Ben Domenico

Service-Oriented Environments for Dynamically Interacting with Mesoscale Weather

Within a decade after John von Neumann and colleagues conducted the first experimental weather forecast on the ENIAC computer in the late 1940s, numerical models of the atmosphere become the foundation of modern-day weather forecasting and one of the driving application areas in computer science. This article describes research that is enabling a major shift toward dynamically adaptive responses to rapidly changing environmental conditions.

PROJECT CRAFT A Real-Time Delivery System for Nexrad Level II Data Via The Internet

Abstract The NOAA NWS announced at the annual meeting of the American Meteorological Society in February 2003 its intent to create an Internet-based pseudo-operational system for delivering Weather Surveillance Radar-1988 Doppler (WSR-88D) Level II data. In April 2004, the NWS deployed the Next-Generation Weather Radar (NEXRAD) level II central collection functionality and set up a framework for distributing these data. The NWS action was the direct result of a successful joint government, university, and private sector development and test effort called the Collaborative Radar Acquisition Field Test (CRAFT) project. Project CRAFT was a multi-institutional effort among the Center for Analysis and Prediction of Storms, the University Corporation for Atmospheric Research, the University of Washington, and the three NOAA organizations, National Severe Storms Laboratory, WSR-88D Radar Operations Center (ROC), and National Climatic Data Center. The principal goal of CRAFT was to demonstrate the real-time compr...

Unidata’s Common Data Model mapping to the ISO 19123 Data Model

Access to real-time distributed Earth and Space Science (ESS) information is essential for enabling critical Decision Support Systems (DSS). Thus, data model interoperability between the ESS and DSS communities is a decisive achievement for enabling cyber-infrastructure which aims to serve important societal benefit areas. The ESS community is characterized by a certain heterogeneity, as far as data models are concerned. Recent spatial data infrastructures implement international standards for the data model in order to achieve interoperability and extensibility. This paper presents well-accepted ESS data models, introducing a unified data model called the Common Data Model (CDM). CDM mapping into the corresponding elements of the international standard coverage data model of ISO 19123 is presented and discussed at the abstract level. The mapping of CDM scientific data types to the ISO coverage model is a first step toward interoperability of data systems. This mapping will provide the abstract framework that can be used to unify subsequent efforts to define appropriate conventions along with explicit agreed-upon encoding forms for each data type. As a valuable case in point, the content mapping rules for CDM grid data are discussed addressing a significant example.

Making Earth Science Data Accessible and Usable in Education

The Earth Exploration Toolbook provides instructions on accessing and analyzing Earth science data to explore scientific concepts and issues. To enable responsible decision-making in the future and to ensure the development of the next generation of scientists, students must develop the skills that enable them to explore scientific questions, assess the results of scientific research, and draw and communicate conclusions to others. These skills are essential as society faces science and engineering challenges, including the need to understand and respond to the impacts of changes in Earths climate.

GALEON: Standards-based Web Services for Interoperability among Earth Sciences Data Systems

One barrier to research at the boundaries of the traditional Earth sciences is a lack of interoperability among data systems employed in the traditional subdisciplines. Solid Earth scientists (including the hydrology community) have tended to view their datasets as descriptions of discrete objects with attributes that can be stored and manipulated conveniently in a database. Geographic Information Systems (GIS) work well in this environment. On the other hand, the oceanographic and atmospheric sciences (the Fluid Earth Sciences or FES) communities think of data as discrete points in a continuous mathematical function space where the behavior of multiple parameters in space and time is governed by a set of equations.

Enabling interoperability for Digital Earth: Earth Science coverage access services

Abstract For Digital Earth, an important priority is to integrate data from multiple sources. Interoperability and metadata are key instruments to reach such an objective. Interoperability is achieved by adopting and applying international standards for service interfaces and data models. As far as geospatial information is concerned, interoperability recognizes three important, interrelated data concepts: feature, coverage, and map. The present work deals with Web services for coverage access. Coverage perspectives characterizing three geospatial communities - i.e. the Earth Science (ES), GIS and Digital Earth communities, are discussed. ES community requirements for coverage access services are presented and discussed making use of two methods concurrently: Critical Success Factor (CSF) analysis method supplemented through the use of Usage Cases. A CSF hierarchy and derived critical requirements and problems are introduced. An implementation approach consisting of four general principles is proposed. Access service categories emerging from the analysis are presented and their comparison with the present access services for the ES is discussed.

Geoscience Data for Educational Use: Recommendations from Scientific/Technical and Educational Communities

ABSTRACT Access to geoscience data has been difficult for many educators. Understanding what educators want in terms of data has been equally difficult for scientists. From 2004 to 2009, we conducted annual workshops that brought together scientists, data providers, data analysis tool specialists, educators, and curriculum developers to better understand data use, access, and user-community needs. All users desired more access to data that provide an opportunity to conduct queries, as well as visual/graphical displays on geoscience data without the barriers presented by specialized data formats or software knowledge. Presented here is a framework for examining data access from a workflow perspective, a redefinition of data not as products but as learning opportunities, and finally, results from a Data Use Survey collected during six workshops that indicate a preference for easy-to-obtain data that allow users to graph, map, and recognize patterns using educationally familiar tools (e.g., Excel and Google Earth).

Interoperability Middleware between Geoscience and Geospatial Catalog Protocols

OGC protocols have been widely accepted by the geospatial/land science communities, We call this community geospatial community. Others communities such as atmosphere, ocean, and modeling science adopt the other set of data access protocols. We name these protocols as geoscience protocols. Although these two protocols have been used wildly, but unfortunately, there is no interoperability between them. For bridging this cross-protocol and cross-community gap, CSISS have developed a catalog middleware to mediate client/server interactions between OGC catalog clients and THREDDS servers. A prototype system has been implemented to demonstrate the concept and approach.

Atmospheric data access for the geospatial user community

Historically the atmospheric and meteorological communities are separate worlds with their own data formats and tools for data handling making sharing of data difficult and cumbersome. On the other hand, these information sources are becoming increasingly of interest outside these communities because of the continuously improving spatial and temporal resolution of e.g. model and satellite data and the interest in historical datasets. New user communities that use geographically based datasets in a cross-domain manner are emerging. This development is supported by the progress made in Geographical Information System (GIS) software. The current GIS software is not yet ready for the wealth of atmospheric data, although the faint outlines of new generation software are already visible: support of HDF, NetCDF and an increasing understanding of temporal issues are only a few of the hints.

NcML-G/sub ML/: encoding NetCDF datasets using GML

We describe the NcML-G/sub ML/: an extension of the NetCDF markup language (NcML). Such extension allows to encode NetCDF dataset resorting to GML 3.0 elements. It was conceived to facilitate the interoperability between the atmospheric science and the GIS communities; NcML-G/sub ML/ leverages the NcML effectiveness for encoding multidimensional arrays, encoding geo-metadata in GML. The abstract and the general content model which lead to the NcML-G/sub ML/are described.