Geospatial Image Metadata Catalog Services As earth observation continues worldwide, large volumes of remotely sensed data on the Earth’s climate and environment have been collected and
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Geospatial Image Metadata Catalog Services
As earth observation continues worldwide, large
volumes of remotely sensed data on the Earth’s
climate and environment have been collected and
archived In order to maintain the data archives
efficiently and to facilitate discovery by users of
desired data in the holdings, each data provider
normally maintains a digital metadata catalog
Some online catalogs provide services to users
for searching the catalog and discovering the data
they need through a well-established Application
Programming Interface (API) Such services are
called Catalog Services The information in the
catalog is the searchable metadata that describe
individual data entries in the archives Currently
most Catalog Services are provided through
Web-based interfaces
This chapter analyses three open catalog
service systems It reviews the metadata
stan-dards, catalog service conceptual schemas and
protocols, and the components of catalog service
specifications
2 rev Iew of g eosp At IAL IMAge
cAt ALog ser vIces
2.1 Pilot Catalog Service Systems
The Federal Geographic Data Committee (FGDC)
Clearinghouse is a virtual collection of digital
spatial data distributed over many servers in the
United States and abroad The primary intention
of the Clearinghouse is to provide discovery
services for digital data, allowing users to
evalu-ate its quality through metadata Most metadata
provide information on how to acquire the data;
in many cases, links to the data or an order form
are available online
The NASA Earth Observing System
Clear-ingHOuse (ECHO) is a clearinghouse of spatial
and temporal metadata that enables the science
community to exchange data and information
ECHO technology can provide metadata discovery services and serve as an order broker for clients and data partners All the NASA Distributed Ac-tive Archive Centers (DAACs), as data providers, generate and ingest metadata information into ECHO
The Open Geospatial Consortium (OGC) has promoted standardization and interoperability among the geospatial communities In catalogue service aspect, OGC has defined the Catalog Service implementation standard (OpenGIS, 2004) and published two recommendation papers (OpenGIS, 2005a; OpenGIS 2005b) The George Mason University (GMU) CSISS Catalog service for Web (CSW) system is an OGC-compliant catalog service, which demonstrates how the earth science community can publish geospatial resources by searching pre-registered spatial and temporal metadata information In particular, the GMU CSISS CSW catalog service is based on the OpenGIS implementation standard, and the ebRIM application profile (OpenGIS, 2005) It provides users with an open and standard means
to access more than 15 Terabytes global Landsat datasets
2.2 Conceptual System Architecture
Since these geospatial catalog services address similar needs, it is not surprising that they have almost the same conceptual system architecture,
as shown in Figure 1
From the point of view of metadata tion, a catalog service usually consists of three components: metadata generation and ingestion,
circula-a conceptucircula-al schemcircula-a for ccircula-atcircula-alog service, circula-and circula-a query interface for catalog service
Metadata generation and ingestion is always based on applicable metadata standards, such
as the Dublin Core (DCMI, 2003), Geographic information – Metadata (19115) from Interna-tional Organization for Standard (ISO, 2003), Content Standard for Digital Geospatial Metadata (CSDGM) from Federal Geographic Data Com-
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Geospatial Image Metadata Catalog Services
mittee (FGDC, 1998), or the ECS Earth Science
Information Model from National Aeronautics
and Space Administration (NASA, 2006)
Metadata structures, relationships and
defini-tions, known as conceptual schemas, play a key
role in catalog services They define what kind
of metadata information can be provided and
how the metadata are organized The
concep-tual schemas are closely related to those of the
pre-ingested metadata information, but are not
necessarily identical Catalog service conceptual
schemas are always oriented toward the field of
application and may be tailored to particular
ap-plication profiles
The query interface for a catalog service
defines the necessary operations, the syntax of
each operation, and the binding protocol To
facilitate access and promote interoperability
among catalog services, the interface definition
may be kept open
2.3 Metadata g eneration
In this section, the three open catalog services
identified in Section 2.2 are analyzed on the
follow-ing two aspects regardfollow-ing metadata generation
. Base Metadata Standard
The base metadata standard is the public geospatial
metadata standard on which the catalog service
is based and to which the catalog service is lored, to meet a given agency’s requirements In addition to international and national geospatial metadata standards, such as ISO 19115 and FGDC CSDGM, several agencies may have de-facto standards in their production environment, such
tai-as NASA ECS
The metadata used by the FGDC house follows FGDC CSDGM Each affiliated catalog service site must organize their metadata information following the CSDGM standard before they join the clearinghouse
Clearing-The ECHO Science Metadata Conceptual Model has been developed based on the NASA Earth Observation System Data and Information Core System (EOSDIS) Science Data Model, with modifications to suit project needs
GMU CSISS CSW builds up its metadata ceptual model by combining the ebRIM informa-tion model and the ECS science data model
con-.. Automatic Generation of Metadata
As the volume of spatial datasets keeps growing, generation of metadata becomes increasingly time-consuming An automatic mechanism for generating metadata will facilitate the generation and frequent update of metadata
Metadata information needs to be organized
as TXT or SGML or HTML files before a node
Figure 1 Conceptual Architecture of Catalog Service
Catalog ServiceClient Catalog Service
MetadataHoldings
DataHoldings
Query Interface
Conceptual Schema
User
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Geospatial Image Metadata Catalog Services
joins the FGDC clearinghouse Some metadata
generation tools are available in addition to the
commercial software packages These tools are
advertised on the FGDC website To help the user
set up a clearinghouse node easily, a software
package, ISite, is provided With this software,
a qualified clearinghouse node server can be set
up in minutes
All the ECHO metadata holdings are obtained
directly from the data providers DAACs can
use some ECS tools to automatically generate
metadata information
GMU CSISS is developing Java-based tools
to automatically extract metadata information
from each granule The Hierarchical Data Format
(HDF), Hierarchical Data Format - Earth
Observ-ing System (HDF-EOS), GeoTIFF and NetCDF
data formats are currently supported
2.4 Metadata Ingestion
. Metadata Distribution
This function deals with the physical
distribu-tion of metadata informadistribu-tion within the catalog
service
The FGDC Clearinghouse is a decentralized
system of servers that contain field-level
meta-data descriptions of available digital spatial meta-data
located on the Internet The metadata
informa-tion is physically managed within the affiliated
server node
Even though in ECHO scenario, the metadata
information is periodically generated by those
distinct data centers, they are centrally managed
by the ECHO operation team That is, in the
design time, metadata information in ECHO is
distributed; while in the run time it is managed
centrally
The GMU CSISS CSW maintains more than
15 Terabytes of global Landsat images All the
metadata information for these images has been
registered into a centralized metadata database
. Ingestion Type
This section examines how each catalog service ingests metadata It focuses on two aspects: remote
vs local and automatic vs manual
In the FGDC Clearinghouse, all the metadata information is manipulated only in the affiliated server node Remote ingestion is not supported
in server nodes The ingestion has to been ally
manu-Due to a centralized metadata information, a database approach is taken Metadata ingestion in ECHO involves two steps Data centers need to up-load their current metadata information remotely
