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CSISS Center for Spatial Information Science
and Systems
The Implementation of ISO TC 211
Standards in Geospatial Web Service
Environments
Meixia Deng & Liping Di Center for Spatial Information Science and Systems (CSISS)
George Mason University (GMU)
4400 University Drive, MSN 6E1
Fairfax, VA 22030
http://csiss.gmu.edu
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Outline
• Background
– Changes, challenges and new demands in Earth Sciences
– Urgent needs for geospatial web service environments and
why
• Limitations of traditional approaches and systems
• To meet new demands and challenges
• Principles of a Geospatial Web Service Environment
– Fundamentals
– Architecture Design and Implementation Guidance
• Standards In Action (Examples)
– Implementation of common data environment (CDE) and
common service environment (CSE) with OGC/ISO standards
– Implementation of Geospatial Data Provenance With ISO
19115 and ISO 19115-2 Lineage Model
• Discussion
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Changes, Challenges and New Demands in Earth
Sciences
• Changing Earth science (ES) for a Changing Planet – Shaped by rapid advances in technology
– Increasingly data-intensive & compute-intensive
– ES research, education and application require easy access to and use of
large volumes of multi-source ES data
– Computer-based data visualization, processing and analysis and model
simulation have become standard methods in ES studies
• Imminent Challenges in ES – How to efficiently transform Earth observations (data) into applicable
products (information), and intelligible results and discoveries (knowledge)?
– How to effectively provide reasoned solutions to problems we face with
climate change, environment protection, natural hazards, and other global
issues?
• New Demands
– Paradigm shift for methodological changes in ES
– Societal demands – e.g. efficiency, quality, and personalized
products and services for better understanding the Earth
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Urgent Need for Geospatial Web Service
Environments
• To meet the demands and challenges of ES
– Traditional approaches and systems have many
limitations
• Insufficient in enabling access, integration and analysis
of historical and real-time information from various
sources in a reliable, accurate, consistent, seamless and
understandable way and in the fastest possible time.
• Big Data and geoprocessing-modeling issues
• To encourage sharing and collaboration
• To engage community and citizen scientists
• To promote scientific democracy
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Why A Geospatial Web Service Environment
• Advantages
– Leveraging the latest advances in Web service,
geospatial interoperability and cyberinfrastructure
– Overcoming major limitations of current systems in
• data, information and knowledge services,
• near real-time and on-demand capability
• Interoperability among data, service and systems
– Approaching to an information system that can
provide complete information to support research,
education, and applications (e.g., decision-
making support).
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CSISS Efforts
• During the past decade, CSISS has dedicated to
developing geospatial Web service technology and
developed a series of operational geospatial web
service environments, which are open and freely
accessible to worldwide users.
– GeoBrain (http://geobrain.laits.gmu.edu)
– DEMExplorer (http://ws.csiss.gmu.edu/DEMExplorer/)
– CropScape (http://nassgeodata.gmu.edu/CropScape/)
– VegScape (http://nassgeodata.gmu.edu/VegScape/)
– GADMFS (the Global Agricultural Drought Monitoring and
Forecasting System) (http://gis.csiss.gmu.edu/GADMFS/)
• Despite very different foci, functionalities,
usages, application areas, and targeted
audiences, all of them share a common
infrastructure.
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Common Infrastructure of the Environments
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Fundamentals (1/3)
• Addressed interoperability at data, service (function) and
system levels
– OGC, ISO, W3C and OASIS standards compliant
– Design and implementation of Common Data Environment
(CDE) for providing standard interfaces to discover and
access diverse data and information in distributed data
archives and repositories
– Design and implementation of Common Service
Environment (CSE) for both human and machine users to
discover and invoke geoprocessing services (analytic
functions) at a standard way for processing and analyzing
data obtained from CDE
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Fundamentals (2/3)
• Addressed service-ability for meeting the Big Data and
geoprocessing-modeling challenges
– To provide sufficient data services: any data available in the
system are coupled with adequate metadata and data pre-
processing services (e.g. sub-setting, reformatting,
resampling, and re-projection) so that the data can be easily
discovered, visualized, customized, retrieved and integrated
through the system
– To provide sufficient information services: adequate
geoprocessing and analysis functions are readily available
and applicable to data in the system as interoperable and
dynamically chainable and executable geospatial Web
services so that online, on-demand and near real-time
geoprocessing and analysis of data can be performed on-
the-fly to generate user-required information products.
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Fundamentals (3/3)
• Systematic framework – Interoperability - the system has the capability of the plug-in-and-play
over the web so that drought related geospatial resources (e.g., data,
services, service systems) from other sources can be plugged into the
system on-the-fly for meeting the on-demand needs of a wider, more
diverse audiences of both human and machine users (the system is
interoperable at data, service, and system levels).
– Scalability - the system is scalable from the construction
perspective (component-based and modular) and user-
orientation perspective (able to deal with any scale from local to
global per users’ requests).
– Reusability – the system is reusable at function, component, and
system levels.
– Adaptability - the system is flexible, self-evolvable and
maintainable.
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Implementation of CDE and CSE (1/5)
• Standards Compliance
ISO/TC 211 standards
W3C and OASIS standards
OGC standards: WCS, WMS, WFS, WPS,
CSW,…
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Implementation of CDE and CSE (2/5)
• ISO/TC211 Standards Observed
– ISO 19107:2003—Spatial Schema
– ISO 19108:2003—Temporal Schema
– ISO 19115:2003—Metadata
– ISO 19119:2005—Services
– ISO19125-1:2004 (Geographic information - Simple Feature
Access - Part 1: Common Architecture); ISO 19125-2:2004
(Geographic information - Simple feature access - Part 2:
SQL Option);
– ISO 19128 Web Map Service (OGC WMS)
– ISO 19136 (Geographic information - Geography Markup
Language (OGC GML)
– ISO 19142:2010 Web Feature Service (OGC WFS)
– More …
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Implementation of CDE and CSE (3/5)
• CDE is implemented with
– OGC standards compliant data services
– catalogue federation and component registration services
• CSE has been implemented with
– ISO/OGC standards (e.g. WPS) for geoprocessing
– augmented CSW and CFS with ontology for service discovery
and registry.
