Data Grids offer redundant and huge distributed storage capabilities, providing an ideal and secure place for the longterm preservation of digitized literary works and documents of artistic and historical relevance.In fact, digitization has been progressively used as a means for avoiding the loss of literary heritage on paper, caused by physical ageing and the environmental conditions in which documents are kept. Document consultation is another problem that leads to additional deterioration. Multiple copies of high resolutions scans stored in a distributed environment and made available for consultation with a easy to use interface is a means to guarantee conservation of cultural heritage. Grid authentication and authorisation mechanisms allow a finegrained access to archives by single users, groups or entire communities. Moreover, metadata services permit a structured organisation of scanned files for quick searches.Two use cases have been considered to demonstrate how grid digital libraries can guarantee enduring preservation of literary heritage: the archives of the work of Italian writer Federico De Roberto, made up of almost 8000 scans, and the musical and the musical archives of the "Civiltà Musicale Napoletana" project, made up of more than 250,000 digitizations.A working prototype of the De Roberto digital repository has been implemented on the gLibrary platform, a grid-based system to host and manage digital libraries developed by INFN Catania, on the Sicilian e-infrastructure of the COMETA consortium.
Hyperspectral imaging is a new technique in remote sensing in which an imaging spectrometer collects hundred of images (at different wavelength channels) for the same area on the surface of Earth. Over the last years, hyperspectral image data sets have been collected from a great amount of locations over the world using a variety of instruments for Earth observation. Only a small amount of them are available for public use and they are spread among different storage locations and exhibit significant heterogeneity regarding the storage format. Therefore, the development of a standardized hyperspectral data repository is a highly desired goal in the remote sensing community. In this paper, we describe the development of a shared digital repository for remotely sensed hyperspectral data, which allows uploading new hyperspectral data sets along with meta-data, ground-truth and analysis results (spectral information). Such repository is presented as a web service for providing the management of images through a web interface, and it is available online from http://www.hypercomp.es/repository. Most importantly, the developed system includes a spectral unmixing-based content based image retrieval (CBIR) functionality which allows searching for images from the database using spectrally pure components or endmembers in the scene. A full spectral unmixing chain is implemented for spectral information extraction, which allows filtering images using the similarity of the spectral signature and abundance of a given ground-truth. In order to accelerate the process of obtaining the spectral information for new entries in the system, we resort to an efficient implementations of spectral unmixing algorithms of graphics processing units (GPUs).
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