Virtual Observatory (VO) is a collection of interoperating data archives and software tools. Taking advantages of the latest information technologies, it aims to provide a data-intensively online research environment for astronomers all around the world. A large number of high-qualified astronomical software packages and libraries are powerful and easy of use, and have been widely used by astronomers for many years. Integrating those toolkits into the VO system is a necessary and important task for the VO developers.
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Sensors are everywhere, which includes space, air and ground. Earth phenomena such as disasters also occur everywhere; such as wildfires, floods and volcanoes. There is a need to rapidly deploy existing sensors to aid emergency workers and investigators. The vision for our effort is to provide users the capability to create “mash ups” (a web application that combines data from more than one source into an integrated experience), similar to that used by Google Earth users to create a composite map with overlays of sensor information and from other data sources such as weather, traffic, urban construction etc. We make use of Web 2.0 technology and Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) web service standards to enable access to Earth’s sensors is an emerging mega-trend which will lower the cost of producing customized science by an order of magnitude. This paper will outline the key aspects of our experiments to date and implications for the future and in particular the Global Earth Observation System of Systems (GEOSS) international effort.
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Modern Geographical Information Systems (GIS) [1] provide a service-oriented architecture for interacting with geographical data sets and related maps. Web-based GIS systems are architected around the same principles as more general Web service systems based on SOAP [2], WSDL [3], and REST. Mirroring the World Wide Web Consortium and OASIS Web service standards-making bodies, the Open Geospatial Consortium [5] defines open standards for messages, XML data formats, and access protocols that are specific to the GIS community. In addition to OGC-based services, there are many companies (such as ESRI and AutoDesk) that provide proprietary, commercial solutions. Services from these various providers are not normally interoperable.
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The peculiar nature of services requires a multidisciplinary approach to investigate on their impact in the economic growth, to define models, to identify terminology, to describe scenarios and user profiles. The integration of several disciplines is a key point for the improvement of the Service Science capacity to find solutions and answers for services, especially for studying and designing new ICT services, the fastest growing segment within the service sector.
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Imagine an Internet-scale Knowledge System where people and intelligent agents can collaborate on solving complex problems in business, engineering, science, medicine, and other endeavors. Its resources include semantically tagged Web sites, wikis, and blogs, as well as social networks, vertical search engines and a vast array of Web services from business processes to AI planners and domain models. Research prototypes of decentralized knowledge systems have been demonstrated for years, but now, thanks to the Web and Moore’s Law, they appear ready for prime time. Architectural concepts for incrementally growing an Internet-scale knowledge system are introduced, with descriptions of early commercial deployments in manufacturing and healthcare.
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Data visualisation has been defined as: The set of techniques used to turn a set of data into visual insight. It aims to give the data a meaningful representation by exploiting the powerful discerning capabilities of the human eye. Part 1 of this briefing paper will highlight some examples of new collaborative web services using Web 2.0 technologies which venture into the numeric data visualisation arena. These mashups allow researchers to upload and analyse their own data in ‘open’ and dynamic environments. Broadly speaking the numeric data being referred to could be micro-data (data about the individual), macro-data or country-level data, derived or summary data.
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Cyberinfrastructure 1 and e-Science 1 are conventionally presented in terms of Grid technologies 2 3 that support remote access to computational science resources (such as supercomputers), distributed data management, networked instruments and similar technologies. Web Services are a key technology for realizing this vision 4 5. In contrast to these heavyweight approaches, however, many important innovations in network programming are emerging outside the (by now) traditional Web Services framework and are collectively known as Web 2.0 6. As we discuss in this chapter, these developments need to be tracked and incorporated into the e-Science vision.
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Guide to Eos and Unity Computing, 2007-08 Edition for UNIX, Windows, and Linux is the principal user manual for the distributed academic computing environment at North Carolina State University. Formerly a College of Engineering system only, Eos was made available to other NCSU colleges in 1996 in a project called Unity. Today, all NCSU students, faculty, and staff receive accounts on a fully merged campus-wide system, or realm, often referred to as Eos/Unity.
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