subject Predicate Object” structure

 But now we have two triples

 The first describes a “type”

 The second describes the name or label of the 

feature
Workshop Summary and Slides 73

Another example

@prefix gu: <http://cegis.usgs.gov/rdf/gu/> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdf:type gu:countyOrEquivalent .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdfs:label "Polk" .

 The object of this triple is a URI using a prefix

 This URI is the name attached to the concept of 

a “county or equivalent”

 The second triple is a little different

Another example

@prefix gu: <http://cegis.usgs.gov/rdf/gu/> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdf:type gu:countyOrEquivalent .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdfs:label "Polk" .

Subjects Predicates Objects

 Predicates are also URIs

 The first three lines declare “prefixes”

 A prefix is simply a shorthand for specifying 

URIs
74 Introduction to Geospatial Semantics and Technology Workshop Handbook

Another example

@prefix gu: <http://cegis.usgs.gov/rdf/gu/> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdf:type gu:countyOrEquivalent .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdfs:label "Polk" .

 The object of a triple can be either a URI or a 

literal value

 The object of this triple is a string literal value

 Literal values can also be numbers, dates, 

geometries, etc

Another example

@prefix gu: <http://cegis.usgs.gov/rdf/gu/> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdf:type gu:countyOrEquivalent .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdfs:label "Polk" .

 The object of a triple can be either a URI or a 

literal value

 The object of this particular triple is a literal 

string value

 More literal values: numbers, dates, geometries
Workshop Summary and Slides 75

Questions?

@prefix gu: <http://cegis.usgs.gov/rdf/gu/> .

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdf:type gu:countyOrEquivalent .

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdfs:label "Polk" .

 Any questions about RDF, prefixes, or triples?

Triplestores

 A collection of triples is called a “graph”

 A program that stores graphs is called a 

“triplestore”

 Triplestores also execute queries on graphs

 The RDF query language is called SPARQL 

(sparkle)
76 Introduction to Geospatial Semantics and Technology Workshop Handbook

SPARQL

Here is an example query

 The SPARQL query language allows you query 

a triplestore for RDF terms(subjects, predicates 

or objects)

 Next we will examine the parts of this query

SELECT ?label

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

} 

SPARQL

 The first part of this query is the “SELECT 

clause”

 The “SELECT” is followed by a space 

separated list of “variables”

 A “variable” is a name prefixed by a '?' 

SELECT ?label

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

} 
Workshop Summary and Slides 77

SPARQL - Variables

 SPARQL variables are names that we give to 

the RDF terms we are querying for

 This query has one variable: ?label

 Variables are arbitrary identifiers

SELECT ?label

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

} 

SPARQL - Graph Patterns

 The second part of a SPARQL query is the 

“graph pattern”

 The “graph pattern” is a list of “triple patterns”

 In this example there are two triple patterns

SELECT ?label

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

} 
78 Introduction to Geospatial Semantics and Technology Workshop Handbook

SPARQL - Graph Patterns

 Each “triple pattern” has the now familiar 

Subject-Predicate-Object structure

 Except now one or more of the RDF terms may 

be replaced by a variable

SELECT ?label

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

} 

SPARQL - Graph Patterns

 A query is executed by searching a graph in a 

triplestore for possible substitutions for the 

variables in a “triple pattern”

 The highlighted pattern would match

<http://cegis.usgs.gov/rdf/gu/Features/758538> rdf:type 

gu:countyOrEquivalent .

but not

<http://cegis.usgs.gov/rdf/gu/Features/766568> rdf:type 

gu:minorCivilDivision .

SELECT ?label

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

} 
Workshop Summary and Slides 79

SPARQL - Graph Patterns

 And this pattern would match any ?feature with 

an rdfs:label

SELECT ?label

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

} 

SPARQL - Graph Patterns

 Because the same ?feature variable is used in 

both triple patterns this query searches for the 

label of a subject that has the type 

“gu:countyOrEquivalent”

SELECT ?label

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

} 
80 Introduction to Geospatial Semantics and Technology Workshop Handbook

SPARQL

 Next we will try and execute this SPARQL 

query.

 Any questions?

SELECT ?label

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

} 

SPARQL Query

 Try executing a SPARQL query

 Enter this URL in your web browser:

http://usgs-ybother.srv.mst.edu/viz/

You should see something like this:
Workshop Summary and Slides 81

SPARQL Query

http://usgs-ybother.srv.mst.edu/viz/

 Click on the “SPARQL Query” button

SPARQL Query

http://usgs-ybother.srv.mst.edu/viz/

 You should see a page like this:
82 Introduction to Geospatial Semantics and Technology Workshop Handbook

SPARQL Query

http://usgs-ybother.srv.mst.edu/viz/

 Now enter the query we saw earlier

SPARQL Query

http://usgs-ybother.srv.mst.edu/viz/

 And click “Submit Query” when it is all entered
Workshop Summary and Slides 83

SPARQL Query

http://usgs-ybother.srv.mst.edu/viz/

 Once the dialog closes, click on “Tabular Results”

SPARQL Query

http://usgs-ybother.srv.mst.edu/viz/

 The “Tabular Results” dialog should look like:
84 Introduction to Geospatial Semantics and Technology Workshop Handbook

Any Questions?

http://usgs-ybother.srv.mst.edu/viz/

 The “Tabular Results” dialog should look like:

GeoSPARQL

 GeoSPARQL is an extension of SPARQL 

 Associates a Geometry with a feature using 

geo:hasGeometry

<http://cegis.usgs.gov/rdf/nhd/Features/102204610> rdf:type nhd:flowline .

<http://cegis.usgs.gov/rdf/nhd/Features/102204610> geo:hasGeometry 

<http://cegis.usgs.gov/rdf/nhd/Geometries/102204610> .

<http://cegis.usgs.gov/rdf/nhd/Geometries/102204610> rdf:type geo:Geometry .

