IN11B-1024 INVITED
A Reusable Semantic Virtual Observatory Platform
Multi-discipline Virtual Observatories are becoming more prevalent as more scientists need to access data from a broad range of disciplines that may be available from varied repositories. It is becoming increasingly important for there to be tool and service support to help professional and citizen scientists access and manipulate appropriate data. In this talk, we will introduce a multi-discipline semantically-enabled virtual observatory platform, provide some examples of how it is being used today, describe a successful effort to reuse the platform in a noticeably different set of science areas, and provide suggestions of techniques, tools, and services that may be of use in scientific applications that require complex interdisciplinary data integration.
IN11B-1025
GEO Water Cycle Activities and Plans
The Group on Earth Observations (GEO) consists of more than 70 countries and 40 international organizations which are working together to develop the Global Earth Observation System of Systems (GEOSS). Since its launch in 2004, GEO has stimulated a wide range of activities related to data systems and their architecture, the development of science and technology to support observational programs, user interactions and interfaces, and capacity building. GEO tasks directed at Water Resources Management, one of the nine GEO Societal Benefit areas, are an integral part of these developments. They draw heavily upon the activities of the Integrated Global Water Cycle Observations (IGWCO) theme and on the activities and infrastructure provided through GEO and its committees. Within the GEO framework the water related activities have been focused on four specific tasks namely integrated data set development; information for floods, droughts and water management; water quality, and capacity building. Currently these efforts are being facilitated by the IGWCO theme that was formed under the former Integrated Global Observing Strategy Partnership (IGOS-P). With the dissolution of this partnership, other mechanisms, including the GEO Water Cycle Community of Practice, are being considered as new opportunitites for coordinating the work of the theme and the water-related GEO tasks. This talk provides a description of the GEO water tasks and reviews the progress that has been made in addressing them. It also provides a perspective on new opportunities and briefly describes some of the mechanisms, such as the Water Cycle Community of Practice, that could be expanded to coordinate a more comprehensive set of water tasks and greater community involvement.
IN11B-1026
Linking Management Actions to Interactive Ecosystem Report Cards via an Ontology
IINTRODUCTION
The Health-e-Waterways Project is a three way collaboration between the University of Queensland,
Microsoft Research and the Healthy Waterways Partnership (SEQ-HWP)(over 60 local government, state
agency, universities, community and environmental organizations). The project is developing a highly
innovative framework and set of services to enable streamlined access to an integrated collection of real-
time, near-real-time and static datasets acquired through ecosystem monitoring programs in South East
Queensland. Using a novel combination of semantic web technologies, scientific data servers, web services,
GIS visualization interfaces and scientific workflows, we are enabling the sharing and integration of high
quality data and models, through a combined integrated water information management system and Web
portal.
DYNAMIC GENERATION OF ECOSYSTEM HEALTH REPORT CARDS
SEQ-HWP is responsible for the Ecosystem Health Monitoring Program (EHMP) in South East Queensland.
This currently involves sampling 30 freshwater indicators at 100 sites twice a year and 250 estuarine/marine
sites every month. The EHMP data sets are statistically aggregated and standardized to produce ecosystem
health grades that are published annually in hard copy EHMP Report Cards. Politicians and planners use
the report cards to make decisions with respect to land use, water quality, allocations and investments in
water recycling plants etc.
To date, these report cards have been largely produced manually, by calculating standardized scores (0-1)
across 5 indicators and 16 indices (physical, chemical, nutrients, ecosystem processes, acquatic
macroinvertebrates and fish) and grades from A-F for each catchment and season (spring and autumn).
Currently this process takes about 5 months.
For the past 6 months, we have been working with the SEQ-HWP staff, developing software services that will
enable the report cards to be generated dynamically via a Web-based Map interface to an underlying
database that contains the EHMP water quality and quantity monitoring data. The GUI enables users to
specify and query:
- Spatial regions of interest through a GoogleEarth or the Microsoft VirtualEarth interface.
- Concepts or indicators of interest through the EHMPOntology.
- Seasons or years of interest through a timeline.
