TEAM LEADER: Peter Haro, SINTEF, peter.haro(at)sintef.no
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.
TEAM LEADER: Alaitz Zabala, UAB, alaitz.zabala(at)uab.cat
TEAM MEMBERS: Joan Masó, CREAF
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.
TEAM LEADER: David Kolitzus, GeoVille (firstname.lastname@example.org)
TEAM MEMBERS: Martin Siklar (siklar(at)geoville.com) , Stefanie Rohland (rohland(at)geoville.com), Sigrid Mourits-Andersen (mourits-andersen(at)geoville.com)
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.