{"id":187914,"date":"2012-05-24T00:00:00","date_gmt":"2012-06-19T15:49:45","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/the-world-of-multi-mouse-e-cloudss-building-e-government-clouds-using-distributed-semantic-services\/"},"modified":"2016-09-26T08:44:39","modified_gmt":"2016-09-26T15:44:39","slug":"the-world-of-multi-mouse-e-cloudss-building-e-government-clouds-using-distributed-semantic-services","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/the-world-of-multi-mouse-e-cloudss-building-e-government-clouds-using-distributed-semantic-services\/","title":{"rendered":"The World of Multi-Mouse; E-CLOUDSS: Building e-Government Clouds Using Distributed Semantic Services"},"content":{"rendered":"
\n

The World of Multi-Mouse<\/b>
\n
\n<\/b>Computers have proved a boon to education, but cash-strapped schools struggle to provide PCs. In this presentation, we address the question of how to get the same benefits of active participation and personal feedback that a computer provides at a cost of just a dollar per child per year. The answer is an “Interpersonal Computer,” in our case, consisting of a PC, a projector, and a mouse for each child participating in the activity.<\/p>\n

In this presentation, we show how we can teach math and language by using a personal and a collaborative approach, and analyze the value of games.<\/p>\n

E-CLOUDSS: Building e-Government Clouds Using Distributed Semantic Services<\/b>
\nCloud computing is facilitating unlimited access to the computing and storage resources needed to build applications. The underlying infrastructure manages such resources transparently, without demanding the application manage or reserve more resources than those it really requires. Therefore, database management systems have exploded into cloud services that must be tuned and composed for efficiently and cost-effectively managing, querying, and exploiting huge data sets.<\/p>\n

In this talk, we address a querying approach that consists of composing services that provide data and data management functions (aggregation, storage, refreshment). We discuss how query processing is tuned with respect to the cost of accessing data and services, the cost of using cloud resources for executing the query, and the mashing up of results according to quality dimensions of completeness, data provenance, and data freshness. We also examine how this approach has provided solutions for e-government applications that integrate services from different countries.<\/p>\n<\/div>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

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