A Report Card Grade is generated for the specified catchment and period. Users can retrieve raw data by
clicking on a grade this displays the corresponding EcoH plot, dynamically generated from the 5 indicators in
the underlying SQL Server database. Clicking on an EcoH plot, displays the actual raw data (16 indices)
used to generate the indicators and plots.
CONCLUSIONS
Numerous state, national and international agencies are advocating the need for standardized frameworks
and procedures for environmental accounting. The Health-e-Waterways project provides an ideal model for
delivering a standardized approach to the aggregation of ecosystem health monitoring data and the
generation of dynamic, interactive Report Cards (that incorporate links back to the raw data sets). The
system we have described here will not only save agencies significant time and money, but it can be used to
guide regional, state and national environmental policy development, based on accurate and timely evidential
data.
http://www.health-e-waterways.org/
IN11B-1027 INVITED
SWEET 2.0: Moving Toward Community-Based Ontologies
The Semantic Web for Earth and Environmental Terminology (SWEET) project has produced an upper-level
ontology set for Earth system science. These ontologies have been under development for several years
and include concepts of science, data, and services. SWEET includes mappings to other controlled
vocabulary lists such as the GCMD science keyword and CF standard names.
The initial design (SWEET 1.0) defined about 1700 concepts organized by facet, such as: physical property,
small-scale process, large-scale phenomena, living and non-living substance, Earth realm, space, time, units,
etc. For Version 2.0, the number of concepts has doubled to 3500 and the facet structure is similar.
However, there no longer remains a one-to-one mapping of a facet to an ontology file. The original 12
ontology files have been reorganized into nearly 100 files, organized by subject. This new design is much
more scalable, as it is easy for domain specialists to add content for their specialization by adding an
additional file. SWEET enables representations of all aspects of the Earth system (from core to heliosphere)
and more general aspects of planetary and solar science. It is anticipated that the ESIP Federation Semantic
Web Cluster will maintain this ontology set over the long-term.
http://sweet.jpl.nasa.gov
IN11B-1028
Semantic Data Integration and Ontology Use within the Global Earth Observation System of Systems (GEOSS) Global Water Cycle Data Integration System
The inadequacies of water cycle observations for monitoring long-term changes in the global water system, as well as their feedback into the climate system, poses a major constraint on sustainable development of water resources and improvement of water management practices. Hence, The Group on Earth Observations (GEO) has established Task WA-08-01, "Integration of in situ and satellite data for water cycle monitoring," an integrative initiative combining different types of satellite and in situ observations related to key variables of the water cycle with model outputs for improved accuracy and global coverage. This presentation proposes development of the Rapid, Integrated Monitoring System for the Water Cycle (Global-RIMS)--already employed by the GEO Global Terrestrial Network for Hydrology (GTN-H)--as either one of the main components or linked with the Asian system to constitute the modeling system of GEOSS for water cycle monitoring. We further propose expanded, augmented capability to run multiple grids to embrace some of the heterogeneous methods and formats of the Earth Science, Hydrology, and Hydraulic Engineering communities. Different methodologies are employed by the Earth Science (land surface modeling), the Hydrological (GIS), and the Hydraulic Engineering Communities; with each community employing models that require different input data. Data will be routed as input variables to the models through web services, allowing satellite and in situ data to be integrated together within the modeling framework. Semantic data integration will provide the automation to enable this system to operate in near-real-time. Multiple data collections for ground water, precipitation, soil moisture satellite data, such as SMAP, and lake data will require multiple low level ontologies, and an upper level ontology will permit user-friendly water management knowledge to be synthesized. These ontologies will have to have overlapping terms mapped and linked together. so that they can cover an even wider net of data sources. The goal is to develop the means to link together the upper level and lower level ontologies and to have these registered within the GEOSS Registry. Actual operational ontologies that would link to models or link to data collections containing input variables required by models would have to be nested underneath this top level ontology, analogous to the mapping that has been carried out among ontologies within GEON.