to a dedicated File Transfer Protocol (FTP) server, and the ECHO operation team is responsible for ingesting these metadata information into the ECHO operational system
GMU CSISS CSW provides published faces As long as the metadata information is well organized, it can be remotely ingested into the GMU CSISS CSW metadata database All the metadata information in that database is online and ready for client’s query
inter-2.5 Conceptual Schema
We examine how the metadata conceptual schema
is defined in each catalog service
In each FGDC Clearinghouse collection, all the metadata information is organized according
to the FGDC CSDGM The conceptual schema
of FGDC Clearinghouse collection is exactly the same as that of the FGDC CSDGM
In ECHO, all the metadata information lected in the NASA DAACs is based on the ECS science data model, with some modifications necessary to suit project needs
col-GMU CSISS CSW defines its conceptual schema based on the ECS science data model combined with ISO 19115 Since GMU CSISS CSW supports metadata queries and data retrieval (through the OGC services), an ebRIM-based profile has been selected to support defining the
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Geospatial Image Metadata Catalog Services
association between a data granule instance and
applicable geospatial service instances
2.6 t ransfer protocol
A catalog service usually provides a standard,
API-based interface to support the client’s query
This “design-by-contract” mechanism promote
third party members’ contribution to develop new
query interfaces, besides those web-based query
interfaces provided by the catalog server itself
The backbone of the FGDC Clearinghouse is
Z39.50 (ISO, 1998) This protocol was initially
developed by the library community to discover
bibliographic records using a standard set of
attri-butes To guide how to implement FGDC metadata
elements within a Z39.50 service, the FGDC has
developed an application profile for geospatial
metadata called "GEO," which provides sets of
attributes, operators, and rules of implementation
that suit geospatial needs In fact, the node server
is a Z39.50 server, which enables FGDC query
utilities to search its metadata holdings on the fly
through Z39.50 protocol and GEO profile
ECHO exposes the Session Manager and a
lim-ited set of the ECHO services as Web Services
de-fined via the Web Services Description Language
(WSDL) ECHO also provides two client packages,
Façade and EchoTalk, for client developers The
syntax of the communication protocol between
client and ECHO is based on the Web Services
Interoperability (WS-I) Basic Profile However,
the semantics of the communication protocol are
defined by ECHO itself Specific query syntax,
in Extensible Markup Language (XML) format,
has been proposed and implemented
GMU CSISS CSW’s communication protocol
is based on the OGC Catalog Service
Implementa-tion SpecificaImplementa-tion, which specifies the interfaces
and several applicable bindings for catalog
ser-vices Operations, core information schema and
query language encodings are included The
transportation-related communication protocol
follows this specification
2.7 System Distribution
This section examines the physical distribution
of catalog service systems
The FGDC Clearinghouse has 400 worldwide registered nodes as of March 22, 2006 FGDC maintains several Web-based search interfaces
to carry out distributed searches across multiple clearinghouse nodes
ECHO acts as an intermediary between data partners and client partners Data partners provide information about their data holdings, and client partners develop software to access this informa-tion through ECHO Query and Order Web Service interface End users who want to search ECHO's metadata must use one of the ECHO clients Although ECHO has close connections with the DAACs and ECHO Clients, ECHO itself is not
a distributed system It does not need to build a distributed search across multiple agencies and nodes at run time
GMU CSISS CSW is a standalone service Like ECHO, it is not a distributed system
2.8 Review Summaries
Table 1 summarizes the results of the analysis
3 conc Lus Ion And dIscuss Ion
We have reviewed three public catalog services
— FGDC Clearinghouse, NASA ECHO and GMU CSISS CSW— considering the following aspects: metadata generation, metadata ingestion, catalog service conceptual schema, query protocols and system distribution This review shows how it
is becoming possible to query metadata ings through public, standard Web-based query interfaces
hold-The review results also show that the catalog service providers still must define a catalog service schema that meets their particular needs These application-oriented approaches can meet projects
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Geospatial Image Metadata Catalog Services
requirements, but they will make it more difficult
to create future cross-federation multi catalog
services We recommend that a standard, common
and discipline-oriented-metadata based schema
be used for future implementations of catalog
services in the same and/or related fields
r eferences
DCMI (2003) DCMI Metadata Terms Retrieved
March 8, 2007, from
http://dublincore.org/docu-ments/dcmi-terms/ß
ECHO (2005) Earth Observing System
Clearing-house Retrieved March 8, 2007, from http://www.
echo.eos.nasa.gov/
FGDC (1998) Content Standard for Digital
Geospatial Metadata (CSDGM) Retrieved March
8, 2007, from http://fgdc.er.usgs.gov/metadata/
contstan.html
FGDC (2005) FGDC Geospatial Data
Clear-inghouse Activity Retrieved March 8, 2007,
NASA (2006) EOSDIS Core System Data Model,
Retrieved March 8, 2007, from http://spg.gsfc.nasa.gov/standards/heritage/eosdis-core-system-data-model
OpenGIS (2004) OpenGIS Catalogue Service Implementation Specification Retrieved March
8, 2007, from http://www.opengeospatial.org/specs/?page=specs
OpenGIS (2005a) OGC Recommendation
Pa-per 04-17r1: OGC Catalogue Services- ebRIM (ISO/TS 15000-3 profile of CSW Retrieved
March 8, 2007, from http://www.opengeospatial.org/specs/?page=recommendation
Tables 1 Review summaries
on Web Service OGC Catalog Service and HTTP binding
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Geospatial Image Metadata Catalog Services
OpenGIS (2005b) OGC Recommendation
Pa-per 04-038r2: ISO19115/ISO19119 Application
Profile for CSW 2.0 Retrieved March 8, 2007,
from http://www.opengeospatial.org/specs/
?page=recommendation
key t er Ms
Catalog Service: A set of information,
con-sisting of some or all of directory, guide, and
in-ventories, combined with a mechanism to provide
responses to queries, possibly including ordering
data (Source: Earth Science and Applications
Data System)
Catalog System: An implementation of a
directory, plus a guide and/or inventories,
inte-grated with user support mechanisms that provide
data access and answers to inquires Capabilities
may include browsing, data searches, and placing
and taking orders A specific implementation of
a catalog service (Source: Earth Science and
Applications Data System, Interagency Working
Group on Data Management for Global Change,
European Patent Organisation)
Service: A distinct part of the functionality
that is provided by an entity through interfaces (Source: ISO 19119: Geographic information – Services)
Interface: A named set of operations that
characterize the behavior of an entity (Source: ISO 19119: Geographic information – Services)
Operation: A specification of a transformation
or query that an object may be called to execute (Source: ISO 19119: Geographic information – Services)
Transfer Protocol: A common set of rules
for defining interactions between distributed systems (Source: 19118: Geographic information
- Encoding)
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Chapter XXIII Geospatial Semantic Web:
George Mason University, USA
Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.
Abstr Act
The Semantic Web technology provides a common interoperable framework in which information is given a well-defined meaning such that data and applications can be used by machines for more ef- fective discovery, automation, integration and reuse Parallel to the development of the Semantic Web, the Geospatial Semantic Web – a geospatial domain-specific version of the Semantic Web, is initiated recently Among all the components of the Geospatial Semantic Web, two are especially unique – geo- spatial ontology and geospatial reasoning This paper is focused on discussing these two critical issues from representation logic to computational logic.
