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.

This document outlines the envisioned Dissemination, Communication and Exploitation strategy of the LAMBDA project, as well as the specific objectives of dissemination activities until the end of the project. Furthermore, it reports on continuing dissemination activities of the LAMBDA project in the first six months.

One of the LAMBDA objectives is strengthening the linkages with industry and developing commercial awareness in order to facilitate the early involvement of researchers in the process of identifying real-world challenges, as well as to understand the use of Big Data and emerging technologies for competitive advantage of companies. Furthermore, research challenges and possibilities for solving problems in industry will be identified through a joint work with key stakeholders.

This deliverable aims to present the Action plan for scientific excellence and innovation capacity building of the PUPIN Institute in the Big Data domain for the following two years (2019-2020).

Deliverable 2.2 is one of the key LAMBDA deliverables setting up a plan of Education, Research and Development activities for the LAMBDA consortium until the end of the project. It is based on the analysis of Big Data tools and research trends (see Deliverable 2.1), analysis of synergies and complementarities between the research and training expertise of the individual partners of the LAMBDA consortium (see Deliverable 2.3) and the needs of the main beneficiary (Institute Mihajlo Pupin) and other stakeholders from the region. 

In the context of WP2 (Exploiting Synergies and Setting the Twinning Initiative) Task 2.2 (SWOT analysis), an action was taken at the beginning of the project with the aim to identify strategic improvement opportunities for the Mihajlo Pupin Institute (PUPIN) as a main beneficiary of the LAMBDA project.

The SWOT methodology is based on four steps: