![]() ![]() the platform's main cloud services, which are: data storage, service execution, security, workflow enactment and provenance. This paper's main contributions are to describe: In this time, over two million workflow executions have been enacted on the system. e-SC has now been in constant use for over four years, with over 300 users. To address this, we have designed e-Science Central (e-SC), a cloud-based science PaaS that allows scientists to store, analyse and share data in the cloud. The danger, therefore, is that the potential of the cloud to revolutionize e-Science will not be fully realized. Some of these functions may be useful to scientists (for instance, Google Charts), but they do not meet the full range of needs of scientists.Īs a result of these limitations, we have concluded that there will be relatively few science research groups with the skills and resources required to build scalable, secure and dependable science applications on the existing cloud offerings. Again, the problem is that the applications provided to date have focused on the large, commercial markets such as e-mail and document management. Software as a service (SaaS): makes packaged applications available to users through the Web. The drawback is that, for commercial reasons, current platforms focus on services required for business applications, rather than those needed for scientific data storage and analysis (in §2, we give our view of the platform services that are needed to support scientific applications, based on our experiences in working with a wide range of scientists over the past 10 years). For example, provides a variety of hosted services that can be used to develop customer relationship management-related applications in the cloud. Platform as a service (PaaS): provides a higher level of abstraction than IaaS, as developers are provided with a platform containing services that can be used to build applications. The drawback is that for the majority of potential scientific users, access to raw hardware is of little use as they lack the skills and resources needed to design, develop and maintain the robust, scalable applications they require. Using IaaS, developers can dynamically provision compute and storage resources, and they typically have control over the whole software stack including the operating system. ![]() Infrastructure as a service (IaaS): this is typical of many cloud offerings-for example, Amazon EC2 . The problems can be seen when the various levels of cloud computing offerings currently available are considered . ![]() On their own however, clouds do not make it easier to design, implement and maintain the scalable, secure and dependable applications needed to support scientists. This paper describes the design of e-SC, its API and its use in three different case studies: spectral data visualization, medical data capture and analysis, and chemical property prediction.Ĭloud computing has the potential to revolutionize e-Science by giving scientists the computational resources they need, when they need them. A representational state transfer-based application programming interface (API) is also provided so that external applications can leverage the platform's functionality, making it easier to build scalable, secure cloud-based applications. The platform is exposed to developers so that they can easily upload their own analysis services into the system and make these available to other users. It is underpinned by a scalable cloud platform consisting of a set of components designed to support the needs of scientists. The SaaS application allows scientists to upload data, edit and run workflows and share results in the cloud, using only a Web browser. Eucalyptus) and public clouds (Amazon AWS and Microsoft Windows Azure). It is a portable system and can be deployed on both private (e.g. e-SC provides both software as a service (SaaS) and platform as a service for scientific data management, analysis and collaboration. Var chart = new (document.This paper describes the e-Science Central (e-SC) cloud data processing system and its application to a number of e-Science projects. Var chart = new (document.getElementById('piechart_div')) Instantiate and draw our chart, passing in some options. Thanks // Load the Visualization API and the piechart package. Is there a native google API way? or can I find a way using jQuery and how? ![]() Google Viz should use the JSON to draw a bar chart How can I retrieve and use a dataset for google charts if it was a separate JSON file? I tried jQuery getJSON but couldn't get it worked. ![]()
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