<http://cegis.usgs.gov/rdf/nhd/Geometries/102204610> geo:asWKT 

"LINESTRING (-93.387722032150236 38.166983407423857 0,-93.387682298816969 

38.167539207422976 0,-93.388619432148857 38.168476474088209 0,-93.391319032144679 

38.169734874086259 0,-93.396768432136241 38.171924274082869 0,-93.398635898799967 

38.172490274081952 0,-93.398990298799447 38.17260060741512 0,-93.399145698799202 

38.172711207414977 0,-93.399287298798981 38.172574207415153 0,-93.399409832132108 

38.172571607415193 0)"^^<http://www.opengis.net/def/sf/wktLiteral> .
Workshop Summary and Slides 85

GeoSPARQL

 Now we will query for the geometries of the 

counties from the last SPARQL Query

SELECT ?label ?wkt

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

 ?feature geo:hasGeometry ?g .

 ?g geo:asWKT ?wkt . 

} 

GeoSPARQL

 Here we have added a new SELECT variable 

called ?wkt

 And we have added two triple patterns

SELECT ?label ?wkt

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

 ?feature geo:hasGeometry ?g .

 ?g geo:asWKT ?wkt . 

} 
86 Introduction to Geospatial Semantics and Technology Workshop Handbook

GeoSPARQL

 The first triple pattern searches for a 

geo:Geometry using the geo:hasGeometry 

predicate

 This geo:Geometry is bound to the variable: ?g

SELECT ?label ?wkt

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

 ?feature geo:hasGeometry ?g .

 ?g geo:asWKT ?wkt . 

} 

GeoSPARQL

 The last triple pattern searches for the WKT(a 

geometry serialization) of the geo:Geometry

 The WKT is bound to the variable ?wkt

SELECT ?label ?wkt

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

 ?feature geo:hasGeometry ?g .

 ?g geo:asWKT ?wkt . 

} 
Workshop Summary and Slides 87

GeoSPARQL example

 Open your web browser to the page:

http://usgs-ybother.srv.mst.edu/viz/

And click on the “SPARQL Query” button

GeoSPARQL example

 http://usgs-ybother.srv.mst.edu/viz/

 Enter the query:

SELECT

?label ?wkt

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label ?label .

 ?feature geo:hasGeometry ?g .

 ?g geo:asWKT ?wkt .

}
88 Introduction to Geospatial Semantics and Technology Workshop Handbook

GeoSPARQL Result

Questions?

FILTER Statements

 Graph patterns allow us to match RDF terms

 But can we remove matches from the results?

 http://usgs-ybother.srv.mst.edu/viz/

 The FILTER statement restricts matches to those that 

satisfy the enclosed expression.

SELECT ?subject ?wkt

WHERE {

 ?subject rdf:type nhd:area .

 ?subject nhd:areaSqKM ?a .

 ?subject geo:hasGeometry ?geo .

 ?geo geo:asWKT ?wkt .

 FILTER(?a > 1.0)

}

 
Workshop Summary and Slides 89

SELECT ?subject ?wkt

WHERE {

 ?subject rdf:type nhd:area .

 ?subject nhd:areaSqKM ?a .

 ?subject geo:hasGeometry ?geo .

 ?geo geo:asWKT ?wkt .

 FILTER(?a > 1.0)

} Try the same query with FILTER(?a > 10.0) 

FILTER statements

The GeoSPARQL standard defines vocabulary for 

topographical relations.

http://usgs-ybother.srv.mst.edu/viz/

SELECT ?wkt

WHERE {

 ?feature rdf:type gu:countyOrEquivalent .

 ?feature rdfs:label "Polk" .

 ?feature geo:hasGeometry ?g .

 ?g geo:asWKT ?county_wkt .

 ?flowline rdf:type nhd:flowline .

 ?flowline geo:hasGeometry ?g2 .

 ?g2 geo:asWKT ?wkt .

 FILTER(geof:sfContains(?county_wkt, ?wkt)) 

} 
90 Introduction to Geospatial Semantics and Technology Workshop Handbook

Federated Queries

With RDF you are not limited to querying the 

data in your own triplestore

Federated SPARQL queries tell a triplestore to 

query other servers over a network 

Federated Query

SELECT ?picture ?wkt

WHERE {

 ?feature rdfs:label “Pomme de Terre Lake” .

 ?feature geo:hasGeometry ?g .

 ?g geo:asWKT ?wkt .

 

 SERVICE <http://dbpedia.org/sparql> {

 GRAPH <http://dbpedia.org> {

 ?dbfeature rdfs:label “Pomme de Terre Lake”@en .

 ?dbfeature rdf:type category:ReservoirsInMissouri .

 ?dbfeature foaf:depiction ?picture .

 } 

 } 

}

 http://usgs-ybother.srv.mst.edu/viz
Workshop Summary and Slides 91

Federated Query

SELECT ?picture ?wkt

WHERE {

 ?feature rdfs:label “Pomme de Terre Lake” .

 ?feature geo:hasGeometry ?g .

 ?g geo:asWKT ?wkt .

 

 SERVICE <http://dbpedia.org/sparql> {

 GRAPH <http://dbpedia.org> {

 ?dbfeature rdfs:label “Pomme de Terre 

Lake”@en .

 ?dbfeature rdf:type 

category:ReservoirsInMissouri .

 ?dbfeature foaf:depiction ?picture .

 } 

 } 

}

Questions?
92 Introduction to Geospatial Semantics and Technology Workshop Handbook

The SOCoP Open Ontology Repository (OOR)

In this session we will demonstrate the use of a geospatial open ontology repository (OOR). The OOR was developed by 

the Spatial Ontology Community of Practice (SOCoP, www.socop.org) to help interdisciplinary conversations and collaboration

between geoscientists and ontologists. We will illustrate searching and browsing geospatial ontologies (such as GeoSPARQL), 

how to map terms in different ontologies, how to visualize stored ontologies, and how to add an ontology to the repository. We 

will discuss plans for federation with other repositories and its interoperation with SPARQL endpoints.

