Davide Salomoni is Director of Technology (Dirigente Tecnologo) at the Italian National Institute for Nuclear Physics (INFN). He has more than 25 years of international experience in both private and public environments related to distributed computing and communication technologies.
He currently leads the Software Development and Distributed Systems department at CNAF (Bologna, Italy), the INFN National Center dedicated to research and development on IT technologies. His interests are focused on the evolution, scalability and interoperability of Cloud computing and storage technologies.
He is the Project Coordinator of the European project called INDIGO-DataCloud, funded with 11.1M€ under the Horizon2020 framework. INDIGO-DataCloud (http://www.indigo-datacloud.eu), a project 26 academic and commercial partners, builds an open source Cloud computing and data platform targeted at multi-disciplinary scientific communities and deployable on heterogeneous infrastructures. Davide also leads or participates to several other national and international projects on distributed architectures. He is the coordinator of the INFN Cloud Computing national working group and is engaged with activities related to technology transfer in Universities, Public Administrations and commercial companies through seminars, courses and lectures.
When: Day 2 - 15th November, Chair of Session 7: Research Data Management in practice #Part 2, 09:35 - 10:30,
Session 10: The Italian Way to Data Management Plan, 14:00 - 16:00,
Efficient and effective: can we combine both to realize high-value, open, scalable, multi-disciplinary data and compute infrastructures?
Abstract. Distributed data and compute resources are more and more ubiquitously available, they are relatively cheap to acquire, they are often connected at unprecedented speed, and still it is often complicated to exploit and interconnect them. This leads to substantial opportunities that are being lost, to unnecessary costs, and to a waste of manpower and resources. Challenges in preparing and implementing Data Management Plans can serve as an example to understand what is still missing, in order to solve problems that mandate the adoption of solutions that must be at the same time both *efficient* and *effective*. In this talk, I will elaborate on some of the issues that scientific communities dealing with large amounts of data are facing, drawing from the experience gained with experiments and projects involving the Italian National Institute for Nuclear Physics (INFN).