Student information
MSc thesis topic: Evaluate and Test Open Data Cube
You will be part of an international, cutting-edge and active EU Horizon project FAIRiCUBE with the mission of enabling players from beyond classic Earth Observation (EO) domains to provide, access, process and share gridded data and algorithms in a FAIR and TRUSTable manner.
The project’s goal is to leverage power of Machine Learning (ML) operating on multi-thematic datacubes for a broader range of governance and research institutions from diverse fields, who at present cannot easily access and utilize these potent resources.
You will be part of an international, cutting-edge and active EU Horizon project FAIRiCUBE with the mission of enabling players from beyond classic Earth Observation (EO) domains to provide, access, process and share gridded data and algorithms in a FAIR and TRUSTable manner.
The project’s goal is to leverage power of Machine Learning (ML) operating on multi-thematic datacubes for a broader range of governance and research institutions from diverse fields, who at present cannot easily access and utilize these potent resources.
One major objective is the creation of a FAIRiCUBE Hub, a crosscutting platform and framework for data ingestion, provision, analyses, processing and dissemination, to unleash the potential of environmental, biodiversity and climate data through dedicated European data spaces.
Data cubes are complex data representations enabling researchers to integrate and analyse data across multiple dimensions such as space, time, and thematic variables, providing a comprehensive framework for environmental monitoring and decision-making. Data cubes have significant role in spatial domain related big data infrastructures by enabling efficient analysis of large datasets. The structured format of data cubes allows creating complex queries and analytical tasks, which are essential for gaining actionable insights.
Currently two infrastructure stacks are considered as part of FAIRiCUBE Hub to host and serve data cube data. You will be contributing to complement FAIRiCUBE Hub with a third open-source alternative from the Open Data Cube (ODC) community. Open Data Cube (ODC) is an Open Source Geospatial Data Management and Analysis Software project that helps you harness the power of Satellite data. At its core, the ODC is a set of Python libraries and PostgreSQL database that helps you work with geospatial raster data.
Relevance to research/projects at GRS or other groups
FAIRiCUBE is an EU funded research & innovation project with a consortium of 8 partners from Norway, Germany, Austria, Luxembourg, Spain, Italy and The Netherlands with WER as a key partner and contributor.
FAIRiCUBE is a research project with a focus on working with large (geospatial) datacubes and machine learning applications. Through this work, we will be able to provide a wider overview of existing geo-datacube solutions.
Objectives and Research questions
FAIRiCUBE is an ongoing research project and in cooperation with the student, additional research questions can be included in the master thesis. As a base definition of the master's thesis, we envision that you will
- Get familiar with academic and commercial data cube provisioning solutions;
- Get familiar with the Open Data Cube concept and software solution;
- Get familiar with the F.A.I.R. aspect of data ingestion and provisioning;
- Get familiar with the FAIRiCUBE meta data concepts;
- Install and manage your own instance running ODC;
- Test the data ingestion and provisioning on a example FAIRiCUBE datasets (subsets);
- Scale up your example to host several EO datasets or a larger dataset;
- Benchmark your ODC data serving;
- Assist one FAIRiCUBE use case to apply a machine learning application using your ODC installation;
- Document your results, train other FAIRiCUBE project members;
- Be part of an exciting research project, extend your academic horizon and participate in project meetings;
- Start creating your own international network and contribute to a meaningful and cutting-edge research project!
Requirements
- Basic Linux and programming knowledge
- Basic geographical and statistics knowledge
- Basic understanding of data cubes and earth observation data
- Advanced English skills (reading and writing)
Literature and information
Theme(s): Modelling & visualisation