IN34A-01 INVITED
Digital Watersheds and Water Observations Data
A digital watershed requires both a description of the physical environment through which water flows and a description of the flow of the water itself. Geographic information systems are appropriate for describing the physical environment. The Arc Hydro geographic data models for surface and groundwater systems are one way by which the physical environment of a watershed can be described in a GIS, and OGC web feature services provide a mechanism for accessing such data through the internet.. The CUAHSI Observations data model is useful for describing time series of water observations measured at point locations, such as streamflow, water quality, groundwater levels and climate data. CUAHSI WaterML web services provide access to such time series data through the internet. The combination of web feature services and WaterML web services provides both geographic and observational data services for digital watersheds. This paper will present an example application of such services using the San Marcos river basin and its underlying Edwards Aquifer in Texas as an example.
IN34A-02 INVITED
Scientific Workflows and the Sensor Web for Virtual Environmental Observatories
Virtual observatories mature from their original domain and become common practice for earth observation research and policy building. The term Virtual Observatory originally came from the astronomical research community. Here, virtual observatories provide universal access to the available astronomical data archives of space and ground-based observatories. Further on, as those virtual observatories aim at integrating heterogeneous ressources provided by a number of participating organizations, the virtual observatory acts as a coordinating entity that strives for common data analysis techniques and tools based on common standards. The Sensor Web is on its way to become one of the major virtual observatories outside of the astronomical research community. Like the original observatory that consists of a number of telescopes, each observing a specific part of the wave spectrum and with a collection of astronomical instruments, the Sensor Web provides a multi-eyes perspective on the current, past, as well as future situation of our planet and its surrounding spheres. The current view of the Sensor Web is that of a single worldwide collaborative, coherent, consistent and consolidated sensor data collection, fusion and distribution system. The Sensor Web can perform as an extensive monitoring and sensing system that provides timely, comprehensive, continuous and multi-mode observations. This technology is key to monitoring and understanding our natural environment, including key areas such as climate change, biodiversity, or natural disasters on local, regional, and global scales. The Sensor Web concept has been well established with ongoing global research and deployment of Sensor Web middleware and standards and represents the foundation layer of systems like the Global Earth Observation System of Systems (GEOSS). The Sensor Web consists of a huge variety of physical and virtual sensors as well as observational data, made available on the Internet at standardized interfaces. All data sets and sensor communication follow well-defined abstract models and corresponding encodings, mostly developed by the OGC Sensor Web Enablement initiative. Scientific progress is currently accelerated by an emerging new concept called scientific workflows, which organize and manage complex distributed computations. A scientific workflow represents and records the highly complex processes that a domain scientist typically would follow in exploration, discovery and ultimately, transformation of raw data to publishable results. The challenge is now to integrate the benefits of scientific workflows with those provided by the Sensor Web in order to leverage all resources for scientific exploration, problem solving, and knowledge generation. Scientific workflows for the Sensor Web represent the next evolutionary step towards efficient, powerful, and flexible earth observation frameworks and platforms. Those platforms support the entire process from capturing data, sharing and integrating, to requesting additional observations. Multiple sites and organizations will participate on single platforms and scientists from different countries and organizations interact and contribute to large-scale research projects. Simultaneously, the data- and information overload becomes manageable, as multiple layers of abstraction will free scientists to deal with underlying data-, processing or storage peculiarities. The vision are automated investigation and discovery mechanisms that allow scientists to pose queries to the system, which in turn would identify potentially related resources, schedules processing tasks and assembles all parts in workflows that may satisfy the query.
IN34A-03 INVITED
A Digital Synthesis Framework for Virtual Observatories
The Digital Synthesis Framework (DSF), being developed as part of the National Center for Supercomputing Applications' Technology Research Education and Commercialization Center (TRECC) project, provides a coherent framework for dynamically publishing visual analysis environments based on underlying observational and modeled information. The initial target of the TRECC effort will be the creation of digital observatories (e.g. digital watersheds) that allow exploration of data from sensor networks and environmental system models. The concept of a synthesis framework involves core capabilities for integrating data from multiple sources, enabling on-demand execution of scientific workflows, and the association of data outputs with multiple visualization and analysis widgets in a dynamically generated web application. In the DSF, NCSA's Cyberintegrator workflow environment is used to integrate data sources and invoke modeling modules. When the workflow is complete, it can be saved and run repeatedly as a service. A publication service allows the workflow outputs (which may be observational data or model outputs) to be associated with visualization widgets and embedded into a dynamically generated scenario viewer web application. The application can display data outputs from completed workflows or can trigger new workflows on demand. Along with maps, graphs, tables, and other displays, the application can display provenance information and links to associated reference material. As a concrete example, we present one of the TRECC pilot projects which presents a web-based dashboard about the status of the bay using information from sensors deployed in and around the bay in Corpus Christi Bay, Texas. The ability to dynamically publish environments that enable exploration of observational and modeled data represents a new level of sophistication in the evolution of virtual observatories and digital watersheds. In addition to presenting DSF capabilities, this presentation will explore the potential of such capabilities in supporting interdisciplinary communication and educational use of sensor networks and sophisticated modeling capabilities. In both cases, the ability of the DSF to enable expert input to focus attention through the selection of relevant data and visualizations provides an important intermediate between raw access to the information and static publication in the literature.