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Geospatial Semantic Web
Inspired by Tim Berners-Lee (Berners-Lee, 1998;
W3C, 2006), inventor of the Web, a growing
number of individuals and groups from academia
and industry have been evolving the Web into
another level - the Semantic Web By
represent-ing not only words, but their definitions and
contexts, the Semantic Web provides a common
interoperable framework in which information is
given a well-defined meaning such that data and
applications can be used by machines
(reason-ing) for more effective discovery, automation,
integration and reuse across various application,
enterprise and community boundaries Compared
to the conventional Web, the Semantic Web excels
in two aspects (W3C, 2006): 1) common formats
for data interchange (the original Web only had
interchange of documents) and 2) a language for
recording how the data relates to real world objects
With such advancements, reasoning engines and
Web-crawling agents can go one step further – and
inductively respond to questions such as “which
airfields within 500 miles of Kandahar support
C5A aircraft?” rather than simply returning Web
pages that contain the text “airfield” and
“Kan-dahar”, which most engines do today
Figure 1 shows the hierarchical architecture
of the Semantic Web At the bottom level, XML (Extensible Markup Language) provides syntax
to represent structured documents with a defined vocabulary but does not necessarily guarantee well-defined semantic constraints on these documents And XML schema defines the structure of an XML document RDF (Resource Description Framework) is a basic data model with XML syntax that identifies objects (“resources”) and their relations to allow information to be exchanged between applications without loss of meaning RDFS (RDF Schema) is a semantic extension of RDF for describing the properties
user-of generalization-hierarchies and classes user-of RDF resources OWL (Web Ontology Language) adds vocabulary to explicitly represent the meaning of terms and their relationships, such as relations between classes (e.g disjointness), cardinality (e.g., “exactly one”), equality and enumerated classes The logic layer represents the facts and derives knowledge, and deductive process and proof validation are deduced by the proof layer
A digital signature can be used to sign and export the derived knowledge A trust layer provides the trust level or a rating of its quality in order
to help users building confidence in the process
Figure 1 Semantic Web architecture (Berners-Lee, 2000)
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Geospatial Semantic Web
and quality of information(Antoniou & Harmelen,
2004)
Parallel to the development of the Semantic
Web, the Geospatial Semantic Web – a geospatial
domain-specific version of the Semantic Web, is
initiated recently Because geospatial information
is heterogeneous, i.e multi-source, multi-format,
multi-scale, and multi-disciplinary, the
impor-tance of semantics on accessing and integration
of distributed geospatial information has long
been recognized (Sheth, 1999) The advent of the
Semantic Web promises a generic framework to
use ontologies to capture the meanings and
rela-tions for information retrieval But this framework
does not relate explicitly to some of the most basic
geospatial entities, properties and relationships
that are most critical to a particular geospatial
information processing task To better support
the discovery, retrieval and consumption of
geospatial information, the Geospatial Semantic
Web is initiated to create and manage geospatial
ontologies to capture the semantic network of
geospatial world and allow intelligent applications
to take advantage of build-in geospatial reasoning
capabilities for deriving knowledge It will do so
by incorporating geospatial data semantics and
exploiting the semantics of both the processing
of geospatial relationships and the description
of tightly-coupled service content (Egenhofer,
2002; Lieberman, Pehle, & Dean, 2005) The
Geospatial Semantic Web was identified as an
immediately-considered research priority early in
2002 (Fonseca & Sheth, 2002) by UCGIS
(Uni-versity Consortium for Geospatial Information
Science) As an international voluntary consensus
standards organization, OGC (Open Geospatial
Consortium) conducted the Geospatial Semantic
Web Interoperability Experiment (GSW-IE) in
2005 aiming to develop a method of discovering,
querying and collecting geospatial content on the
basis of formal semantic specifications
The architecture of the Geospatial Semantic
Web is similar to that portrayed in Figure 1 The
Geospatial Semantic Web and the Semantic Web
share top level (general) ontology, ontological guages, and general reasoning mechanisms The Geospatial Semantic Web extends the Semantic Web with domain-specific components Among all the components of the Geospatial Semantic Web, two are especially unique – geospatial ontology and geospatial reasoning The former aims at expressing geospatial concepts and re-lationships, specialized processing of geospatial rules and relationships, and self-described Web service with its highly dynamic geospatial con-tent beyond the purely lexical and syntactic level (Egenhofer, 2002; Lieberman et al., 2005; O'Dea, Geoghegan, & Ekins, 2005) The latter embraces sets of geospatial inference rules on the basis of geospatial ontologies and techniques to conduct automated geospatial reasoning by machine with less human interaction for deriving geospatial knowledge These two are the foci to be elaborated
lan-in the followlan-ing two sections lan-in this paper Two application cases are presented to show the syn-dicated achievements of the Geospatial Semantic Web A short summary is given at the end
g eosp At IAL o nt o Logy
It is widely recognized that ontology is critical for the development of the Semantic Web Ontology originated from philosophy as a reference to the nature and the organization of reality In general,
an ontology is a “specification of a ization” (Gruber, 1993) In the computer science
conceptual-domain, ontology provides a commonly agreed upon understanding of domain knowledge in a generic way for sharing across applications and groups (Chandrasekaran, Johnson, & Benjamins, 1999) Typically, ontology consists of a list of
terms (classes of objects) and the relationships
between those terms Moreover, ontology can also represent property information (e.g., an airfield has runways), value restrictions (e.g., aircraft can only take off at an airfield), disjointness statements (e.g., aircraft and train are disjoint), and specifi-
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Geospatial Semantic Web
cation of logical relationships between objects
(e.g., a runway must be at least 400 meters long
for supporting C5A aircraft)
In the geospatial domain, a specific range of
geospatial ontolgoies are needed to define a formal
vocabulary that sufficiently captures the semantic
details of geospatial concepts, categories,
rela-tions and processes as well as their interrelarela-tions
at different levels A geospatial ontology does
not simply give a definition, but also represents
relationships between concepts For example, an
ontological definition of “surface water” describes
its properties and characteristics but also carries
relationship meanings to other entities, such as
“surface water” belongs to “hydrosphere”, and
“river” is a kind of “surface water”
A well-formatted geospatial ontology is very
useful in the following areas:
• Interoperability Since the geospatial
sci-ences deal with phenomena across a variety
of scales and disciplines, the semantics of
geospatial information is essential for the
development of interoperable geospatial
software and data formats Geospatial
ontol-ogy provides a common understanding of
not only general geospatial concepts but also
complex geospatial scientific computing
Through geospatial ontology, the different
geospatial data models and representations
can be integrated
• Spatial reasoning about geospatial
associa-tions and patterns, e.g., topological relaassocia-tions