– W3C standards (e.g. Web Service Description Language
(WSDL), Simple Object Access Protocol (SOAP) for binding)
and OASIS standards (e.g. WS-BPEL) for Web service and
service chaining
-
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Implementation of CDE and CSE (4/5)
• With CDE and CSE, data and services in distributed
systems can be accessed and used over Internet from a
single point of entry. CDE and CSE enable federated
discovery of and access to distributed data and
information coupled with interoperable, personalized and
on-demand data and processing services.
• Catalog Federation and Component Registry Services
– Standards compliant:
• OGC Catalog Service for the Web (CSW) Specification
• ISO 19119 Metadata Profile
• ISO 19115:2003—Metadata
• OASIS ebRIM Profile
• OpenSearch
– Support publishing and discovery of distributed geospatial
data and associated services
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Implementation of CDE and CSE (5/5)
• OGC Data Services
– Web Map Service
– OGC WMS ( also as ISO 19128 Web Map Service)
– OGC WMS-Tiling (WMTS) built on WMS
– Web Coverage Service (WCS)
- OGC WCS Specification
– Web Feature Service (WFS)
- OGC WFS Specification (also as ISO 19142:2010)
– Coordinate Transformation Services
- OGC CTS
• OGC WPS
– Implemented a large number of WPSs, over 80 of them
based on GRASS
• BPELPower –workflow engine
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Implementation of Geospatial Data Provenance
• Importance
– data quality and usability evaluation, data trail audition,…
– workflow replication and product reproducibility
– Integration of generation of the geospatial provenance
metadata and execution of geo-processing workflow
promises great benefit since they are complementary.
• Challenges
– The heterogeneity of data and computing resources in the
distributed environment constructed under the service-
oriented architecture (SOA) brings a great challenge to
resource integration.
– Specifically, the issues, such as the lack of interoperability
and compatibility among provenance metadata models and
between provenance and workflow, create obstacles for the
integration of provenance, and geo-processing workflow.
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Implementation of Geospatial Data Provenance
• A proposed method
– To break the provenance heterogeneity through recording
provenance information in a standard lineage model defined
in ISO 19115:2003 and ISO 19115-2:2009 standards.
– To bridge the gap between provenance and geo-processing
workflow through extending both workflow language and
service interface, making it possible for the automatic
capture of provenance information in the geospatial web
service environment.
• The proposed method is implemented in GeoBrain.
– The testing result from implementation shows that the
geospatial provenance information is successfully captured
throughout the life cycle of geo-processing workflows and
properly recorded in the ISO standard lineage model.
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Discussion (1/2)
• Why the common infrastructure of an open, three-tier,
component-based, standards-compliant, and SOA- based
geospatial web service system?
– organizing and delivery of large volumes of multi-source
datasets;
– disseminating data, information, and model results quickly to
a wide audience;
– enabling thorough, collaborative, and on-demand analysis to
users’ best advantages.
– highlighting the role of data-intensive science in transforming
raw observations into applicable, intelligible results and
discoveries.
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Discussion (2/2)
• Why a standards-compliant approach?
– Enabling interoperability in building all the open
environments in CSISS, which proves to be very successful.
• the best option so far for enabling wide interoperability in
building open data and information environments, despite some
existing arguments about the costs vs. benefits of adopting
standards.
– Enabling reusability. Components developed in GeoBrain
have been successfully used for building other environments
in CSISS. Great savings!
• It still remains a grand challenge to enable adequate and
proper interoperability among different data, services, and
systems due to technical, cultural, and organizational
barriers.
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References (1/2)
• Deng, M., L. Di, W. Han, A. Yagci, C. Peng and Gil Heo, 2013. Web-
service-based Monitoring and Analysis of Global Agricultural Drought,
Photogrammetric Engineering & Remote Sensing (PE&RS), 79 (10),
pp.929-943.
• Di, L., Y. Shao, and L. Kang , 2013. Implementation of Geospatial Data
Provenance in a Web Service Workflow Environment With ISO 19115
and ISO 19115-2 Lineage Model, IEEE Transactions On Geoscience
And Remote Sensing, 51(11), pp. 5082-5089.
• Deng, M. and L. Di, 2013. Building Open Environments To Meet Big
Data Challenges In Earth Sciences, Big Data Techniques and
Technologies in Geoinformatics (Editor: Hassan Karimi), CRC Press,
Chapter 4, pp. 67-88
• Deng, M. and L. Di, 2010. Facilitating Data-intensive Research and
Education in Earth Science - A Geospatial Web Service Approach, LAP
LAMBERT Academic Publishing GmbH & Co. KG, Saarbrücken,
Germany. ISBN: 978-3-8383-9714-6.
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References (2/2)
• Deng, M. and L. Di, 2010. GeoBrain for Data-Intensive Earth
Science (ES) Education, Advanced Geoinformation Science (C.
Yang, D. Wong, Q. Miao and R. Yang, editors), CRC Press.
• Deng, M. and L. Di, 2009. Building an Online Learning and
Research Environment to Enhance Use of Geospatial Data,
International Journal of Spatial Data Infrastructures Research,
2009, 4:77-95.