IN34A-04 INVITED
Semantic Sensor Web
Sensors are distributed across the globe leading to an avalanche of data about our environment. It is
possible today to utilize networks of sensors to detect and identify a multitude of observations, from simple
phenomena to complex events and situations. The lack of integration and communication between these
networks, however, often isolates important data streams and intensifies the existing problem of too much
data and not enough knowledge. With a view to addressing this problem, the Semantic Sensor Web (SSW)
[1] proposes that sensor data be annotated with semantic metadata that will both increase interoperability
and provide contextual information essential for situational knowledge. Kno.e.sis Center's approach to SSW
is an evolutionary one. It adds semantic annotations to the existing standard sensor languages of the Sensor
Web Enablement (SWE) defined by OGC. These annotations enhance primarily syntactic XML-based
descriptions in OGC's SWE languages with microformats, and W3C's Semantic Web languages- RDF and
OWL. In association with semantic annotation and semantic web capabilities including ontologies and rules,
SSW supports interoperability, analysis and reasoning over heterogeneous multi-modal sensor data. In this
presentation, we will also demonstrate a mashup with support for complex spatio-temporal-thematic queries
[2] and semantic analysis that utilize semantic annotations, multiple ontologies and rules. It uses existing
services (e.g., GoogleMap) and semantics enhanced SWE's Sensor Observation Service (SOS) over
weather and road condition data from various sensors that are part of Ohio's transportation network. Our
upcoming plans are to demonstrate end to end (heterogeneous sensor to application) semantics support and
study scalability of SSW involving thousands of sensors to about a billion triples. Keywords: Semantic Sensor
Web, Spatiotemporal thematic queries, Semantic Web Enablement, Sensor Observation Service [1] Amit
Sheth, Cory Henson, Satya S. Sahoo, "Semantic Sensor Web," IEEE Internet Computing, 12 (4), July-August
2008, pp. 78-83. http://knoesis.wright.edu/research/semsci/application_domain/sem_sensor/ [2] Amit Sheth
and Matthew Perry, "Traveling the Semantic Web through Space, Time and Theme," IEEE Internet
Computing, 12 (2), February-March 2008. http://knoesis.org/research/semweb/projects/stt/
http://knoesis.wright.edu/research/semsci/application_domain/sem_sensor/
IN34A-05
Report of the Cyberinfrastructure for Environment Observationa, Analysis and Forecasting workshop: toward collaborative VEOs
In May 2008, NCAR hosted a workshop to assist the US National Science Foundation in considering how it
might most effectively craft programs to support the creation and use of new cyberinfrastructure capabilities
to support environmental research and education over the next decade. The workshop continued a
succession of discussions that were identifying key issues and the means of addressing them. Although the
aim was not to build a consensus for a fully defined proposal or plan, the workshop did identify opportunities
through stimulating a constructive dialogue among environmental scientists, information scientists, educators,
and technologists from multiple disciplinary and environmental communities. The product of the workshop is
a white paper that examines opportunities for applying cyberinfrastructure in environmental research and
education, identifies significant issues, and provides a roadmap for addressing key questions. In this
presentation we will present this report and indicate key outcomes and future directions.
http://www.cyberobservatories.net
IN34A-06
Environmental Monitoring Using Sensor Networks
Environmental observatories, consisting of a variety of sensor systems, computational resources and
informatics, are important for us to observe, model, predict, and ultimately help preserve the health of the
nature. The commoditization and proliferation of coin-to-palm sized wireless sensors will allow environmental
monitoring with unprecedented fine spatial and temporal resolution. Once scattered around, these sensors
can identify themselves, locate their positions, describe their functions, and self-organize into a network.
They communicate through wireless channel with nearby sensors and transmit data through multi-hop
protocols to a gateway, which can forward information to a remote data server.
In this project, we describe an environmental observatory called Texas Environmental Observatory (TEO)
that incorporates a sensor network system with intertwined wired and wireless sensors. We are enhancing
and expanding the existing wired weather stations to include wireless sensor networks (WSNs) and telemetry
using solar-powered cellular modems. The new WSNs will monitor soil moisture and support long-term
hydrologic modeling. Hydrologic models are helpful in predicting how changes in land cover translate into
changes in the stream flow regime. These models require inputs that are difficult to measure over large
areas, especially variables related to storm events, such as soil moisture antecedent conditions and rainfall
amount and intensity. This will also contribute to improve rainfall estimations from meteorological radar data
and enhance hydrological forecasts.
