TEAM LEADERS: Raúl Palma (PSNC), Otakar Čerba (UWB)

PROJECT IDEA: The goal of this working group is to improve the SPOI dataset, both by extending and improving the underlying model (ontology), and to enrich the knowledge base with links to other relevant datasets. Regarding the ontology, we aim to include properties definitions, mappings to other vocabularies to the current taxonomy of classes, and possibly additional terms for annotations/ratings. Regarding the dataset, we aim to discuss and find possibility of linking with review/ratings datasets, relevant eurostat indicators, and others that may be identified during the hackathon.

TEAM LEADERS: Tomáš Řezník (Masaryk University/Lesprojekt), Raúl Palma (PSNC)

PROJECT IDEA: Our team would like to share with you the latest development of the European Horizon 2020 research and development project called Data-Driven Bioeconomy (DataBio). This DataBio workshop on metadata and semantics in the Era of Big Data may be considered as a starting point for any activity aiming at new way of (geospatial) metadata handling.

More precisely, we would like to focus on the following issues:

• Tight data and metadata together: ensure updated metadata despite Big data velocity updates.
• Support metadata heterogeneity: enable discovery of static (e.g. datasets) as well as mobile/other resources (e.g. sensors active during agricultural machinery fleet tracking) in a unified platform.
• Use efficient encodings: support XML-based format for backwards compatibility, on the contrary use visionary lightweight and semantics-based formats.
• Integrate metadata in other tools: the best metadata platform is the one where a user does not notice that (s)he works with metadata.

TEAM LEADER: Karel Jedlička, Carl Gutbrod

PROJECT IDEA: Current climate zones maps are very generic : they show large areas and display some differences in topography. Things like seaside buffer zones, weather divides and South-North differences are not shown. The idea is to provide local agro-climatic maps by processing detailed EO data.

Proposed workflow:

• Define the Area of Interest (EU/World?)
• Discuss if it would help to divide the area of interest to current climate zones or to propose different segmentation (e.g. Watersheds?).
• Design a method of segmentation
• Design a method of calculation of of average, mean, min and max, slope, aspect and altitude morphometric characteristics to each particular zone defined by vector overlay (Climate zone/Watershed/Open Land Use Zone/whatever)
• Design a method of calculation of water buffers
• Do a pilot study on smaller area (such as one country) as a proof of concept

TEAM LEADER: Mara Musil

PROJECT IDEA:  Our vision is to build Senslog as universal web server, which will be able to integrated observation from different sensors, different platforms, different standards. The SensLog is expect to be in future some type of observation broaked with focus on localised data. From this reason, we would like integrate connectors for currently two most important “industrial” standards. Are you working with Lora or SigFox,  if yes join our team to cooperate on integration of this protocol and testing of connectivity among different platforms.

TEAM LEADER: Andrey Sadovykh

PROJECT IDEA:

Sensors are used typically to monitor various physical or virtual world. The information retrieved from the sensors are generally stored in the database to be able to do the post processing and analysis. This database from sensors could grow exponentially. It often requires to have new database machines as the size increases. Cloud computing, virtualization and new database technologies are the key technologies to solve these problems.

Traditionally SQL databases are most widely used and have also proved reliable with time. However, with growing databases and availabilities of new database technologies, there is a possibility to get performance optimization. These technologies are often open source and highly scalable. With the new dynamics in the database technologies comparing existing SQL database to NOSQL database technology is highly recommended. Therefore, with the open sensor database and tools available from Senslog, we would like to do a proof of concept comparing these two technologies.

The first goal of the project is doing a proof of concept of Senslog database migration from SQL (PostgreSQL)  to NOSQL (MongoDB). Typical techniques of transforming SQL model to Mongodb schema: tables to collections, converting relations to table embedding and Reference-IDs. This transformation will be particular to Senslog database logic, however, a general conclusion will be extracted.

The second goal of the project will be performance testing and comparison between these two (PostgreSQL and MongoDB) databases. The idea will be to deploy PostgreSQL (old schema) and MongoDB(with new schema) two instances on same characteristics machine.  We will develop test scripts for performance testing (load testing and stress testing) with performance testing tool (Jmeter).