Meteor Crater Ontology

@prefix : <http://cegis.usgs.gov/Ontology/Instances#>.

@prefix geo: <http://www.opengis.net/def/geosparql/>.

@prefix ogc: <http://www.opengis.net/>.

@prefix owl: <http://www.w3.org/2002/07/owl#>.

@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>.

@prefix xml: <http://www.w3.org/XML/1998/namespace>.

@prefix xsd: <http://www.w3.org/2001/XMLSchema#>.

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>.

@prefix usgs: <http://cegis.usgs.gov/Ontology/>.

@prefix dbpedia: <http://dbpedia.org/ontology/>.

@prefix dcterms: <http://purl.org/dc/terms/>.

@prefix gn: <http://www.geonames.org/ontology#>.

@prefix usgsgeo: <http://cegis.usgs.gov.Ontology/geometry/>.

<http://cegis.usgs.gov/Ontology/Instances>

 rdf:type owl:Ontology.

#################################################################

#

# Annotation properties

#

#################################################################

dcterms:description

 rdf:type owl:AnnotationProperty.

dcterms:identifier

 rdf:type owl:AnnotationProperty.

geo:asWKT

 rdf:type owl:AnnotationProperty.

geo:hasGeometry

 rdf:type owl:AnnotationProperty.

#################################################################

#

# Data Properties

#

#################################################################

usgsgeo:hasUTM

 rdf:type owl:DatatypeProperty.
Workshop Summary and Slides 93

dbpedia:MaximumElevation

 rdf:type owl:DatatypeProperty.

dbpedia:MaximumDepth

 rdf:type owl:DatatypeProperty.

usgsgeo:hasInnerDiameter

 rdf:type owl:DatatypeProperty.

dbpedia:MinimumElevation

 rdf:type owl:DatatypeProperty.

usgsgeo:hasPLSS

 rdf:type owl:DatatypeProperty.

usgsgeo:hasMBR

 rdf:type owl:DatatypeProperty.

usgsgeo:hasWidth

 rdf:type owl:DatatypeProperty.

usgsgeo:hasOuterDiameter

 rdf:type owl:DatatypeProperty.

usgs:hasElevation

 rdf:type owl:DatatypeProperty.

#################################################################

#

# Object Properties

#

#################################################################

usgs:hasVerticalControlAccuracy

 rdf:type owl:ObjectProperty.

usgs:hasHorizontalControlAccuracy

 rdf:type owl:ObjectProperty.

usgs:hasMonument

 rdf:type owl:ObjectProperty.

usgs:hasName

 rdf:type owl:ObjectProperty.

usgs:hasRelationshipToSurface

 rdf:type owl:ObjectProperty.

usgsgeo:hasShape

 rdf:type owl:ObjectProperty.

usgs:hasOperationalStatus

 rdf:type owl:ObjectProperty.

usgs:hasProduct

 rdf:type owl:ObjectProperty.
94 Introduction to Geospatial Semantics and Technology Workshop Handbook

gn:nearbyFeatures

 rdf:type owl:ObjectProperty.

gn:locatedIn

 rdf:type owl:ObjectProperty.

#################################################################

#

# Classes

#

#################################################################

usgs:Building

 rdf:type owl:Class.

usgs:ControlStation

 rdf:type owl:Class.

usgs:MeteoricCrater

 rdf:type owl:Class.

usgs:Road

 rdf:type owl:Class.

usgs:Well

 rdf:type owl:Class.

usgs:Quarry

 rdf:type owl:Class.

geo:Geometry

 rdf:type owl:Class.

usgs:MineShaft

 rdf:type owl:Class.

#################################################################

#

# Individuals

#

#################################################################

:7945

 rdf:type usgs:MeteoricCrater,

 owl:NamedIndividual;

 dcterms:identifier “7945”^^xsd:string;

 rdfs:comment “A meteor crater”^^xsd:string;

 dcterms:description “Circular-shaped depression on the surface of the 

land caused by the impact of a meteorite”^^xsd:string;

 rdfs:label “Meteor Crater”^^xsd:string;

 usgs:hasName usgs:CharacterIdentifier;

 gn:nearbyFeatures :8763,

 :5723,

 :5123,

 :e5706,

 :1649,
Workshop Summary and Slides 95

 :1652,

 :3876,

 :9763,

 :1552;

 geo:hasGeometry :7945geo.

:3876

 rdf:type usgs:Road,

 owl:NamedIndividual;

 usgs:hasName usgs:CharacterIdentifier;

 rdfs:label “Crater Road”^^xsd:string;

 geo:hasGeometry :3876geo.

:8763

 rdf:type usgs:Building,

 owl:NamedIndividual;

 usgs:hasName usgs:CharacterIdentifier;

 rdfs:label “Meteor Crater Museum”^^xsd:string;

 geo:hasGeometry :8763geo.

:1649

 rdf:type usgs:Quarry,

 owl:NamedIndividual;

 usgs:hasProduct usgs:Sand;

 usgs:hasName usgs:unknown;

 usgs:hasOperationalStatus usgs:unknown;

 geo:hasGeometry :1649geo.

:1652

 rdf:type usgs:Quarry,

 owl:NamedIndividual;

 usgs:hasProduct usgs:Sand;

 usgs:hasOperationalStatus usgs:unknown;

 usgs:hasName usgs:unknown;

 geo:hasGeometry :1652geo.

:9763

 rdf:type usgs:Well,

 owl:NamedIndividual;

 usgs:hasProduct usgs:water;

 usgs:hasOperationalStatus usgs:Operational;

 usgs:hasName usgs:unknown;

 geo:hasGeometry :9863geo.

