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  1. Register for the Webcast at: http://www.prismtech.com/events/art-and-science-dds-data-modeling-webcast Why Attend: * Understand the role and scope of Data Modeling in DDS * Learn the key techniques for effective and extensible Data Models Design * Learn about the most common DDS Data Modeling Idioms Abstract The Data Distribution Service (DDS) is a standard for ubiquitous, interoperable, secure, platform independent, and real-time data sharing across network connected devices. DDS is today used and recommended in a large class of application domains, such as Industrial Internet of Things (IIoT), Defense and Aerospace, Transportation, Robotics, Energy, and Medical. Differently from traditional message-centric technologies, DDS is data-centric – the accent is on seamless (user-defined) data sharing as opposed to message delivery. Therefore, when embracing DDS and data-centricity, data modeling becomes a key step in the design of a distributed system. This webcast will (1) explain the role and scope of data modeling in DDS, (2) introduce the techniques at the foundation of effective and extensible Data Models, and (3) summarize the most common DDS Data Modeling Idioms. Webcast Presenter: Angelo Corsaro, Ph.D. is Chief Technology Officer (CTO) at ADLINK Technology Inc. As CTO he looks after technology strategy and innovation for ADLINK’s Industrial Internet of Things (IIoT) Platform. Angelo also serves as PrismTech (an ADLINK company) CTO, where he looks after technology strategy and innovation for PrismTech's Vortex IIoT data sharing platform. Angelo leads the strategic standardization at the Object Management Group (OMG), where he co-chairs the Data Distribution Service (DDS) Special Interest Group. Before joining PrismTech, Angelo was working as a Scientist at the SELEX-SI and FINMECCANICA Technology Directorate. There, he was responsible for the corporate middleware strategy, for strategic standardization, and R&D collaborations with top Universities. Angelo is a well-known and cited expert in the area of high performance and large scale distributed systems with 100s of publications for referred journal, conferences, workshops, and magazines. Angelo received a Ph.D. and a M.S. in Computer Science from the Washington University in St. Louis, and a Laurea Magna cum Laude in Computer Engineering from the University of Catania, Italy.
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