IN11B-1029
Developing a Domain Ontology: the Case of Water Cycle and Hydrology
A semantic web ontology enables semantic data integration and semantic smart searching. Several organizations have attempted to implement smart registration and integration or searching using ontologies. These are the NOESIS (NSF project: LEAD) and HydroSeek (NSF project: CUAHS HIS) data discovery engines and the NSF project GEON. All three applications use ontologies to discover data from multiple sources and projects. The NASA WaterNet project was established to identify creative, innovative ways to bridge NASA research results to real world applications, linking decision support needs to available data, observations, and modeling capability. WaterNet (NASA project) utilized the smart query tool Noesis as a testbed to test whether different ontologies (and different catalog searches) could be combined to match resources with user needs. NOESIS contains the upper level SWEET ontology that accepts plug in domain ontologies to refine user search queries, reducing the burden of multiple keyword searches. Another smart search interface was that developed for CUAHSI, HydroSeek, that uses a multi-layered concept search ontology, tagging variables names from any number of data sources to specific leaf and higher level concepts on which the search is executed. This approach has proven to be quite successful in mitigating semantic heterogeneity as the user does not need to know the semantic specifics of each data source system but just uses a set of common keywords to discover the data for a specific temporal and geospatial domain. This presentation will show tests with Noesis and Hydroseek lead to the conclusion that the construction of a complex, and highly heterogeneous water cycle ontology requires multiple ontology modules. To illustrate the complexity and heterogeneity of a water cycle ontology, Hydroseek successfully utilizes WaterOneFlow to integrate data across multiple different data collections, such as USGS NWIS. However,different methodologies are employed by the Earth Science, the Hydrological, and Hydraulic Engineering Communities, and each community employs models that require different input data. If a sub-domain ontology is created for each of these,describing water balance calculations, then the resulting structure of the semantic network describing these various terms can be rather complex, heterogeneous, and overlapping, and will require "mapping" between equivalent terms in the ontologies, along with the development of an upper level conceptual or domain ontology to utilize and link to those already in existence.
IN11B-1030
Development of an Ontology for Navigating and Discovering Hydrologic Data
Ontologies are increasingly emerging as a tool for bridging semantic heterogeneities, a problem that is prevalent in scientific data sets particularly across domains. The problem of semantic or descriptive heterogeneity is the result of historically independent annotation efforts by those that have collected or acted as steward for collected data responding to a specific mission statement without the realization that these data sets need to come together or at least complement each other in the long run. Because of this legacy approiach and the resulting status quo new ways need to be explored to overcome these annotation discrepancies not necessarily through a complete re-annotation but rather through tools that accept heterogeneity but try to mediate between the various existing description conventions. The hydrologic community is seeking to overcome these discrepancies for their constituency (through the Consortium of Universities for the Development of Hydrologic Sciences, CUAHSI, Hydrologic Information Systems, HIS, effort) by developing an information system in which disparate data sources can be accessed through a single search engine in which all data sources appear to be "one". To this end a data-discovery ontology for hydrologic data has been developed that permits registration of data sets to leaf concepts that are sufficiently detailed but one step more generic then what is typically used for data variable descriptions, for example Nitrate for all nitrate data collected. These leaf concepts originate from broader concept trees that can be navigated upwards through branches to more and more general concepts the top one of which is called HydroShpere. The ontology was in its first design meant to prove the concept and incorporated only a limited number of branches and leafs with detailed information only provided for the nutrients branch. Efforts are under way now to i) expose the ontology and its upper structure to wider audience vetting the approach and ii) to incorporate more branches to better capture a larger data spectrum that can be accessed for example in the USGS National Water Information System (NWIS), and EPA's STORET database.
IN11B-1031
Semantic Web Data Discovery of Hydrology and Other Earth Science Data at NASA Goddard Earth Sciences DISC
The enhancement of Mirador, a keyword-based data search and access web interface, by integrating an
Earth Sciences ontology for the data archived at the NASA Goddard Earth Sciences Data and Information
Services Center (GES DISC), promises to significantly improve the users' capability to quickly search for and
access data sets of interest. Mirador employs the power of Google's universal search technology for fast
metadata keyword searches, augmented by additional capabilities such as event searches (e.g., hurricanes),
searches based on location gazetteer, and data services such as format converters and sub-setters. To
optimally use the current Mirador's metadata keyword search capability, based on indexing, requires user
familiarity with the data sets in Mirador to know what keywords to use. Currently, Mirador does not allow
search by navigation.