:5123

 rdf:type usgs:ControlStation,

 owl:NamedIndividual;

 gn:locatedIn :7945;

 usgs:hasElevation “5123 ft.”;

 usgs:hasName usgs:CharacterIdentifier;

 rdfs:label “USGS Benchmark 5123”^^xsd:string;

 usgs:hasVerticalControlAccuracy usgs:3rdOrderOrBetter;

 usgs:hasRelationshipToSurface usgs:ExposedAtSurface;

 usgs:hasMonument usgs:Tablet;

 geo:hasGeometry :5123geo.
96 Introduction to Geospatial Semantics and Technology Workshop Handbook

:5723

 rdf:type usgs:ControlStation,

 owl:NamedIndividual;

 usgs:hasElevation “5723 ft.”;

 usgs:hasName usgs:CharacterIdentifier;

 rdfs:label “USGS Benchamrk BM5723”^^xsd:string;

 usgs:hasHorizontalControlAccuracy usgs:3rdOrderOrBetter;

 usgs:hasRelationshipToSurface usgs:ExposedAtSurface;

 usgs:hasMonument usgs:NoTablet;

 geo:hasGeometry :5723geo.

:e5706

 rdf:type usgs:ControlStation,

 owl:NamedIndividual;

 usgs:hasElevation “5706 ft.”;

 usgs:hasName usgs:CharacterIdentifier;

 rdfs:label “USGS Benchmark BM East 5706”^^xsd:string;

 usgs:hasHorizontalControlAccuracy usgs:3rdOrderOrBetter;

 usgs:hasRelationshipToSurface usgs:ExposedAtSurface;

 usgs:hasMonument usgs:NoTablet;

 geo:hasGeometry :e5706geo.

:1497

 rdf:type usgs:MineShaft,

 owl:NamedIndividual;

 gn:locatedIn :7945;

 usgs:hasOperationalStatus usgs:Abandoned;

 usgs:hasName usgs:unknown;

 geo:hasGeometry :1497geo.

:1523

 rdf:type usgs:MineShaft,

 owl:NamedIndividual;

 gn:locatedIn :7945;

 usgs:hasOperationalStatus usgs:Abandoned;

 usgs:hasName usgs:unknown;

 geo:hasGeometry :1523geo.

:1529

 rdf:type usgs:MineShaft,

 owl:NamedIndividual;

 gn:locatedIn :7945;

 usgs:hasOperationalStatus usgs:Abandoned;

 usgs:hasName usgs:unknown;

 geo:hasGeometry :1529geo.

:1546

 rdf:type usgs:MineShaft,

 owl:NamedIndividual;

 gn:locatedIn :7945;

 usgs:hasOperationalStatus usgs:Abandoned;

 usgs:hasName usgs:unknown;

 geo:hasGeometry :1546geo.

:1552

 rdf:type usgs:MineShaft,
Workshop Summary and Slides 97

 owl:NamedIndividual;

 usgs:hasOperationalStatus usgs:Abandoned;

 usgs:hasName usgs:unknown;

 geo:hasGeometry :1552geo.

:7945geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 usgsgeo:hasWidth “0.2Km”;

 usgsgeo:hasOuterDiameter “1250 m”;

 dbpedia:MinimumElevation “5123 ft.”;

 dbpedia:MaximumElevation “5723 ft.”;

 dbpedia:MaximumDepth “600 ft.”;

 usgsgeo:hasInnerDiameter “833 m”;

 usgsgeo:hasShape usgsgeo:Circular;

 usgsgeo:hasUTM “E 497959.94m N 3876020.68m Zone12”;

 usgsgeo:hasMBR “Max E 489536.79m Min E 497317.62m Max N 3876632.29m Min 

N 3875479.58m”;

 usgsgeo:hasPLSS “T 19 N, R 12 1/2 E, Section 13 and 24”;

 geo:asWKT “POINT -111.02236372362403 35.02684835590344”.

:1649geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT -111.02334 35.02136”.

:1652geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT -111.02600 35.02056”.

:3876geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “”.

:5123geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT -111.02314 35.02808”.

:5723geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT -111.02913 35.02945”.

:8763geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT -111.02149 35.03270”.

:9863geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT -111.02328 35.03655”.
98 Introduction to Geospatial Semantics and Technology Workshop Handbook

:e5706geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT -111.01656 35.02470”.

:1497geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT (-111.02309 35.02726)”.

:1523geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT (-111.02271 35.02750)”.

:1529geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT (-111.02122 35.02787)”.

:1546geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT (-111.02225 35.02692)”.

:1552geo

 rdf:type geo:Geometry,

 owl:NamedIndividual;

 geo:asWKT “POINT (-111.02242 35.01962)”.

usgs:3rdOrderOrBetter

 rdf:type owl:NamedIndividual.

usgs:CharacterIdentifier

 rdf:type owl:NamedIndividual.

usgs:ExposedAtSurface

 rdf:type owl:NamedIndividual.

usgs:Tablet

 rdf:type owl:NamedIndividual.

usgs:Sand

 rdf:type owl:NamedIndividual.

usgs:Abandoned

 rdf:type owl:NamedIndividual.

usgs:Water

 rdf:type owl:NamedIndividual.

usgs:Unknown

 rdf:type owl:NamedIndividual.

usgs:NoTablet

 rdf:type owl:NamedIndividual.
Internet Resources 99

Internet Resources

Semantic Web. World Wide Web Consortium (W3C). 

http://www.w3.org/standards/semanticweb/

Standards and Shared Vocabularies

Basic Geo (WGS84 lat/long) Vocabulary 

http://www.w3.org/2003/01/geo/.

