app/views/climate/aboutProject.scala.html

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@(message: String)

@main("About Project") {

   <h1>About Project</h1>
   <div class="jumbotron">
   <p>This project aims to develop an online collaborative working environment, where scientists can not only efficiently perform their 
   climate data analyses but also effectively share their analysis tools, datasets, and results with others. This project is based on a tight collaboration between Jet Propulsion 
   Laboratory (JPL) and Carnegie Mellon University (CMU).</p>
   <p>JPL has developed a technology that wraps existing climate data analysis tools into web services, with programmable interfaces that are universally accessible from the Internet. 
   Based on the technology, JPL has developed a collection of web services that enable multi-aspect physics-based and phenomenon-oriented climate model performance evaluation and 
   diagnosis through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. The system is called Climate Model Diagnostic Analyzer (CMDA).</p>
   <p>CMU has developed a technology to model software usage behaviors into social networks, and based on semantics-oriented analytics to assist Earth scientists in designing data 
   analysis procedures. Using the technology, CMU has developed a semantic model for CMDA services in order to capture various hidden relationships, including semantic relationships 
   and usage relationships in CMDA services, to help users not only learn available datasets and web services, but also learn how to use them and design climate analytics workflows 
   faster than before. CMU has also developed a provenance model to record and track scientists’ activities and behaviors using CMDA services.</p>
   <p>One of the key outcomes of this project will be a repository of climate data analytics web services, equipped with mechanisms to organize and manage these climate analytics 
   services and help share and reuse the services properly. Our vision is that the climate data analytics web services can be shared, organized, searched, and recommended like photos 
   and videos on YouTube and Shutterfly. We intend to build the web service repository with a full understanding of the needs of the Earth science researchers, and make it easy for the 
   next-generation Earth scientists to contribute to a pool of data analytics tools, build communities, and form collaborative relationships.</p>
</div>
}