(connectivity, adjacency and intersection
of geospatial objects), cardinal direction
(relative directions among geospatial
ob-jects, such as east, west and southwest), and
proximity relations (geographical distance
between geospatial objects, such as A is close
to B and X is very far from Y, and contextual
relations, such as an obstacle separates two
objects that would be considered nearby
space, but are considered far because of the
obstacle) (Arpinar, Sheth, & Ramakrishnan,
2004)
• Reuse and organization of information,
such as standardizing libraries or tories of geospatial information and work-flows
reposi-Compared to general ontologies, geospatial ontologies specifically encode 1) spatial concepts, e.g., location and units, 2) spatial relationships, e.g., inside, near and east, 3) physical facts, e.g., physical phenomena, physical properties and physical substances, 4) geospatial data, e.g., data properties, such as instruments, platforms and sensors, and 5) geospatial computing processes, e.g., disciplines, parameters and algorithms According to the interactions and the role within the context of the Geospatial Semantic Web, geospatial ontology can be classified into several large groups with hierarchical relationships as Figure 2 in which the ontologies at upper levels are consistent to the ontologies at lower levels.General ontology is the core upper level vo-cabulary representing common human consensus reality that all other ontologies must reference It
is domain independent The widely used Dublin Core Metadata (Dublin, 2006) provides a standard for metadata vocabularies to describe resources that enable the development of more intelligent information discovery systems OpenCyc (Open-Cyc, 2006) is the world's largest and most com-plete general knowledge base and commonsense reasoning engine defining more than 47,000 upper level concepts and 306,000 assertions about these concepts
Geospatial feature ontology, defining tial entities and physical phenomena, provides the core geospatial vocabulary and structure, and forms the ontological foundation of geospatial information It should be coordinated with the development of geospatial standards to define its scope and content, such as the ISO 19100 series and the OGC specifications Geospatial factor ontology describes geospatial location, unit conversion factors and numerical exten-sions To enable geospatial topological, proximity
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Geospatial Semantic Web
and contextual reasoning, geospatial
relation-ship ontology represents geospatial and logical
relationships between geospatial features The
RDF geo vocabulary (Brickley, 2004) provides
a basic RDF vocabulary with a namespace for
representing lat(itude), long(itude) and other
information about spatially-located things using
WGS84 as a reference datum The OWL-Space
initiative (formerly DAML-Space) provides the
ontologies of comprehensive spatial properties
and relations including topology, dimensioin,
orientation and shape, length and area, lat/log
and elevation, geopolitical subdivisions,
granu-larity, aggregate and distributions(Hobbs, 2003)
By incorporating Region Connection Calculus
(RCC), the CoBrA (Harry Chen, Finin, & Joshi,
2003) and the SWETO-GS (Arpinar et al., 2004)
define basic relations between two-dimensional
areas and relevant rules to enable the reasoning of
spatiotemporal thematic proximity The ontologies
described above facilitate the information
com-munication between geospatial applications
Geospatial domain-specific ontology
rep-resents the specific concepts in one domain by
using proprietary vocabularies over which the
user will query Sometimes there exists using
different terms to represent a geospatial feature
in different domains To achieve interoperability,
there must be a link between domain ontology
and feature ontology, either by subclassing feature
ontology concepts or by mapping from feature concepts to domain concepts To provide formal semantic descriptions of geospatial data collec-tions and scientific concepts, several projects are underway to develop a semantic framework The ontologies within the Semantic Web for Earth and Environmental Terminology (SWEET)(Raskin, 2006) contain several thousand terms spanning
a broad extent of Earth system science and lated concepts in order to provide a high-level semantic description of Earth system science
re-To facilitate data register and data discovery, the GEON (Geosciences Network) project develops
a series of geological ontologies to standardize the description of geological map including data structure and content(Lin et al., 2004)
Geospatial data ontology uses the ontologies that fall below it in Figure 2 to provide a dataset description which includes representation, stor-age, modeling, format, resources, services and distributions It ensures that the data are discov-erable, usable and interoperable in a standard way The ontologies of geospatial metadata for ISO 19115 and FGDC (Federal Geographic Data Committee) being developed in (Islam, Bermudez, Beran, Fellah, & Piasecki, 2004; Zhao, 2004) add semantic meanings and relationships to the metadata terms by which data sets are explicitly associated with providers, instruments, sensors and disciplines
Figure 2 The hierarchy of geospatial ontology
General Ontology Geospatial Feature Ontology
Geospatial Factor Ontology Geospatial Relationship Ontology
Geospatial Domain-Specific Ontology
Geospatial Data Ontology Geospatial Service Ontology
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Geospatial Semantic Web
Geospatial service ontology describes who
provides the service, what the service does and
what other properties the service has that make
it discoverable by incorporating the lower level
ontologies It also states the service inputs, outputs,
preconditions and effects to ensure the service
measurable by using data ontology To allow
dynamic invocation, this ontology also includes
the concrete service ports, protocols and
encod-ings Geospatial service ontology enhances and
extends the current offerings of web services by
enabling full semantic queries against service
offerings Since the OWL-S provides a semantic
framework to describe web services, it seems like
a good choice to follow its logical structure for the
definition of geospatial service ontology
g eosp At IAL seMAnt Ic
r eAson Ing
Geospatial semantic reasoning can deduce (infer)
conclusions from given geospatial knowledge by
uncovering implicit ontological knowledge and
unexpected relationships and inconsistencies For
example, suppose area Y is inside area X and area
Z is within area Y We can deduce that Z is inside
X if the meanings of inside and within are well
defined as following, i.e., inside is same as within
and both of them are transitive properties
Logic, particularly in the form of predicate
logic (first order logic), is the foundation of
reason-ing by offerreason-ing a formal language for expressreason-ing knowledge in well-understood semantics The proof system can automatically drive statements syntactically from a set of premises and provide explanations for answers by tracing logical conse-quences In general, the more expressive a logical system is, the more computational complexity it has for drawing conclusions Description logic
is a particular decidable fragment of predicate logic with desirable computational properties for reasoning systems in which correspondences are illustrated by the axiomatic semantics in the form
of logical axioms RDF(S), OWL Lite and OWL
DL can be viewed as description logics Rule
systems (Horn logic), known as A 1 , … A n B, is
another subset of predicate logic with an efficient proof system that is orthogonal to description logic In geospatial domain, RDF and OWL al-low ontology reasoning by defining the geospatial representation of real-world features, and rules allow default reasoning and fuzzy reasoning by defining how spatial features relate to each other and how they process geospatial data (H Chen, Fellah, & Bishr, 2005; O'Dea et al., 2005)
The subsumption is the basic inference in