CIDOC—Conceptual Reference Model 

http://www.cidoc-crm.org/index.html

DOLCE—Descriptive Ontology for Linguistic and Cognitive Engineering 

http://www.loa.istc.cnr.it/DOLCE.html

GeoSPARQL Users Guide 2012

http://ontolog.cim3.net/cgi-bin/wiki.pl?InteropProject/Geosparql_USER_GUIDE_2012

Glossary of Semantic Web Terms 

https://wiki.base22.com/display/btg/Glossary+of+Semantic+Web+Terms#GlossaryofSemanticWebTerms-T

Publishing Vocabularies

http://www.w3.org/TR/swbp-vocab-pub/

Resource Description Framework (RDF) Primer 

http://www.w3.org/TR/2004/REC-rdf-primer-20040210/

SPARQL Protocol and RDF Query Language (SPARQL) 

http://www.w3.org/TR/rdf-sparql-query/.

Turtle—Terse RDF Triple Language 

http://www.w3.org/TR/2011/WD-turtle-20110809/

WordNet—WordNet, A lexical database for English. Princeton University. 

http://wordnet.princeton.edu/.

Software and Technology Products

AllegroGraph RDFStore

http://www.franz.com/agraph/

Jena

http://openjena.org/wiki/TDB

Oracle

http://www.oracle.com/technetwork/database/options/semantic-tech/index.html

Parliament

http://parliament.semwebcentral.org/

Protégé Ontology Editor

http://protege.stanford.edu/
100 Introduction to Geospatial Semantics and Technology Workshop Handbook

Semantic Web Development Tools

http://www.w3.org/2001/sw/wiki/Tools

SemWebCentral

http://www.semwebcentral.org/

TopBraid Composer

http://www.topquadrant.com/products/TB_Composer.html

Ontologies and Linked Data

OpenCyc

http://sw.opencyc.org/

DBpedia

http://dbpedia.org/About

 

e-Government

http://oegov.org/

Freebase

http://www.freebase.com/

Linked Open Data Initiative

http://linkeddata.org/

LinkedGeoData

http://linkedgeodata.org/About

NeoGeo Vocabulary 

http://geovocab.org/doc/survey.html

OntologyDesignPatterns.org 

http://ontologydesignpatterns.org/wiki/Main_Page.

Open Ontology Repository Initiative 

http://OpenOntologyRepository.org

Semantic MediaWiki

http://mapping.referata.com/wiki/Semantic_Maps

Semantic Web

http://semanticweb.org/wiki/Main_Page

Semantic Web for Earth and Environmental Terminology (SWEET) Ontologies 

http://sweet.jpl.nasa.gov/

U.S. Geological Survey Triple Data

http://usgs-ybother.srv.mst.edu:8890/parliament

Online Tutorials

Information Semantics 101: Semantics, Semantic Models, Ontologies, Knowledge Representation, and the Semantic Web

http://c4i.gmu.edu/OIC09/workshop.php
Internet Resources 101

Introduction to Ontologies and Semantic Web [On-line] 

http://www.obitko.com/tutorials/ontologies-semantic-web/

Introduction to Ontologies and Semantic Technologies

http://stids.c4i.gmu.edu/STIDS2011/agenda2011.php

SPARQL By Example, A Tutorial

http://www.cambridgesemantics.com/semantic-university/sparql-by-example

Ontology Communities, Professional Organizations, and Workshop Events 

International Association for Ontology and its Applications (IOAO) 

http://www.iaoa.org/

The 11th International Semantic Web Conference 

http://iswc2012.semanticweb.org/

Terra Cognita 2011 Workshop 

http://asio.bbn.com/terracognita2011

Semantic Technology for Intelligence, Defense, and Security (STIDS) 

http://stids.c4i.gmu.edu/

Federation of Earth Science Information Partners (ESIP) Semantic Web Cluster 

http://wiki.esipfed.org/index.php/Semantic_Web

Spatial Ontology Community of Practice (SOCoP)

http://www.socop.org/

Ontolog collaborative work environment

http://ontolog.cim3.net/

Research Groups and Programs of Study

GeoLinkedData.es, Ontology Engineering Group

http://geo.linkeddata.es/web/guest

Laboratory for Applied Ontology

http://www.loa.istc.cnr.it/

Tetherless World Constellation

http://tw.rpi.edu/web/TWC

Muenster Semantic Interoperability Lab 

http://musil.uni-muenster.de/

Blogs 

Data.gov/semantic

http://www.data.gov/communities/node/116/blogs

John Goodwin

http://www.johngoodwin.me.uk/
102 Introduction to Geospatial Semantics and Technology Workshop Handbook

Suggested Literature

Semantic and Geospatial Semantic Web

Berners-Lee, T., Hendler, J., and Lassila, O., 2001, The Semantic Web: Scientific American, May 2001, p. 35-43. 

Egenhofer, M.J., 2002, Toward the Semantic Geospatial Web, in 10th ACM International Symposium on Advances in Geographic Information Systems (ACM-GIS), November 8-9, 2002. McLean, Va., p. 1–4. 

Hitzler, P., and van Harmelen, F., 2010, A Reasonable Semantic Web. Semantic Web—Interoperability, Usability, Applicability: 

Semantic Web, IOS Press, p. 39-44. (Also available at http://dx.doi.org/ 10.3233/SW-2010-0010.)

Kuhn, W., 2005, Geospatial Semantics—Why, of what, and how? Journal on Data Semantics III, v. 3534, p. 1–24. 

Noy, N.F., and McGuinness, D.L., 2001, Ontology Development 101—A guide to creating your first ontology: Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880, 

Stanford University. 

Geospatial Semantics and Ontology

Arpinar, I.B., Sheth, A., Ramakrishnan, C., Usery, E.L., Azami, M., and Kwan, M., 2004, Geospatial ontology development and 

semantic analytics in Wilson, J.P., and Forthingham, A.S., eds., Handbook of Geographic Information Science, Blackwell 

Publishing. 

