We make science discovery happen
Statistical Challenges in 21st Century Cosmology
Centro Cultural de Belem, Lisboa, Portugal
Astronomical Telescopes and Instrumentation, Edinburgh, GB
ESO, Garching bei München, Germany
European Week of Astronomy and Space Science, Athens, Greece
Conference Center of the University Federico II, Naples, Italy
Angelicum Congress Center, Rome, Italy
Sorrento, Naples, Italy
Nowadays, many scientific areas share the same need of being able to deal with massive and distributed datasets and to perform complex knowledge extraction tasks. DAME (DAta Mining & Exploration) is a general purpose, web-based, distributed data mining infrastructure specialized in Massive Data Sets exploration with machine learning methods.
Initially fine tuned to deal with astronomical data only, DAME has evolved in a general purpose platform program, hosting a cloud of applications and services useful also in other domains of human endeavor.
DAME is an evolving platform and new services as well as additional features are continuously added. The modular architecture of DAME can also be exploited to build applications, finely tuned to specific needs.
The goal of DAME is to offer and develop open and broadly available software tools and services for scientific purposes. Groups or individuals interested in collaborating or participating in scientific and/or technological projects/activities are welcomed and encouraged to contact us. Please, consult policy and citation document.
DAME partners acknowledge the financial support of the Italian Ministry of Foreign Affairs for the Italy-USA bi-lateral grant Building an e-science Data Mining Infrastructure, the European Union through the projects VO-Tech and VO-AIDA, the Ministry of University and Research through the PON S.Co.P.E. GRID project, the INAF for the partial support through the PRIN 2010 Tomography of Galaxy Clusters and the PRIN 2014 Glittering Kaleidoscopes in the sky, the multifaceted nature and role of galaxy clusters, the European and Italian Space Agencies for the support in the participation to the ESA EUCLID space mission program and the European Commission for the support through the Program FP7-SPACE-2013-1 ViaLactea. We acknowledge the support of the EU COST Action TD1403 Big Data Era in Sky and Earth Observation. We also acknowledge a crucial support from the Fishbein Family Foundation, and a partial support from the NASA grant 08-AISR08-0085.