on-tology, typically written asY ⊆ X , i.e., checking whether the concept denoted by X is considered more general than that denoted by Y For example,
Feature
⊆ Fea-ture andRunway ⊆ AirportFac ility Such a concept hierarchy provides useful information on the connection between different concepts The
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Geospatial Semantic Web
instantiation inference can check if individual
i is instance of class C, i.e., i ∈ CI Moreover,
this instance relationship may trigger the
appli-cation rules to get additional facts The retrieval
inference can thus retrieve set of individuals that
instantiate the class The other basic inference is
satisfiability, which detects whether a new concept
makes sense or whether it is contradictory to the
existing one For example, C ⊆ Diff D ¬ C
is not satisfied
In the Geospatial Semantic Web applications,
rules are needed to deal with the situations where
reasoning moves from representation logic to
com-putational logic For example, to answer “which
airfields near Kandahar support C5A aircraft”,
the following rules are necessary
IF isTypeOf (?airport, Airport:airport) AND
Locate (?location, gazetteer:Kandahar) AND
Buffer (?airport, ?location, 500, “miles”)
AND
HasRunway (?runway, ?airport) AND
GreaterThan (?runway, 400, “meters”)
THEN
supportC5A (?airport)
The above example expresses that an airport
supports C5A landing near Kandahar if it has a
runway at least 400 meters long, and is located
within 500 miles of Kandahar (by finding the
location of Kandahar and calculating its circle
buf-fer) At present, there are a number of proposed
standard Semantic Web rule languages SWRL
(Semantic Web Rule Language) (Horrocks et al.,
2004), based on a combination of the OWL with
the RuleML, is a good candidate
On the Semantic Web, “theory” reasoning is a
desirable complement to “standard” reasoning (F
Bry & Marchiori, 2005) The Geospatial Semantic
Web requires specific geospatial reasoning
meth-ods to take advantage of any particular properties
of geospatial entities Region Connection Calculus
(RCC8) (Cohn, Bennett, Gooday, & Gotts, 1997)
uses regions as the primary spatial entity and
provides a rich vocabulary of qualitative shape descriptions and a logical calculus for qualitative reasoning with a first-order and propositional sub-variant In (Francois Bry, Lorenz, Ohlbach,
& Rosner, 2005), a geospatial world model is developed for Semantic Web applications In this model, geospatial data is represented as a hierarchy of graphs that combine very low-level coordinate-based computations with abstract symbolic reasoning and the ontology of transport networks Based on this model, two-dimensional fuzzy reasoning for geospatial data is developed (Ohlbach & Lorenz, 2005)
AppLIc At Ions
The Geospatial Semantic Web promises an
“intelligent” method to discover, retrieve and integrate large and diverse geospatial information and services Numerous efforts to approach this
“intelligence” are currently active
geon Intelligent g eologic data Integration
GEON project (http://www.geonrid.org) develops
an interoperable framework and system that lows the intelligent integration of geologic data from different resources In this framework, data providers register a data set with one or more
al-“mediation ontologies”, i.e., standards for data structure and content, and subsequently query the different data sets in a uniform fashion Thus, heterogeneous source vocabularies are made compatible via the ontologies, and multiple con-ceptual dimensions become queryable simultane-ously, e.g., find regions with igneous rocks from geologic period P having composition C, fabric F and texture T(Lin et al., 2004) In order to answer semantic queries, such as synonymous, more specific and less specific, the system embedded
in the GEON grid environment reasons with the ontologies and builds the distributed query plans accordingly
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Geospatial Semantic Web
Intelligent g eospatial w eb services
A geospatial Web service is a modular application
representing a real geospatial computing process
over the network In order to solve real-world
geospatial problems through Web services, an
“intelligent” mechanism is required to facilitate
service discovery and integration and automate
the assembly of service chains An approach to
intelligent geospatial Web service is presented in
(Di, Zhao, Yang, Yu, & Yue, 2005) This approach
uses ontologized “Geo-Object”, a component of
“Geo-Tree”, to integrate the views of geospatial
services and make them understandable and
in-ferable By using semantic-enabled OGC catalog
service, a “Geo-Object” can be easily found based
on the flexible semantic match on its inputs and
outputs Actually, a “Geo-Tree” describing a
geospatial modeling process can be easily
rep-resented as a service chain The construction of
such a tree is backward (from goal to source) in
which all relevant “Geo-Object” are discovered
and linked automatically based on the user’s goals
Once all the components have been found, the tree
is initiated as a service chain in BPEL (Business
Process Execution Language) and then be sent to
the workflow engine for being executed
c onc Lus Ion
The Semantic Web technology is concerned
with preserving the concept meanings and links
between concepts in order to make information
machine-accessible It is an efficient way of
representing data and applications Geospatial
ontologies provide semantic descriptions of the
geospatial world, and geospatial reasoning derives
additional facts from them From representation
logic to computational logic, the Geospatial
Se-mantic Web enhances our ability to express and
deduce geospatial concepts and relationships for
achieving interoperability among distributed
heterogeneous geospatial data and applications
Fotheringham (Eds.), Handbook of Geographic Information Science: Blackwell Publishing.
Berners-Lee, T (1998) Semantic Web Road Map Retrieved March 21, 2006, from http://www.w3.org/DesignIssues/semantic.html
Berners-Lee, T (2000) Semantic Web on XML
Paper presented at the XML 2000, Washington DC
Brickley, D (2004) Basic Geo (WGS84 lat/long) Vocabulary Retrieved March 25, 2006, from http://www.w3.org/2003/01/geo
Bry, F., Lorenz, B., Ohlbach, H J., & Rosner,
M (2005, Septemper 11-16, 2005) A Geospatial World Model for the Semantic Web Paper pre-
sented at the Third Workshop on Principles and Practice of Semantic Web Reasoning, Dagstuhl, Germany
Bry, F., & Marchiori, M (2005, 27th 28th
April, 2005) Ten Theses on Logic Language for the Semantic Web Paper presented at the W3C
Workshop on Rule Languages for Interoperability, Washington D.C., USA
Chandrasekaran, B., Johnson, T., & Benjamins,
V (1999) Ontologies: What are they? why do we
need them? IEEE Intelligent Systems and Their Applications, 14(1), 20-26.
Chen, H., Fellah, S., & Bishr, Y (2005, April
27-28, 2005) Rules for Geospatial Semantic Web Applications Paper presented at the W3C
Workshop on Rule Languages for Interoperability, Washington D C., USA
Trang 15
Geospatial Semantic Web
Chen, H., Finin, T., & Joshi, A (2003, October
12-15, 2003) An Intelligent Broker for
Context-Aware Systems Paper presented at the Ubicomp
2003, Seattle, Washington, USA
Cohn, A., Bennett, B., Gooday, J., & Gotts, N
(1997) Qualitative Spatial Representation and
Reasoning with the Region Connection Calculus
GeoInformatica, 1(3), 275-316.
Di, L., Zhao, P., Yang, W., Yu, G., & Yue, P
(2005) Intelligent Geospatial Web Services
Paper presented at the IEEE 25th Anniversary
International Geoscience and Remote Sensing
Symposium
Dublin (2006) Retrieved March 20, 2006, from
http://dublincore.org
Egenhofer, M (2002, November 8-9, 2002)
Toward the Semantic Geospatial Web Paper
presented at the The Tenth ACM International
Symposium on Advances in Geographic
Informa-tion Systems, McLean, VA
Fonseca, F., & Sheth, A (2002) The
Geospa-tial Semantic Web Retrieved March 20, 2006,
from http://www.ucgis.org/priorities/research/
2002researchPDF/shortterm/e_geoseman-tic_web.pdf
Gruber, T (1993) A Translation Approach to
Portable Ontologies Knowledge Acquisition,
5(2), 199-220.