Corcho, O., Fernández-López, M., and Gómez-Pérez, A., 2003, Methodologies, tools and languages for building ontologies. 

Where is their meeting point? Data and Knowledge Engineering v. 46, p. 41–64. 

Frank, A.U., 2001, Tiers of ontology and consistency constraints in geographic information systems: International Journal of 

Geographic Information Science, v. 15, no. 7, p. 667–678.

Gangemi, A., and Presutti, V., 2009, Ontology design patterns, in Staab, S., and Studer, R., eds., Handbook of Ontologies (2d 

ed.): Berlin, Springer.

Kokla, M., and Kavouras, M., 2001, Fusion of top-level and geographical domain ontologies based on context formation and 

complementarity: International Journal of Geographic Information Science, v. 15, no. 7, p. 679–687. 

Kuhn, W., 2001, Ontologies in support of activities in geographical space: International Journal of Geographic Information 

Systems, v.15, no. 7, p. 613-631.

Lutz, M., and Klien, E., 2006, Ontology-based retrieval of geographic information: International Journal of Geographical Information Science, v. 20, no. 3, p.233–260. 

Perry, M., Sheth, A., Arpinar, I.B., and Hakimpour, F., 2009, Geospatial and temporal semantic analytics, in, Karimi, H.A., ed., 

Handbook of Research on Geoinformatics: Hershey, Pa., Information Science Reference, p.161–170. 

Schuurman, N., and Leszczynski, A., 2006, Ontology-based metadata: Transactions in GIS, v. 11, p. 709–26.

Sen, S., 2008, User of Affordances in Geospatial Ontologies, in Proceedings of the 2006 International Conference on Towards 

affordance-based robot control, no. 4760, Springer-Verlag, p. 122–139.

Staab, S., and Studer, R., eds., 2004, The Handbook on Ontologies: Berlin, Springer-Verlag, 660 p.
Suggested Literature 103

Taxomony, Mereotopology and Other Relations

Behr, R,. and Schneider, M., 2001, Topological relations of complex points and complex regions, in International Conference 

on Conceptual Modeling, 20th, Yokohama, Japan, 2001, Lecture Notes in Computer Science 2224, Berlin, Springer-Verlag 

p. 56–69.

Casati, R., and Varzi, A., 1999, Parts and places, the structures of spatial representation: Cambridge, Mass., Massachusetts Institute of Technology Press, 238 p.

Green, R., Bean, C.A., and Myaeng, S.H., eds., 2002,The semantics of relationships—An interdisciplinary perspective: Dordrecht, Kluwer, 223 p. 

Perry, M., and Herring, J., eds., 2012, GeoSPARQL—A geographic query language for RDF data: Open Geospatial Consortium 

OGC 11-052r4. (Also available at http://www.w3.org/2011/02/GeoSPARQL.pdf.)

Welty, C., and Guarino, N., 2001, Supporting ontological analysis of taxonomic relations: Data and Knowledge Engineering, 

v. 39, p. 51–74. 

Linked Data and Social Networking

Cucchiarelli, A., and D’Antonio, F., and Velardi, P., 2011, Semantically interconnected social networks: Social Network Analysis 

and Mining, Springer, p. 69–95. (Also available at http://www.springerlink.com/content/p8p809h04527n88q/.)

Gruber T., 2007, Ontology of folksonomy—A Mash-up of apples and oranges: International Journal on Semantic Web and Information Systems, v. 3, no. 1, 11 p. (Also available at http://tomgruber.org/writing/ontology-of-folksonomy.htm.)

Hahmann, S., and Burghardt, D., 2010, Connecting LinkedGeoData and Geonames in the spatial semantic Web, in Proceedings of the 6th International GIScience Conference, Zurich, Switzerland, 2010. (Also available at http://kartographie.geo.

tu-dresden.de/aigaion/attachments/Hahmann_Burghardt_LinkedGeoData_Geonames.pdf-c9d454e361d4e3188da338f4

ffc66864.pdf.) 

Application Engineering

Allemang, D., and Hendler, J., 2008, Semantic Web for the working ontologist, effective modeling in RDFS and OWL: Burlington, Mass., Morgan Kaufmann, 330 p.

Dago, E., Blomqvist, E., Gangemi, A., Montiel, E., Nikitina, N., Presutti, V., and Villazon-Terrazas, B., 2005, Pattern based 

ontology design—Methodology and software support—NeOn—Lifecycle Support for Networked Ontologies: Integrated Project (IST-2005-027595). (Also available at http://www.neon-project.org/nw/images/5/5c/NeOn_2010_D252.pdf.)

Guarino, N., and Welty, C., 2002, Evaluating ontological decisions with OntoClean: Communications of the ACM, v. 45, no. 2, 

p. 61–65. 

Pulido, J.R.G., Ruiz, M.A.G., Herrera, R., Cabello, E., Legrand, S., and Elliman, D., 2006, Ontology languages for the semantic 

web—A never completely updated review: Knowledge-Based Systems, v. 19, no. 7, p. 489–497.

Geography, GIScience, and GeoInformatics

Agarwal, P., 2005, Ontological considerations in GIScience: International Journal of Geographical Information Science, v. 

19, no. 5, p. 501–536.

Couclelis, H., 2010, Ontologies of geographic information: International Journal of Geographical Information Science, v. 24, 

no. 12, p. 1,785–1,809. 

Fonseca, F., Egenhofer, M., Davis, C. and Camara, G., 2002, Semantic granularity in ontology–driven geographic information 

systems: Annals of Mathematics and Artificial Intelligence, v. 36, p. 121–151. 
104 Introduction to Geospatial Semantics and Technology Workshop Handbook

Frank, A.U., 2003, Ontology for spatio-temporal databases, chap. 2 of Spatiotemporal databases—The Chorochronos Approach: 

Koubarakis, M. , Sellis, T.K. , Frank, A.U., Grumbach, S., Güting, R.H., Jenson, C.S., Lorentzos, N., Manolopoulos, Y., 

Nardelli, E., Pernici, B., Schek, H-J., Scholl, M., Theodoulidis, B., and Tryfona, N., eds., Springer, ser. Lecture Notes in Computer Science, v. 2520, 352 p. 

