UBITECH has actively participated in the kick-off meeting, in Athens, Greece (January 10-11, 2017) of the BigDataOcean Innovation Action, officially started on January 1st, 2017. The project is funded by European Commission under Horizon 2020 Programme (Grant Agreement No. 732310) and spans on the period January 2017 – June 2019. The BigDataOcean project that enables maritime big data scenarios for EU-based companies, organisations and scientists, through a multi-segment platform that will combine data of different velocity, variety and volume under an inter-linked, trusted, multilingual engine to produce a big-data repository of value and veracity back to the participants and local communities, bringing together the data, the network and the technologies to create a curated, semantically enhanced, interlinked and multilingual repository for maritime big data, where different stakeholders will be able to contribute with data in order to support their own goals and operations, but also allow new stakeholders (e.g. entrepreneurs, local communities, local authorities) will be able to develop new solutions in order to enable new, socially and environmentally sustainable business models or solutions.
Within BigDataOcean, UBITECH undertakes the technical integration lead of the project’s R&D activities, while UBITECH R&D team heavily contributes and leads the technological choices towards the definition and design of the integrated maritime data value chain, wherein all individual maritime-related stakeholders will be identified and brought together, bringing forward the value that one can add to each other, under a seamless collaboration and mutually beneficiary prism, adding stakeholders that priory seemed disconnected/irrelevant in order to realize a holistic big data-centred value chain. Moreover, UBITECH delivers the scalable architecture of the BigDataOcean framework enabling the integrated maritime data value chain, as well as the BigDataOcean libraries and algorithms for knowledge extraction, business intelligence and usage analytics, including (indicatively) clustering, segmentation, classification (e.g. linear regression, association rules and decision trees) in order to receive statistical data; constituting an extensible big (linked) data analytics apps library that will enable various types of maritime stakeholders to utilise and share analytic methods on big data for the discovery and communication of meaningful knowledge and new patterns that were unattainable or hidden in the previous isolated data structures; and targeting maritime-related stakeholders that usually do not tend blending their data, in order to setup business intelligence systems through the use of cross-sectorial and multi-lingual big data and gain significant competitive advantage.
Source: http://www.bigdataocean.eu/site/2016/12/30/big-data-ocean-kickoff-meeting/