Hobbs, J (2003) An Ontology of Spatial
Rela-tions for the Semantic Web Paper presented at
the Workshop on the Analysis of Geographic
References
Horrocks, I., Patel-Schneider, P., Boley, H., Tabet,
S., Grosof, B., & Dean, M (2004) SWRL: A
Semantic Web Rule Language Combining OWL
and RuleML Retrieved March 27th, 2006, from
http://www.w3.org/Submission/SWRL/
Islam, A S., Bermudez, L., Beran, B., Fellah, S.,
& Piasecki, M (2004) Ontology for Geographic Information - Metadata (ISO 19115:2003) Re-trieved March 31, 2006, from http://loki.cae.drexel.edu/~wbs/ontology/iso-19115.htm
Lieberman, J., Pehle, T., & Dean, M (2005, June
9-10, 2005) Semantic Evolution of Geospatial Web Services Paper presented at the W3C Workshop
on Frameworks for Semantic in Web Services, Innsbruck, Austria
Lin, K., Ludaescher, B., Broadaric, B., Seber, D.,
Baru, C., & Sinha, K (2004) Semantic Mediation Services in Geologic Data Integration: A Case Study from the GEON Grid Paper presented at
the GSA Annual Meeting
O’Dea, D., Geoghegan, S., & Ekins, C (2005)
Dealing with Geospatial Information in the mantic Web Paper presented at the Australasian
Se-Ontology Workshop, Sydney, Australia
Ohlbach, H J., & Lorenz, B (2005) Geospatial Reasoning: Basic Concepts and Theory Retrieved 27th March, 2006, 2006
OpenCyc (2006) Retrieved March 20, 2006, from http://www.opencyc.org
Raskin, R (2006) Guide to SWEET Ontologies Retrieved March 22, 2006, from http://sweet.jpl.nasa.gov/sweet
Sheth, A (1999) Changing Focus on ability in Information Systems: From System, Syntax, Structure to Semantics In M Goodchild,
Interoper-M Egenhofer, R Fegeas & C Kottman (Eds.),
Interoperating Geographic Information Systems
(pp 5-30) New York: Kluwer
W3C (2006) Semantic Web Retrieved March
25, 2006, from http://www.w3.org/2001/swZhao, P (2004) Geospatial Ontology Retrieved March 27, 2006, from http://geobrain.laits.gmu.edu/ontology
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Geospatial Semantic Web
key t er Ms
Interoperability: Capability to communicate,
execute programs, or transfer data among various
functional units in a manner that requires the
user to have little or no knowledge of the unique
characteristics of those units [ISO 2382-1]
Geospatial Ontology: A formal vocabulary
that sufficiently captures the semantic details
of geospatial concepts, categories, relations and
processes as well as their interrelations at
dif-ferent levels
Geospatial Reasoning: Using logic to infer
implicit spatial relationships and knowledge from
given geospatial facts
Geospatial Semantic Web: A
domain-spe-cific version of the Semantic Web which creates
and manages geospatial ontologies to exploit the
logical structure of geospatial world and allow
applications to take advantage of “intelligent”
geospatial reasoning capabilities
Geospatial Web Service: A modular
appli-cation designed to enable the discovery, access, and process of geospatial information across the Web
Ontolog: A specification of conceptualization
In computer science domain, ontology provides
a commonly agreed understanding of domain knowledge in a generic way for sharing across applications and groups
Semantic Web: A common interoperable
framework in which information is given defined meaning such that the data and applica-tions can be used by machine for more effective discovery, automation, integration, and reuse across various applications, enterprises and com-munity boundaries
Trang 17well-Section VDistributed Geoprocessing
Trang 18
Chapter XXIV Geospatial Web Service
Chaining
Carlos Granell
Universitat Jaume I, Spain
Michael Gould
Universitat Jaume I, Spain
Miguel Ángel Esbrí
Universitat Jaume I, Spain
Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.
Abstr Act
In the context of Geographic Information System’s evolution from monolithic systems to personal top GIS and then to collections of remote Internet services, we discuss the combination or chaining of distributed geospatial web services The adoption of web services technology provides remote access
desk-to a diverse and wide array of geospatial datasets and allows developers desk-to create web applications (web browser-based or GIS client-based), hiding the underlying server functionalities from their public interfaces A major challenge in working with these remote services, as opposed to a single desktop application, is to properly integrate ad hoc services to build a coherent service chain; this is especially tricky in real-time scenarios where web applications need to be built on-the-fly This chapter discusses strategies for geospatial web service chaining and poses some challenging issues, many related to se- mantics, to be resolved for geospatial web service chaining to become a commonplace activity.
Trang 190
Geospatial Web Service Chaining
Int roduct Ion
The development of Geographic Information
Systems (GIS) has been highly influenced by
the overall progress of Information Technology
(IT) These systems evolved from monolithic
systems to become personal desktop GIS with
all or most data held locally and then again to the
Internet GIS paradigm in the form of Web
ser-vices (Peng & Tsou, 2001) The highly distributed
web services model is such that geospatial data
are loosely coupled with the underlying systems
used to create and handle them, and
geo-process-ing functionalities are made available as remote,
interchangable, interoperable, and specialized
geospatial services
In recent years the software industry has moved
away from complex architectures such as CORBA
(Common Object Request Broker Architecture)
(Vinoski, 1997) toward more universal and easily
defined architecture based on
already-implement-ed Internet protocols (Kaye, 2003) The success
factor of Web services technology has been to
promote service integration and interoperability
among heterogeneous distributed information
sources, without leaving the well-known and
ac-cepted Internet (Web) architecture This has led
to de facto standards for delivery of services such
as Web Service Description Language (WSDL)
to describe the functionality of a service, Simple
Object Access Protocol (SOAP) to encapsulate
web service messages, and Universal Description,
Discovery, and Integration (UDDI) to register and
provide access to service offerings Alternative
service architectures such as Representational
State Transfer, or REST, (Fielding, 2000) exist as
well; however the former de facto standards have
dominated Perhaps the most beneficial
character-istic of Web services technology is to provide not
only access to individual Web services but also
integrate several services assembling a new
value-added service chain Adoption of Web services
technology as an option to fixed, monolithic GIS
is an emerging trend, due in part to the diversity
and complexity of geospatial data, especially in real-time scenarios such as emergency response, where information systems often need to be built on-the-fly (Lemmens et al., 2006)
ch AInIng geosp At IAL ser vIce s
Interoperability, or the ability of software ponents to interact with minimal knowledge of the underlying structure of other components, has become a basic requirement for distributed information systems (Sheth, 1999), and so it is also critical to GIS and to geospatial web services The Open Geospatial Consortium (OGC) has formed working groups within the GIS community to foster interoperability between geodata and geospatial services in order to define well-estab-lished interfaces to a wider range of geospatial web services (Whiteside, 2005) Table 1 lists a sample of key geospatial web services interfaces
com-as defined by OGC
The notion of chaining of geospatial web services (Alameh, 2003) emerged as a mecha-nism for assembling or combining individual geospatial web services to create customized web applications A simple chain of the above listed geospatial web services may be that constructed
to produce a coverage portrayal service (CPS) that assembles an image retrieved from various web coverage services (WCS) and portrays it to
a web coordinate transformation service (WCTS) for the transformation of the composite image into another coordinates reference system for proper alignment with other geodata (Alameh, 2003).The OGC and ISO Technical Committee 211 (ISO/TC211) have jointly developed international standards for geospatial service architecture and have defined interoperable geospatial web service interfaces (ISO 19119, 2005; Percivall 2002) Transparent, translucent and opaque ser-vice-chaining approaches have been defined by these organizations according to the degree of transparency of the web service chain complex-ity to the client:
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Geospatial Web Service Chaining
• Transparent or user-defined chaining:
the user or client application defines and
controls completely the structure and order
of execution of the individual services
Ob-viously, the user has prior knowledge about
the geospatial web services to be used in the
chain
• Opaque or aggregate service chaining:
a single aggregate service comprises and
coordinates all individual geospatial web
services in the chain Opaque chaining