Painho, M., Curvelo, P., and Jovani, I., 2007, An ontological-based approach to Geographic Information System curricula 

design: The European Information Society, Lecture Notes in Geoinformation and Cartography, part 1, p. 15–34. 

Schuurman, N., 2006, Formalization Matters—Critical GIS and Ontology Research: Annals of the Association of American 

Geographers, v. 94, no. 4, p. 726–739.

Zhou, N., 2011, Ontological and semantic technologies for geospatial portals in Zhao, P., and Di, L., eds., Geospatial Web Services—Advances in Information Interoperability: Hershey, Pa., IGI Global, p. 227–243.

Land Cover

Ahlqvist, O., 2008, Extending post-classification change detection using semantic similarity metrics to overcome class heterogeneity—A study of 1992 and 2001 U.S. National Land Cover Database changes: Remote Sensing of Environment, v.112, 

p. 1,226–1,241. 

Feng, C., and Flewelling, D. M., 2004, Assessment of semantic similarity between land use/landcover classification systems: 

Computers, Environment and Urban Systems, v. 28, issue 3, p. 229–246. 

Ecology and Environmental Monitoring

Bittner, T., 2007, From top-level to domain ontologies—Ecosystem classifications as a case study, in Conference on Spatial 

Information Theory, 9th, Melbourne, Australia, 2007, Cognitive and Computational Foundations of Geographic Information 

Science, p. 61–77. 

Fonseca, F., Martin, J., and Rodrigues, A., 2002, From geo- to eco-ontologies, in Egenhofer, M.J., and Mark, D.M., eds., Geographic information science: Springer.

Pundt, H., and Bishr, Y., 2002, Domain ontologies for data sharing—An example from environmental monitoring using field 

GIS: Computer and Geosciences, v. 28, issue 1, p. 95–102.

Sorokine, A., Bittner, T., and Renscher, C., 2006, Ontological investigation of ecosystem hierarchies and formal theory for multiscale ecosystem classifications: Geoinformaticea, v. 10, no. 3, p. 313–335. 

Terrain

Brodaric, B., 2007, Geo-pragmatics for the geospatial semantic web: Transactions in GIS, v. 11, issue 3, p. 453–477

Brodaric, B., and Gahegan, M., 2007, Experiments to examine the situated nature of geoscientific concepts: Spatial Cognition 

and Computation, v. 7, issue 1, p. 61–95.

Mark, D.M., and Smith, B., 2004, A science of topography—From qualitative ontology to digital representations, in Bishop, 

M.P., and Shroder, J.F., Jr., eds., Geographic information science and mountain geomorphology: Chichester, United Kingdom, 

Praxis Publishing, p. 75–100. 

Sinha, A. K., Malik, Z., Rezgui, A., Barnes, C.G., Lin, K., Heiken, G., Thomas, W.A., Gundersen, L.C., Raskin, R., Jackson, I., 

Fox, P., McGuinness, D., Seber, D., and Zimmerman, H., 2010, Geoinformatics—Transforming data to knowledge for geosciences: GSA Today, v. 20, no. 12, p. 4–10.

Smith, B., and Mark, D., 2003, Do mountains exist?—Towards an ontology of landforms: Environment and Planning, v. 30, 

issue 3, p. 411–427. 
Suggested Literature 105

Ontology of Rasters and Images

Bittner, T., and Winter, S., 1999, On ontology in image analysis in Integrated Spatial Databases, in Agouris, P., and Stefanidis, 

A., eds., Lecture Notes in Computer Science, v. 1737, p. 168–191

Camara, G., Egenhofer, M., Fonseca, F., and Monteiro, A.M.V., 2001, What’s in an Image? in Montello, D.R., ed., Spatial 

Information Theory—Foundations of geographic information science: Berlin, Germany, Springer-Verlag, Lecture Notes in 

Computer Science, v. 2205, p. 474–488.

Hornsby, K., 2004, Retrieving event-based semantics from images in Conference on Multimedia Software Engineering, 6th, 

Miami, Fla., Los Alamitos, Calif., 2004, Institute of Electrical and Electronics Engineers, p. 529–536.

Liu, Y., Lin, Y., Qin, S., Zhang, Y., and Wu, L., 2005, Research on GSQL Extension Supporting Raster Data, Journal of Image 

and Graphics, accessed May 31, 2011, at http://en.cnki.com.cn/Article_en/CJFDTOTAL-ZGTB20050100J.htm

Quintero, R., Torres, M., Moreno, M., and Guzman, G., 2009, Towards a semantic representation of raster spatial data in International Conference on Geospatial Semantics, 3d, Mexico City, Mexico, 2009, Lecture Notes in Computer Science 5892, Berlin, 

Springer-Verlag, p. 63–82.

Zheng, B., Huang, L., and Zinhai, L., 2009, Ontology for the cell-based geographic information in Liu, Y., and Tang, X., eds., 

International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining: Proc. Of SPIE, v. 7492. 

Similarity and Interoperability

Bish, Y., 1998, Overcoming the semantic and other barriers to GIS interoperability: International Journal of Geographical Information Science, v. 12, no. 4, p. 299–314. 

Bittner, T., Donnelly, M., Smith, B., 2006, A spatio-temporal ontology for geographic information integration: International 

Journal of Geographical Information Science, v. 23, issue 6, p. 765–798

Cruz, I.F., and Sunna, W., 2008, Structural alignment methods with applications to geospatial ontologies. Transactions in GIS, 

v. 12, issue 6, p. 683–711. 

