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تسجيل مستخدم جديدTHE CAVES Project - Collaborative Analysis Versioning Environment System; THE CODESH Project - Collaborative Development Shell
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Dimitri Bourilkov
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A key feature of collaboration in science and software development is to have a {em log} of what and how is being done - for private use and reuse and for sharing selected parts with collaborators, which most often today are distributed geographically on an ever larger scale. Even better if this log is {em automatic}, created on the fly while a scientist or software developer is working in a habitual way, without the need for extra efforts. The {tt CAVES} and {tt CODESH} projects address this problem in a novel way, building on the concepts of {em virtual state} and {em virtual transition} to provide an automatic persistent logbook for sessions of data analysis or software development in a collaborating group. A repository of sessions can be configured dynamically to record and make available the knowledge accumulated in the course of a scientific or software endeavor. Access can be controlled to define logbooks of private sessions and sessions shared within or between collaborating groups.
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The Collaborative Analysis Versioning Environment System (CAVES) project concentrates on the interactions between users performing data and/or computing intensive analyses on large data sets, as encountered in many contemporary scientific disciplines
. In modern science increasingly larger groups of researchers collaborate on a given topic over extended periods of time. The logging and sharing of knowledge about how analyses are performed or how results are obtained is important throughout the lifetime of a project. Here is where virtual data concepts play a major role. The ability to seamlessly log, exchange and reproduce results and the methods, algorithms and computer programs used in obtaining them enhances in a qualitative way the level of collaboration in a group or between groups in larger organizations. The CAVES project takes a pragmatic approach in assessing the needs of a community of scientists by building series of prototypes with increasing sophistication. In extending the functionality of existing data analysis packages with virtual data capabilities these prototypes provide an easy and habitual entry point for researchers to explore virtual data concepts in real life applications and to provide valuable feedback for refining the system design. The architecture is modular based on Web, Grid and other services which can be plugged in as desired. As a proof of principle we build a first system by extending the very popular data analysis framework ROOT, widely used in high energy physics and other fields, making it virtual data enabled.
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