DAME: A Distributed Data Mining & Exploration Framework within the Virtual Observatory
M. Brescia, S. Cavuoti, R. D'Abrusco, O. Laurino, G. Longo

TL;DR
DAME is a web-based, distributed data mining framework designed to handle massive, distributed datasets across disciplines, enabling customizable workflows and interoperability for scientific data analysis.
Contribution
It introduces a multi-disciplinary, platform-independent data mining platform tailored for massive datasets, with a focus on interoperability and workflow customization.
Findings
Effective in astrophysical data analysis
Supports complex, customizable workflows
Demonstrated versatility across scientific domains
Abstract
Nowadays, many scientific areas share the same broad requirements of being able to deal with massive and distributed datasets while, when possible, being integrated with services and applications. In order to solve the growing gap between the incremental generation of data and our understanding of it, it is required to know how to access, retrieve, analyze, mine and integrate data from disparate sources. One of the fundamental aspects of any new generation of data mining software tool or package which really wants to become a service for the community is the possibility to use it within complex workflows which each user can fine tune in order to match the specific demands of his scientific goal. These workflows need often to access different resources (data, providers, computing facilities and packages) and require a strict interoperability on (at least) the client side. The project…
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Taxonomy
TopicsAdvanced Computational Techniques and Applications · Scientific Computing and Data Management · Distributed and Parallel Computing Systems
