One of the main objectives of LAMBDA (Learning, Applying, Multiplying Big Data Analytics) project is to develop a series of Big Data Analysis training session and foster knowledge exchange in this area. This deliverable reports the project period from month 1 till month 18. In this period we have held commenced the first LAMBDA summer school which has provided lectures on cutting edge technologies following different learning modes e.g., webinars, lectures, hands-on sessions and demonstrations.

Funded by "Spreading Excellence and Widening Participation" Work Programme 2016-2017, the LAMBDA (Learning, Applying, Multiplying Big Data Analytics) project aims the following goals:

This document presents details of the dissemination and communication activities implemented for the reporting period (M1-M12). During this period, WP5 focused its efforts on developing and implementing the appropriate dissemination and communication strategies and activities that will result in the best and most effective promotion of the project in the local, regional areas as well as European and international level.

The LAMBDA Big Data Analytics Summer School was organized by the LAMBDA consortium partners Institute Mihajlo Pupin (PUPIN), Fraunhofer Institute for Intelligent Analysis and Information Systems (Fraunhofer/IAIS), Institute for Computer Science - University of Bonn (UBO) and Department of Computer Science - University of Oxford (UOXF). The event took place in Belgrade between June 17th and June 20th, 2019. Overall, more than 60 participants gathered at the PUPIN premises to exchange knowledge and expertise in Big Data technologies.

This document entitled “Data Management Plan” (DMP) outlines the strategy for data management to be applied throughout the course of the LAMBDA project, as well as the actions that will be taken after the LAMBDA project has been finished. It is based on the “Guidelines on Data Management in Horizon 2020” document and follows the FAIR Data management principles. The DMP will be updated in the course of the project whenever significant changes arise, in addition to the periodic evaluation/assessment of the project.

This deliverable sets out the quality practices for the LAMBDA project and provides assurance that the quality control and risk management requirements are planned appropriately. It is the first deliverable of Task 1.3 (quality control, risk management and self-assessment) which monitors the project implementation in order to work effectively towards achieving the project goals. Quality control, risk management and self-assessment procedures defined in the project proposal phase have been further elaborated and presented in this deliverable.

This deliverable is a one-page statement that PUPIN has declared the peer-reviewed publications in the Big Data and Analytics domain published by PUPIN staff in the last
three years preceding the start date of LAMBDA.