Fonseca, F., David, C., and Câmara, G., 2003, Bridging ontologies and conceptual schemas in geographic information integration: Geoinformatica v. 7, issue 4, p. 355–378.

Fonseca, F., Egenhofer, M., Agouris, P., and Câmara, G., 2002, Using ontologies for integrated geographic information systems: 

Transactions in GIS, v. 6, no. 3, p. 231–257. 

Kavouras, M., and Kokla, M., 2008, Theories of geographic concepts—Ontological approaches to semantic integration: Boca 

Raton, Fla., CRC Press, 319 p.

Kokla, M., and Kavouras, M., 2005, Semantic information in geo-ontologies—Extraction, comparison, and reconciliation: Journal on data semantics, v. 3, p. 125–142.

Rodríguez, M. A., Egenhofer, M.J., and Rugg, R.D., 1999, Assessing semantic similarities among geospatial feature class definitions in Vckovski, A., Brassel, K., and Schek, H.J., eds., Interoperating geographic information systems, Interop ’99, Zurich, 

Switzerland: Springer-Verlag, Lecture Notes in Computer Science, v. 1580, p. 189–202. 

Schwering, A., 2008, Approaches to semantic similarity measurement for geo-spatial data: Transactions in GIS, v. 12, issue 1, 

p. 5–29.

Uitermark, H.T., van Oosterom, P.J.M., Mars, N.J.I., and Molenaar, M., 2005, Ontology-based integration of topographic data 

sets: International Journal of Applied Earth Observation and Geoinformation, v. 7, p. 97–106. 

Logic and Knowledge Representation and Reasoning

Bouquet, P., Ghidini, C., Giunchiglia, F., and Blanzieri, E., 2003, Theories and uses of context in knowledge representation and 

reasoning: Journal of Pragmatics, v. 35, issue 3, p. 455–484. 
106 Introduction to Geospatial Semantics and Technology Workshop Handbook

Brachman, R.J., and Levesque, H.J., 2004, Knowledge representation and reasoning: San Francisco, Calif., Morgan Kaufman, 

381 p.

Zhang, C., Zhao, T., Li, W., and Osleeb, J.P., 2010, Towards logic-based geospatial feature discovery and integration using 

web feature service and geospatial semantic web: International Journal of Geographical Information Science, v. 24, issue 6, 

p. 903–923. 

Sowa, J.F., 2000, Knowledge representation–Logical, philosophical, and computational foundations: Brooks/Cole, 608 p.

USGS Resources

Guptill, S., ed., 1990, An enhanced digital line graph design: U.S. Geological Survey Circular 1048 

Spatial Data Transfer Standard Technical Review Board, 1997, Spatial Data Transfer Standard part 2—Spatial features: Federal Geographic Data Committee, (Also available at http://mcmcweb.er.usgs.gov/sdts/SDTS_standard_nov97/p2anxa.

html#342523.)

U.S. Board on Geographic Names, 2010b, Geographic Names Information System (GNIS): U.S. Geological Survey, accessed on 

DATE, at http://geonames.usgs.gov/pls/gnispublic/f?p=gnispq:8:1829334408278873

U.S. Geological Survey, Digital line graph standards, (Also available at http://nationalmap.gov/standards/dlgstds.html.) 

Varanka, D., 2009a, Landscape features, technology codes, and semantics in U.S. National Topographic Mapping Databases, in

The International Conference on Advanced Geographic Information Systems and Web Services (GEOWS), Cancun, Mexico, 

2009, Geographic Information Systems and Web Services.

Varanka, D., 2009b, A topographic feature taxonomy for a U.S. National topographic mapping ontology, in International Cartographic Conference, 24th, Santiago, Chile, 2009, International Cartographic Association, [CD-ROM publication].

Varanka, D., 2011, Ontology patterns for complex topographic feature types: Cartography and Geographic Information Science, 

v. 38, no. 2, p. 126–136.

Varanka, D.E., Carter, J.J., Shoberg, T., and Usery, E.L., 2011, Topographic mapping data semantics through data conversion 

and enhancement, in Sheth, Amit, and Ashish, Naveen, eds., Geospatial semantics and the semantic web—Foundations, algorithms, and applications: Springer, Semantic Web and Beyond, v. 12, p. 145–162.

Usery, E.L., and Varanka, D.E., 2012, Design and development of linked data for The National Map: The Semantic Web Journal. 

Also available at: http://www.semantic-web-journal.net/content/design-and-development-linked-data-national-map. 

Edited Journal Issues and Proceedings from Scholarly Meetings

Crampton, J., ed., 2010, Ontological issues for The National Map: Cartographica: The International Journal for Geographic 

Information and Visualization, v. 45, no. 2, p. 103-104. 

Hitzler, P., and Janowicz, K., eds., 2012, Semantic web—Interoperability, usability, applicability, v. 3, no. 1, IOS Press.

Janowicz, K., Raubal, M., and Levashkin, S., eds., 2009, GeoSpatial semantics, in International Conference, 3d, Mexico City, 

Mexico, 2009, Lecture Notes in Computer Science 5892, Berlin, Springer-Verlag.

Kuhn, W., Worboys, M., and Timpf, S., eds., 2009, Spatial information theory—Foundations of geographic information science 

in Central organization for statistics and information technology international conference, Aber Wrac’h, France, 2009, Lecture 

Notes in Computer Science 2825, Berlin, Springer-Verlag. 

Wiegand, N., Berg-Cross, G., and Varanka, D.E., eds., 2011, First ACM SIGSPATIAL international workshop on spatial semantics and ontologies, in SIGSPATIAL international conference on advances in geographic information system, 19th, Chicago, 

Ill., 2011, Geographic Information System. 
Workshop Review Form 107

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Varanka—Introduction to Geospatial Semantics and Technology Workshop Handbook—Open-File Report 2012–1109