The initial objective of the current Mirador enhancement effort is to develop an interface that presents users
with multiple views (e.g., Project, Instrument, Earth Science Parameter, Application) of all the available data in
Mirador. Starting with any of these top level views, users can simply and quickly navigate down any of the
trees to find data of interest. The key semantic technology behind these tree structures is an ontology based
on the Global Change Master Directory (GCMD) Directory Interchange Format (DIF). Use cases will be
presented to illustrate the enhanced Mirador. The current initial effort only begins to tap into the full power of
the Semantic Web. With the new, enhanced Mirador (expected release date of version 1 is December 2008),
users will be able to easily navigate the hierarchical path of their choice. Mirador's semantic infrastructure,
once fully realized, will enable interoperability with other semantically based hydrological data discovery and
service frameworks.
http://mirador.gsfc.nasa.gov
IN11B-1032 INVITED
Reactive Leadership: Divining, Developing, and Demonstrating Community Ontologies
The Marine Metadata Interoperability Project (known as MMI, on the web at http://marinemetadata.org) was
formed to provide leadership in metadata practices to the marine science community. In 2004 this meant
finding and writing about resources and best practices, which until then were all but invisible. In 2008 the
scope is far wider, encompassing comprehensive guidance, collaborative community environments, and
introduction and demonstration of advanced technologies to an increasingly interested scientific domain.
MMI's technical leadership, based on experiences gained in the hydrologic community, emphasized the role
ontologies could play in marine science. An early MMI workshop successfully incorporated a large number of
community vocabularies, tools to harmonize them in a common ontological format, and the mapping of terms
from vocabularies expressed in that format.
That 2005 workshop demonstrated the connections to be made among different community vocabularies,
and was well regarded by participants, but did not lead to widespread adoption of the tools, technologies, or
even the vocabularies. Ontology development efforts for marine sensors and platforms showed intermittent
progress, but again were not adopted or pushed toward completion.
It is now 2008, and the marine community is increasingly attentive to a wide range of interoperability issues. A
large part of the community has at least heard of "semantic interoperability", and many understand its critical
role in finding and working with data. Demand for specific solutions, and for workable approaches, is
becoming more vocal in the marine community.
Yet there is still no encompassing model in place for achieving semantic interoperability, only simple
operational registries have been set up for oceanographic community vocabularies, and only a few isolated
applications demonstrate how semantic barriers can be overcome. Why has progress been so slow? Are
good answers on the horizon? And if we build it, will the community come to use a semantic framework based
on ontologies?
This presentation will review 5 years of building community semantic interoperability. We'll examine this
community's adoption and application of ontologies, how well that has worked so far (and why), and where
(and how far) marine ontologies might go from here.
http://marinemetadata.org/agu2008communityontologies
IN11B-1033
Information Modeling to Assess Eruptive Behavior and Possible Threats on Mt. Etna, Italy
One of the best-studied volcanoes of the world, Mt. Etna in Sicily repeatedly exhibits eruptive scenarios that depart from the behavior considered typical for this volcano. Episodes of intense explosive activity, pyroclastic density currents, dome growth, cone collapse, and phreatomagmatic explosions pose a variety of previously underestimated threats to human lives in the summit area of the volcano. However, retrospective analysis of these events shows that they were likely caused by the same very sets of premises and starting conditions as "normal" effusive eruptions, yet combined in an unexpected, probably unique, way. Physical modeling tells us what may happen in terms of physical parameters but not what events we will actually see on a volcano. Bayesian modeling of volcanoes can unite physical parameters and observed events but, unlike physics, it lacks strictness of terms used to describe the events and, hence, may fail to provide a reasonably impartial, complete and self-consistent set of possible scenarios to be expected. Therefore, a tool is needed to process the observational knowledge as strictly as physical matters are treated by mathematics to provide an appropriate event-based framework for assessment of natural hazards during volcanic eruptions. This task requires a modeling not of the volcano itself but of our knowledge of it, and therefore falls into the field of informatis, knowledge engineering, and artificial intelligence. We involved an approach of artificial intelligence developed specially for the needs of geoscience, the method of event bush. Scenarios inferred from event bush fit the observed ones and allow one to foresee other low-probable events that may occur at the volcano. Application of the event bush provides a more impartial vision of volcanic phenomena and may serve as an intermediary between physical modeling, the expert knowledge and numerical assessment, e.g., by means of Bayesian belief networks.
