The Experts below are selected from a list of 595965 Experts worldwide ranked by ideXlab platform
Michael Coleman - One of the best experts on this subject based on the ideXlab platform.
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multi disease Data Management System platform for vector borne diseases
PLOS Neglected Tropical Diseases, 2011Co-Authors: Lars Eisen, Marlize Coleman, Saul Lozanofuentes, Nathan Mceachen, Miguel Orlans, Michael ColemanAbstract:Background Emerging information technologies present new opportunities to reduce the burden of malaria, dengue and other infectious diseases. For example, use of a Data Management System software package can help disease control programs to better manage and analyze their Data, and thus enhances their ability to carry out continuous surveillance, monitor interventions and evaluate control program performance. Methods and Findings We describe a novel multi-disease Data Management System platform (hereinafter referred to as the System) with current capacity for dengue and malaria that supports Data entry, storage and query. It also allows for production of maps and both standardized and customized reports. The System is comprised exclusively of software components that can be distributed without the user incurring licensing costs. It was designed to maximize the ability of the user to adapt the System to local conditions without involvement of software developers. Key points of System adaptability include 1) customizable functionality content by disease, 2) configurable roles and permissions, 3) customizable user interfaces and display labels and 4) configurable information trees including a geographical entity tree and a term tree. The System includes significant portions of functionality that is entirely or in large part re-used across diseases, which provides an economy of scope as new diseases downstream are added to the System at decreased cost. Conclusions We have developed a System with great potential for aiding disease control programs in their task to reduce the burden of dengue and malaria, including the implementation of integrated vector Management programs. Next steps include evaluations of operational implementations of the current System with capacity for dengue and malaria, and the inclusion in the System platform of other important vector-borne diseases.
Lars Eisen - One of the best experts on this subject based on the ideXlab platform.
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multi disease Data Management System platform for vector borne diseases
PLOS Neglected Tropical Diseases, 2011Co-Authors: Lars Eisen, Marlize Coleman, Saul Lozanofuentes, Nathan Mceachen, Miguel Orlans, Michael ColemanAbstract:Background Emerging information technologies present new opportunities to reduce the burden of malaria, dengue and other infectious diseases. For example, use of a Data Management System software package can help disease control programs to better manage and analyze their Data, and thus enhances their ability to carry out continuous surveillance, monitor interventions and evaluate control program performance. Methods and Findings We describe a novel multi-disease Data Management System platform (hereinafter referred to as the System) with current capacity for dengue and malaria that supports Data entry, storage and query. It also allows for production of maps and both standardized and customized reports. The System is comprised exclusively of software components that can be distributed without the user incurring licensing costs. It was designed to maximize the ability of the user to adapt the System to local conditions without involvement of software developers. Key points of System adaptability include 1) customizable functionality content by disease, 2) configurable roles and permissions, 3) customizable user interfaces and display labels and 4) configurable information trees including a geographical entity tree and a term tree. The System includes significant portions of functionality that is entirely or in large part re-used across diseases, which provides an economy of scope as new diseases downstream are added to the System at decreased cost. Conclusions We have developed a System with great potential for aiding disease control programs in their task to reduce the burden of dengue and malaria, including the implementation of integrated vector Management programs. Next steps include evaluations of operational implementations of the current System with capacity for dengue and malaria, and the inclusion in the System platform of other important vector-borne diseases.
/illinois U., Urbana, Astron. Dept. /illinois U. Urbana - One of the best experts on this subject based on the ideXlab platform.
