Results of the Patras DataBio Hackathon 2019

The jury of the Patras DataBio Hackathon 2019 selected the following projects as overall winners of this hackathon:

Congratulations to all the winning teams and many thanks for participation to all participants!

This is a video showing the winning application in action:

Lisbon INSPIRE Hackathon 2019: Team 3 – Fishy Data

TEAM LEADER: Peter Haro, SINTEF, peter.haro(at)

TEAM MEMBERS: Øystein Knutsen, student, SINTEF, Dmitrij Kožuch, cartographer, GIS specialist, developer, Plan4All association

PROJECT IDEA: The main idea pertains to interconnecting public and private datasets to create better machine learning methodologies and prediction modules for the fishery domain. Furthermore, for this to provide added value for end users in systems such as DSS, big data visualization is a key facet, thus the team will focus on collating data and visualizing it in an effective manner. 

The initiative is based on activities in the DataBio project,

Lisbon INSPIRE Hackathon 2019: Team 2 – Inclusion of Scientific Publications in Geospatial User Feedback

TEAM LEADER: Alaitz Zabala, UAB, alaitz.zabala(at)


PROJECT IDEA:  Simplify the inclusion of scientific publications in the Geospatial User Feedback by adding an automatic import from a RIS citation format.

Feedback items related to publications in several elements: publications, reference documents,… 

Currently, describing a scientific publication when filling in a Geospatial User Feedback item, means describing much information and even creating new resources (e.g. individual authors). This is currently a manual process, so mistakes can be taken.

As many journals allow describing a citation using standard formats such as RIS, the Geospatial User Feedback system, NiMMbus, can benefit by adding the functionality of automatically importing the RIS citation format. This will lead to the easy creation of new publication citations.

Lisbon INSPIRE Hackathon 2019: Team 1 – The Future of EO in Agriculture, Possibilities and Constraints

TEAM LEADER: David Kolitzus, GeoVille (

TEAM MEMBERS: Martin Siklar (siklar(at) , Stefanie Rohland (rohland(at), Sigrid Mourits-Andersen (mourits-andersen(at)

PROJECT IDEA: Collect scientific evidence, success stories and related initiatives regarding current Earth Observation (EO) practices to remove or reduce gaps and identify priorities to meet identified key user requirements in the agricultural domain.  This will serve as a basis for reaching out to dedicated EU DGs and the respective decision makers to foster the integration of EO data and related technologies in the agriculture sector.

The findings of this hackathon will be developed further and combined with other knowledge hubs.

This initiative is based on activities in the EO4Agri project –

The additional impact shall be created by reaching out to key science experts to validate our findings.

TEAM 6: Integration of Meteoblue Data with Sensors and Visualisation Client

This is the team no. 5 for the Patras DataBio Hackathon 2019.

Team mentors: Marek Splichal, Raitis Berzins, Michal Kepka

Description: For the purposes of this hackathon, Meteoblue data / image / map API for weather forecasts and historic data will be available. The goal of this team is to support integration of these data with HSLayers NG and SensLog and provide climatic services.

INSPIRE Hackathons Featured at the EuroGEOSS Workshop 2019

The results from the distributed INSPIRE hackathons (Patras DataBio Hackathon 2019 and the Lisbon INSPIRE Hackathon 2019) will be presented at the EuroGEOSS Workshop 2019 in Lisbon, 4th July 2019 at the session Best practices on how to involve users to achieve EO service sustainability (2-3.30pm).

More information about the EuroGEOSS Workshop 2019 can be found at

TEAM 5: Unusual Data Exploration

This is the team no. 5 for the Patras DataBio Hackathon 2019.

Team mentors: Pavel Hájek, Runar Bergheim, Raul Palma

Description: We would like to inspect opportunities of statistical data across the Europe, in order to explore new, unexpected patterns in data. First of all, any relevant statistical data about demography, agriculture, industry, etc. need to be found and inspected. Then, such data should be consolidated to statistical areas of NUTS3 regions, if they are not already. And finally, appropriate (multi criterion) analysis should be applied that may  unveil unusual data patterns and relations.

European Big Data Value Forum 2019

European Big Data Value Forum

We are happy to inform you that you can already register to the European Big Data Value Forum 2019 ( that will take place from 14 to 16 of October in Helsinki (Finland). You can check the entry fees here:, and get your tickets hereEarly bird tickets are available until the 26th of July.

The European Big Data Value Forum is the flagship event of the European Big Data community. Around the theme “Artificial Intelligence and Big Data Transforming Business and Society”, the edition of this year, jointly organized by the BDVA, the EC and VTT, is aimed to attract more than 600 participants, including relevant European industry players, policy makers and research community. You cannot miss it!