Sensor data are transmitted from monitoring site to a Central Data Collection (CDC) Server. We incorporate
a GPRS modem for wireless telemetry, a single-board computer (SBC) as Remote Field Gateway (RFG)
Server, and a WSN for distributed soil moisture monitoring. The RFG provides effective control,
management, and coordination of two independent sensor systems, i.e., a traditional datalogger-based wired
sensor system and the WSN-based wireless sensor system. The RFG also supports remote manipulation of
the devices in the field such as the SBC, datalogger, and WSN.
Sensor data collected from the distributed monitoring stations are stored in a database (DB) Server. The
CDC Server acts as an intermediate component to hide the heterogeneity of different devices and support
data validation required by the DB Server.
Daemon programs running on the CDC Server pre-process the data before it is inserted into the database,
and periodically perform synchronization tasks. A SWE-compliant data repository is installed to enable data
exchange, accepting data from both internal DB Server and external sources through the OGC web services.
The web portal, i.e. TEO Online, serves as a user-friendly interface for data visualization, analysis, synthesis,
modeling, and K-12 educational outreach activities. It also provides useful capabilities for system developers
and operators to remotely monitor system status and remotely update software and system configuration,
which greatly simplifies the system debugging and maintenance tasks. We also implement Sensor
Observation Services (SOS) at this layer, conforming to the SWE standard to facilitate data exchange. The
standard SensorML/O&M data representation makes it easy to integrate our sensor data into the existing
Geographic Information Systems (GIS) web services and exchange the data with other organizations.
http://www.teo.unt.edu
IN34A-07
Development Of An Open System For Integration Of Heterogeneous Models For Flood Forecasting And Hazard Mitigation
During a typhoon or a heavy storm event, using various forecasting models to predict rainfall intensity, and water level variation in rivers and flood situation in the urban area is able to reveal its capability technically. However, in practice, the following two causes tend to restrain the further application of these models as a decision support system (DSS) for the hazard mitigation. The first one is due to the difficulty of integration of heterogeneous models. One has to take into consideration the different using format of models, such as input files, output files, computational requirements, and so on. The second one is that the development of DSS requires, due to the heterogeneity of models and systems, a friendly user interface or platform to hide the complexity of various tools from users. It is expected that users can be governmental officials rather than professional experts, therefore the complicated interface of DSS is not acceptable. Based on the above considerations, in the present study, we develop an open system for integration of several simulation models for flood forecasting by adopting the FEWS (Flood Early Warning System) platform developed by WL | Delft Hydraulics. It allows us to link heterogeneous models effectively and provides suitable display modules. In addition, FEWS also has been adopted by Water Resource Agency (WRA), Taiwan as the standard operational system for river flooding management. That means this work can be much easily integrated with the use of practical cases. In the present study, based on FEWS platform, the basin rainfall-runoff model, SOBEK channel-routing model, and estuary tide forecasting model are linked and integrated through the physical connection of model initial and boundary definitions. The work flow of the integrated processes of models is shown in Fig. 1. This differs from the typical single model linking used in FEWS, which only aims at data exchange but without much physical consideration. So it really makes the tighter collaboration work among these hydrological models. In addition, in order to make communication between system users and decision makers efficient and effective, a real-time and multi-user communication platform, designated as Co-life, is incorporated in the present study. Through its application sharing function, the flood forecasting results can be displayed for all attendees situated at different locations to help the processes of decision making for hazard mitigation. Fig. 2 shows the cyber-conference of WRA officials with the Co-life system for hazard mitigation during the typhoon event.
IN34A-08
Open-Source Semantic and Schematic Mediation in Hydrogeologic Spatial Data Infrastructures
A common task in cyber-based data environments, hydrogeologic or otherwise, is an initial search for data amongst distributed heterogeneous sources, followed by amalgamation of the multiple results into a single file organized using a common structure and perhaps standard content. For example, querying water well databases to obtain a list of the rock materials that occur beyond a certain ground depth, represented in some specific XML dialect. This task is often achieved with the aid of open geospatial technologies (OGC), which conveniently enable interoperability at the system and syntax levels by providing standard web service interfaces (WMS, WFS, WCS) and a standard data transfer language (GML). However, at present such technologies, which are mainly non-open source, provide minimal support for interoperating at the schematic and semantic levels, meaning it is difficult to query the data sources and obtain results in a common data structure populated with standard content. Classical data integration systems provide mediator and wrapper middleware to address this issue: mediators dispatch queries to distributed data repositories and integrate query results, while wrappers perform translation to common standards for both queries and results, and these actions are typically supported by ontologies. Under this classical scenario existing open geospatial services can be considered wrappers with minimal translation capacity, thus requiring a mediator to both integrate and translate. Consequently, we have used open source components to develop a re-usable mediator that operates as a virtual open geospatial web service (WFS), one that integrates and translates both query requests and results from OGC-wrapped data sources to common standards. The mediator is designed as a customizable XML processing pipeline that operates on declarative descriptions that support schematic and semantic translation. It is being implemented in virtual environments for hydrogeology to enhance knowledge of Canada's watersheds, as well as in environments aimed at the delivery of geologic information. Discussed will be the role and design of the mediator and its implementation in a distributed groundwater information context.