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The Dark Energy Survey Data Management System
Fermi National Accelerator Laboratory, 2008Co-Authors: Mohr, Joseph J., /illinois U., Urbana, Astron. Dept. /illinois U. Urbana, Barkhouse Wayne, U., /north Dakota, Beldica Cristina, Bertin Emmanuel, /paris, Inst. Astrophys., Dora Cai Y.Abstract:The Dark Energy Survey (DES) collaboration will study cosmic acceleration with a 5000 deg2 griZY survey in the southern sky over 525 nights from 2011-2016. The DES Data Management (DESDM) System will be used to process and archive these Data and the resulting science ready Data products. The DESDM System consists of an integrated archive, a processing framework, an ensemble of astronomy codes and a Data access framework. We are developing the DESDM System for operation in the high performance computing (HPC) environments at the National Center for Supercomputing Applications (NCSA) and Fermilab. Operating the DESDM System in an HPC environment offers both speed and flexibility. We will employ it for our regular nightly processing needs, and for more compute-intensive tasks such as large scale image coaddition campaigns, extraction of weak lensing shear from the full survey Dataset, and massive seasonal reprocessing of the DES Data. Data products will be available to the Collaboration and later to the public through a virtual-observatory compatible web portal. Our approach leverages investments in publicly available HPC Systems, greatly reducing hardware and maintenance costs to the project, which must deploy and maintain only the storage, Database platforms and orchestration and web portal nodes that are specific to DESDM. In Fall 2007, we tested the current DESDM System on both simulated and real survey Data. We used TeraGrid to process 10 simulated DES nights (3TB of raw Data), ingesting and calibrating approximately 250 million objects into the DES Archive Database. We also used DESDM to process and calibrate over 50 nights of survey Data acquired with the Mosaic2 camera. Comparison to truth tables in the case of the simulated Data and internal crosschecks in the case of the real Data indicate that astrometric and photometric Data quality is excellent
Nathan Mceachen - One of the best experts on this subject based on the ideXlab platform.
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multi disease Data Management System platform for vector borne diseases
PLOS Neglected Tropical Diseases, 2011Co-Authors: Lars Eisen, Marlize Coleman, Saul Lozanofuentes, Nathan Mceachen, Miguel Orlans, Michael ColemanAbstract:Background Emerging information technologies present new opportunities to reduce the burden of malaria, dengue and other infectious diseases. For example, use of a Data Management System software package can help disease control programs to better manage and analyze their Data, and thus enhances their ability to carry out continuous surveillance, monitor interventions and evaluate control program performance. Methods and Findings We describe a novel multi-disease Data Management System platform (hereinafter referred to as the System) with current capacity for dengue and malaria that supports Data entry, storage and query. It also allows for production of maps and both standardized and customized reports. The System is comprised exclusively of software components that can be distributed without the user incurring licensing costs. It was designed to maximize the ability of the user to adapt the System to local conditions without involvement of software developers. Key points of System adaptability include 1) customizable functionality content by disease, 2) configurable roles and permissions, 3) customizable user interfaces and display labels and 4) configurable information trees including a geographical entity tree and a term tree. The System includes significant portions of functionality that is entirely or in large part re-used across diseases, which provides an economy of scope as new diseases downstream are added to the System at decreased cost. Conclusions We have developed a System with great potential for aiding disease control programs in their task to reduce the burden of dengue and malaria, including the implementation of integrated vector Management programs. Next steps include evaluations of operational implementations of the current System with capacity for dengue and malaria, and the inclusion in the System platform of other important vector-borne diseases.
Saul Lozanofuentes - One of the best experts on this subject based on the ideXlab platform.
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multi disease Data Management System platform for vector borne diseases
PLOS Neglected Tropical Diseases, 2011Co-Authors: Lars Eisen, Marlize Coleman, Saul Lozanofuentes, Nathan Mceachen, Miguel Orlans, Michael ColemanAbstract:Background Emerging information technologies present new opportunities to reduce the burden of malaria, dengue and other infectious diseases. For example, use of a Data Management System software package can help disease control programs to better manage and analyze their Data, and thus enhances their ability to carry out continuous surveillance, monitor interventions and evaluate control program performance. Methods and Findings We describe a novel multi-disease Data Management System platform (hereinafter referred to as the System) with current capacity for dengue and malaria that supports Data entry, storage and query. It also allows for production of maps and both standardized and customized reports. The System is comprised exclusively of software components that can be distributed without the user incurring licensing costs. It was designed to maximize the ability of the user to adapt the System to local conditions without involvement of software developers. Key points of System adaptability include 1) customizable functionality content by disease, 2) configurable roles and permissions, 3) customizable user interfaces and display labels and 4) configurable information trees including a geographical entity tree and a term tree. The System includes significant portions of functionality that is entirely or in large part re-used across diseases, which provides an economy of scope as new diseases downstream are added to the System at decreased cost. Conclusions We have developed a System with great potential for aiding disease control programs in their task to reduce the burden of dengue and malaria, including the implementation of integrated vector Management programs. Next steps include evaluations of operational implementations of the current System with capacity for dengue and malaria, and the inclusion in the System platform of other important vector-borne diseases.
