BigDataStack Connected Consumer Use Case implementation: in-store consumer-tailored recommendations via food retailers’ on-line applications.

The Connected Consumer use case utilizes the BigDataStack environment to implement and offer a recommender system for the grocery market. All of the data that are used to train the analytic algorithms of the use case are corporate data provided by one of the top food retailers companies in Spain. The final goal of the scenario is to make use of the capabilities of BigDataStack to produce in-store tailored recommendations to customers at the on-line applications of the food retailer.

Online the BigDataStack software components

The BigDataStack project published all software components, most of them Open Source in the online catalogue available here: 

The catalogue provides you with a downloadable factsheet for each of the components, information on its license and access to the code on GitHub or GitLab for the Open Source components. 

Women in science day

11th of February is the "women in science" day and we would like to celebrate it highlighting the role of our women inside the project.
We asked Amaryllis Raouzaiou, senior researcher and project manager at the Athens Technology Center to answer 3 quick questions about her role in the project and her personal experience as a woman through a career as a researcher.

Three BigDataStack takeaways on Artificial Intelligence and Big Data transforming Business and Society

Three BigDataStack team members attended the European Big Data Value Forum (EBDVF) on Artificial Intelligence and Big Data transforming Business and Society, in October 2019, in Helsinki. Ana- Belén Gonzalez (Atos) Leads the exploitation work in BigDataStack, Mauricio Fadel (NEC) is BigDataStack’s connection to the BDVA where he joins the technical and coordination meetings. Bin Cheng, Senior researcher at NEC European labs, gave a talk during EBFVF on Enabling Smart Manufacturing with Federated AI at the Edge about his research on edge computing, developed in BigDataStack. We video interviewed them there and asked about their main takeaways

Call for Papers for IEEE BIGDATASERVICE2020 Workshop

Authors are invited to submit original research work to the BIGDATASERVICE 2020 workshop on Big Data Infrastructures For Data Intensive Applications.  The workshop takes place at the Sixth IEEE International Conference on Big Data Computing Service and Machine Learning Applications on 13 April, in Oxford. The deadline for submission is extended to 31 January. 

A BigDataStack Seafarer Tale

Real Time Ship Management Danaos use case. A Seafarer's vessel has to complete its route within a specific time-frame. When a part of the main engine fails unexpectedly, the ship risks staying off-hire. This can be very damaging to a shipping company, as chartering revenues decrease, while replacing a spare part immediately increases cost. The seafarer needs identification of potential failure to allow timely ordering, or even replacement of spare parts before failure.


BigDataStack at the 2nd Workshop of EU Research & Innovation Maritime Projects

 Danaos Auditorium |Akti kondili 14 | Piraeus | 5th Nov 2019 |10.00 -18.00


2nd Workshop of EU Research & Innovation Maritime Projects

The Hellenic contribution


Today, on the 5th of November more than 200 participants took part in the 2nd Workshop of EU Research & Innovation Maritime Project, hosted by Danaos.

Policy4Data Policy Brief

Big data in Europe for 2020 and beyond: Policy insights and recommendations from current H2020 big data projects.

Kuryr network performance optimisation in BigDataStack

Kuryr provides a significant boost in pod-to-pod network performance. 
With Kuryr, we are able to achieve higher throughput, solving application needs for better bandwidth while at the same time achieving better utilization on our high bandwidth NICs.

Triple Monitoring Engine, our response to variable resources requests

BigDataStack Innovation Potential: Initial Plan and Activities

As the Cloud offering for Big Data increases, the potential configurations for running computation become immeasurable. While, initially, this potentially endless set of possibilities is great news for the user, the complexity of big data infrastructures makes it unaffordable for the average user to keep track of the status of the system and dynamically adapt.