pres-ents the aggregate service to the user having
no awareness of the individual services
• Translucent or workflow-managed
chain-ing: As the name implies, translucent
chaining takes place between transparent
and opaque chaining The user invokes a
workflow management service or mediated
service that acts as a broker and constructs
and manages chains of geospatial web
services Translucent chaining promises to
reduce the transparency or exposure of
geo-spatial service chaining to the user because
mediated services handle most of the work
required to assemble, manage, and execute
the geospatial service chains However, these
require a certain degree of intelligence, for mediated services to be able to liberate us-ers to the task of constructing the chain of geospatial web services, encapsulating the details and complexity For this reason, they could be inherently complex and challenging
to design and implement (Alameh, 2003) This ‘intelligence’ comes in the form of se-mantic discovery and interpretation of each service’s capabilities and data consumption needs
ch ALLenges In ser vIce
ch AInIng
Several challenges remain before robust, reliable and easily developed geospatial web service chains become commonplace Some of these challenges stem from the use of web services in general (Kaye, 2003) and others are specific of geospatial needs
Many of the important issues in web service chaining that remain to be solved are semantic
in nature: creating, publishing and consuming descriptions of how web services can be discov-
Table 1 Examples of geospatial web services
Service name Service description
Web Map Service (WMS) Dynamically produces spatially referenced maps of client-specified criteria from one or
more geographic datasets, returning pre-defined maps in an image or graphics format (png, jpeg, gif)
Web Feature Service (WFS) Allows clients to filter and retrieves vector representation of geospatial features and
feature collections Web Coverage Ser vice
(WCS)
Retrieves client-specified coverage or image dataset Catalog Service (CSW) Retrieves object metadata stored that meets specified query criteria
Gazetteer Service Retrieves location geometries for specified geographic names
Web Terrain Service (WTS) Dynamically produces perspective views from geographic feature and/or coverage data,
returning pictorial renderings of data in an image or graphics format Web Coordinate Transforma-
tion Service (WCTS) Transforms the coordinates of feature or coverage data from one coordinate reference system (CRS) to another, including for example, conversions and rectification Coverage Portrayal Service
(CPS)
Dynamically produces pictorial renderings in an image or graphics format of a coverage subset dynamically retrieved from a Web Coverage Service (WCS)
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Geospatial Web Service Chaining
ered and composed on-the-fly according to user
needs The research area of semantic web services
(McIlraith et al., 2001) proposes the markup of
web services description by means of semantic
web languages such as S (Semantic
OWL-based Semantic Web Service Ontology) and
WSMO (Web Service Modeling Ontology) (Lara
et al., 2004) Another important issue is related to
security, in the sense of setting policies for access
control and authentication For example, consider
two or more services that need to interact properly
to complete a service chain in a critical scenario
It is necessary to ensure that communications and
transactions among these services are conducted
in a secure environment and that messages are
reliably delivered to the correct destinations
Also, the adoption of e-commerce features such
as service costs, billing and payment mechanisms
in web services offers a great opportunity for
e-commerce to take a central role in the growing
online economy (Medjahed et al., 2003) Table
2 summarizes some of these challenges for web
service chaining
In addition to the challenges for web services
listed in Table 2, other challenges apply more
directly to geospatial web services (Tu et al.,
2004) In practice, chaining geographic services
is nontrivial (Lemmens et al., 2006), in part
because geographic data are quite varied and,
thus, different from other types of data in that
they may include multiple versions of the same
phenomena, and may be massive data sets
Geo-spatial service monitoring, how to verify that what
is described is what is delivered, and geospatial
service compliance with standards, how to ensure
geospatial web service chains are compliant to
particular specifications such those provided by the OGC In addition, common GIS scenarios or use cases such as hydrologic analysis or environ-mental walk-through simulations, require huge amounts of geospatial data for browsing large vector datasets (especially when represented in XML such as the case for Geography Markup Language, GML) and high-resolution satellite imagery Some effective methods are emerging for integrating heterogeneous data sets from dif-ferent application domains and visualizing them
to the user (Hobona et al., 2006) Due to the large volumes of geospatial data, especially in XML (GML) format, there is a critical requirement on the performance on the data transfer Table 3 sum-marizes some of these challenges for geospatial web service chaining
c onc Lus Ion
The future scenario for geospatial web service chaining may not ever reach a wholly automated, spontaneous service chaining for a set of self-de-scribing geospatial web services, however in the near term semi-automated solutions are emerging
to help users solve geographical problems with remote services Geospatial web services listed
in Table 1 mainly deal with the delivery of data instead of advanced processing performed online More complex geospatial services have to be specified in order to distribute over the Internet all the functionalities (computation, analysis, etc.) common in our desktop GIS The first steps towards advanced geoprocessing services online are outlined by the recently published OpenGIS
Table 2 Challenges in web service chaining
• Semantics: dynamic discovery, composition
• Security: access control, authentication
• Transactional integrity
• E-commerce features: billing, accounting, paying mechanisms
• Quality of Service (QoS): reliability, robustness
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Geospatial Web Service Chaining
Web Processing Service discussion paper (Schut
and Whiteside, 2005), which provides interface
specifications to enable geospatial web services to
support a limited range of geo-processing tasks,
by creating accessible libraries of geo-processing
algorithms under the appearance of geospatial
web service chains
r eferences
Alameh, N (2003) Chaining Geographic
Infor-mation Web Services IEEE Internet Computing,
7(5), 22-29
Fielding, R.T (2000) Architectural Styles and the
Design of Network-based Software Architectures
PhD thesis, University of California, Irvine
Hobona, G., James, P., & Fairbain, D (2006)
Web-Based Visualization of 3D Geospatial Data
Using Java3D IEEE Computer Graphics and
Ap-plications, 26(4), 28-33
ISO 19119:2005, Geographic Information –
Ser-vices ISO/TC 211 Geographic
information/Geo-matics
Kaye, D (2003) Loosely coupled: the missing
pieces of Web services, Marin County, California:
RDS Press
Lara, R., Roman, D., Polleres, A., & Fensel, D
(2004) A conceptual comparison of WSMO and
OWL-S Proc of European Conference on Web
Services 2004, Springer LNCS, 254-269
Lemmens, R., Wytzisk, A., de By, R., Granell, C., Gould, M., & van Oosterom, P (2006) Integrating Semantic and Syntactic Descriptions to Chain Geographic Services IEEE Internet Computing, 10(5), 42-52
McIlraith, S.A., Son, T.C., & Zeng, H (2001) Semantic web services IEEE Intelligent Systems, 16(2), 46-53
Medjahed, B., Benatallah, B., Bouguettaya, A., Ngu, A.H.H., & Elmagarmid, A.K (2003) Busi-ness-to-business interactions: issues and enabling technologies Intl Journal on Very Large Data Bases, 12(1), 59-85
Peng, Z.-R & Tsou, M.-H (2001) Internet GIS: distributed geographic information services for the internet and wireless networks, Hoboken, New Jersey: John Wiley & Sons, Inc
Percivall, G (Ed.) (2002) The OpenGIS Abstract Specification Topic 12: OpenGIS Service Archi-tecture, Open Geospatial Consortium Document number 02-112
Schut, P & Whiteside, A (Eds.) (2005) GIS Web Processing Service Open Geospatial Consortium, Discussion paper Document number 05-007
Open-Sheth, A P (1999) Changing Focus on erability in Information Systems from System, Syntax, Structure to Semantics In M F Good-child, M.J Egenhofer, R Fegeas & C.A Kottman (Eds.), Interoperating Geographic Information Systems, Kluwer (pp 5-30)
Interop-• Management: monitoring, compliance with standards
• Duplicity: multiple versions of the same geographical phenomena will exist
• Performance: GML vs binary transmission formats
• Simulation: Hydrologic analysis, pollution analysis, traffic simulation, walk-through tions, terrain flight simulations, emergency response exercises
simula-• Semantics: geo-ontologies will help to clarify meanings during geo-web service chaining.
