We present an architecture for global customization of web content, by w h i c h a w eb site can customize content for each visitor based on the activities undertaken by the same user on other, unrelated sites. Our architecture distinguishes itself in the privacy mechanisms it provides: each u s e r c o n trols what information a merchant can learn about her activities at other merchants, and each merchant controls to what other merchants the information it contributes is revealed. To a c hieve t h i s w e i n troduce novel data protection mechanisms for merchants and users. We further describe aspects of a prototype implementation of our architecture.
In order to help scientists in the above ground biomass community and to support the science behind the upcoming BIOMASS, NISAR, and GEDI satellite missions, ESA and NASA are collaborating on the Multi-Mission Algorithm and Analysis Platform (MAAP). The MAAP is a jointly developed and implemented platform that will include not only data (satellite, airborne, in situ data, and products), but also computing capabilities and sets of tools and algorithms developed to support this specific field of research. To best ensure that users are able to collaborate across the platform and to access needed resources, the MAAP requires all data, algorithms, and software to conform to open access and open source policies. In addition to aiding researchers, the MAAP exercise is establishing a collaboration framework between ESA and NASA that focuses on sharing data, science algorithms, and computable resources in order to foster and accelerate scientific research.
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