IN11B-1034
Semantic Web Approach and Classification of Geoscience Metadata
This presentation is dealing with the Semantic Web approach for the mapping and usage of inner and outer
relations of geoscience metadata objects. Geoscience products often consist of data products (e.g. data
sets, data files, data granuals) and appropriate metadata objects (e.g. XML documents). A classification of
the metadata objects related to project, platform, instrument, product type, ... makes it easier in order to
identify the inner semantic relations of documents of one class as well as the relations to documents in other
classes. The new GFZ ISDC ontology concept is using an -in addition to NASA's GCMD- extended approach.
Not only new features of existing metadata classes are introduced in this concept but also new classes have
been created. The new ISDC metadata classification and the first results modeling and using the semantic
correlations are presented in this talk.
http://isdc.gfz-potsdam.de
IN11B-1035
Semantic Web Infrastructure Supporting NextFrAMES Modeling Platform
Emerging modeling frameworks offer new ways to modelers to develop model applications by offering a wide range of software components to handle common modeling tasks such as managing space and time, distributing computational tasks in parallel processing environment, performing input/output and providing diagnostic facilities. NextFrAMES, the next generation updates to the Framework for Aquatic Modeling of the Earth System originally developed at University of New Hampshire and currently hosted at The City College of New York takes a step further by hiding most of these services from modeler behind a platform agnostic modeling platform that allows scientists to focus on the implementation of scientific concepts in the form of a new modeling markup language and through a minimalist application programming interface that provide means to implement model processes. At the core of the NextFrAMES modeling platform there is a run-time engine that interprets the modeling markup language loads the module plugins establishes the model I/O and executes the model defined by the modeling XML and the accompanying plugins. The current implementation of the run-time engine is designed for single processor or symmetric multi processing (SMP) systems but future implementation of the run-time engine optimized for different hardware architectures are anticipated. The modeling XML and the accompanying plugins define the model structure and the computational processes in a highly abstract manner, which is not only suitable for the run-time engine, but has the potential to integrate into semantic web infrastructure, where intelligent parsers can extract information about the model configurations such as input/output requirements applicable space and time scales and underlying modeling processes. The NextFrAMES run-time engine itself is also designed to tap into web enabled data services directly, therefore it can be incorporated into complex workflow to implement End-to-End application from observation to the delivery of highly aggregated information. Our presentation will discuss the web services ranging from OpenDAP and WaterOneFlow data services to metadata provided through catalog services that could serve NextFrAMES modeling applications. We will also discuss the support infrastructure needed to streamline the integration of NextFrAMES into an End-to-End application to deliver highly processed information to end users. The End-to-End application will be demonstrated through examples from the State-of-the Global Water System effort that builds on data services provided through WMO's Global Terrestrial Network for Hydrology to deliver water resources related information to policy makers for better water management. Key components of this E2E system are promoted as Community of Practice examples for the Global Observing System of Systems therefore the State-of-the Global Water System can be viewed as test case for the interoperability of the incorporated web service components.
IN11B-1036
Water and Energy Cycle EOS House web portal (WECHO)
Water is the origin of life, the vast amount of water related Earth observation is of great value to water community users. This paper reports our research and development in providing the Water and Energy Cycle EOS House web portal (WECHO), a web-based tool, for the community to access water resource archived in EOS ClearingHouse (ECHO). WECHO aims to provide users the capabilities to search, browse and visualize data through common browsers, such as Internet Explore and Firefox. WECHO supports users to 1) access all ECHO functionalities, including registering as a new user, querying metadata and ordering delivery of earth observing data, subscribing to updates of interested metadata items and specific events; 2) semantically search ECHO with water ontologies integrated; 3) interactively access Earth Information Exchange (EIE) with the support of Semantic Web for Earth and Environmental Terminology (SWEET) and NOESIS.