Table 3 Challenges in geospatial web service chaining
Trang 23
Geospatial Web Service Chaining
Tu, S., Flanagin, M., Wu, Y., Abdelguerfi, M.,
Normand, E., Mahadevan, V., Ratcliff, J & Shaw,
K (2004) Design strategies to Improve
Perfor-mance of GIS Web Services Proc of International
Conference on Information Technology (ITCC)
2004 Volume II, Las Vegas, NV
Vinoski, S (1997) CORBA: Integrating diverse
applications within distributed heterogeneous
environments IEEE Communications Magazine,
45(2), 46-55
Whiteside, A (Ed.) (2005) OpenGIS web
ser-vices architecture description Open Geospatial
Consortium, Discussion paper
key t er Ms
GML: The Geography Markup Language
is a XML grammar defined by OGC to express
geographical features To help users and
devel-opers to structure and facilitate the creation of
GML-based application, GML provides GML
profiles that are XML schemas that extend the
very GML specification in a modular fashion
A GML profile is a GML subset for a concrete
context or application but without the need for the
full GML grammar, simplifying thus the adoption
of GML and facilitating its rapid usage Some
common examples of GML profiles that have been
published are Point Profile, for applications with
point geometric data, and GML Simple Features
profile, supporting vector feature requests and
responses as the case of WFS
ISO/TC211: ISO Technical Committee 211 in
Geographic information/Geomatics is in charge
of establishing a set of standards for digital
geo-graphic information concerning objects or
phe-nomena that are directly or indirectly associated
with a location relative to the Earth
OGC: The Open Geospatial Consortium is an
international industry consortium participating in
a consensus process to develop publicly available interface specifications OGC members include government agencies, commercial companies, and university research groups
Service Chain: Sequence of services where,
for each adjacent pair of services, occurrence of the first service is necessary for the occurrence for the second service [paraphrased from ISO 19119]
Service: Functionality provided by a service
provider through interfaces [paraphrased from ISO 19119]
Service Consumer: The role of service
con-sumer requires certain requirements and needs that are fulfilled by one or more web services available over the Internet
Service Metadata: Metadata describing the
operations and geographic information available
at a particular instance of a service [paraphrased from ISO 19119]
Service Provider: The role of service provider
provides software applications as web services, creating functional descriptions and making them available in public registries
SOAP: A protocol for exchanging XML-based
messages between services over a computer network, usually the Internet A SOAP message may think of as an envelope that wraps mainly two elements: a header, with useful information
to interpret the data, and a body, which ally contains the exchanged data among web services
actu-UDDI: A specification/protocol that allows
service providers to publish service descriptions
in a service registry and service consumers to discover services in a service registry according
to their service descriptions, usually described in
WSDL The main element of UDDI is the ness registry, a service registry based on XML
busi-that contains three kind of information for each
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Geospatial Web Service Chaining
web service published: white pages or contact
information, yellow pages include business
categorization, and green pages that comprise
technical information of the web service along
with a link to its WSDL description
WSDL: A XML-based specification that
al-lows service providers to describe syntactically
service interfaces Basically, a WSDL description
allows service providers to describe a web
ser-vice’s function and its input and output parameters
in order to be discovered and invoked by client
applications and other web services
Trang 25
Chapter XXV Multi-Agent Systems for
Distributed Geospatial Modeling, Simulation and
George Mason University, USA
Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.
Abstr Act
Multi-agent system is specialized in studying the collective effects of multiple intelligent agents An intelligent agent is a computer system with autonomous action in an environment This technology is especially suitable for studying geospatial phenomena since they are complex in nature and call for intertwined actions from different forces This chapter describes multi-agent systems and their applica- tion in geospatial modeling, simulation and computing Geospatial data integration and mining are discussed.
Trang 26
Multi-Agent Systems for Distributed Geospatial Modeling, Simulation and Computing
This section reviews applications of multi-agent
systems in geospatial data integration,
model-ing, simulation, and computing Agent is a
com-puter system with autonomous action in some
environment (Weiss, 2000) This is by no means a
comprehensive or concise definition for an agent
As pointed out by many scientists, no consensus
has been reached on the definition of an agent
(Franklin & Graesser, 1997; Russell & Norvig,
2002; Weiss, 2000) Readers who are interested
in the different interpretations and typologies of
agents in different contexts may refer to Weiss
(2000) and Nwana (Nwana, 1996) for an in-depth
discussion In this context, the definition focuses
on the most commonly agreed-upon property of
agents - namely, their autonomous ability This
is the backbone in forming multi-agent systems
Multi-agent systems are formed by many agents
that interact with each other These systems
em-phasize the interaction between agents and the
emergent effects from relatively simple individual
behaviors of agents One of the key promises of
multi-agent systems is its capability to decompose
complex geospatial problems into manageable
pieces Agents communicate and interact with
each other through an understanding of common
ontology (or domain-specific vocabulary) and
communication languages Agents can be
man-aged and discovered through a centralized
direc-tory, peer-to-peer discovery, or hybrid mechanism
Agent mobility provides a mechanism to extend stabilities and sustainability of geospatial services
in a heterogeneous distributed environment Table
1 summarizes some of the most popular ties of agents that are important for interactions
proper-in a distributed multi-agent system Table 2 lists some popular platforms for developing multi- agent systems.
Standards are emerging to enable agent to communicate in ubiquitous environment FIPA (Foundation for Intelligent Physical Agents) is one of the major efforts in evolving standards and specifications for agent architecture, agent
ontology, and agent communication languages Through a well-defined ontology, geospatial data integration and geospatial service chains can be
completed with reasoning support Applications
of multi-agent systems in geospatial fields are
quickly expanding as these systems promise simpler programming, robustness, parallelism, scalability, cost-effectiveness, and geographic distribution (Stone & Veloso, 2000) This section
focuses on exploring potentials of multi-agent
technology in a distributed geospatial ing environment First, a comparison between
comput-the multi-agent approach and web service
ap-proach – the most popular distributed technology
- is given Next, several application aspects are
discussed, i.e., geospatial data integration, geospatial modeling/simulation, and geospatial
data mining These applications are just the tip
of the iceburg Many are beyond the scope of this
Table 1 Properties of an agent(Franklin & Graesser, 1997; Russell & Norvig, 2002; Weiss, 2000)
Reactive reaction based on its sense
Autonomous responses based on its own experiences
Rational maximize its own interest
goal-oriented pursue an goal
temporally continuous deals with continuous process
Mobile able to transport itself from platform to platform
Communication interactions on another level of abstraction - language