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References and Further Reading

1.1 What is a Platform

Further reading

• Earth Observation Cloud Platform Concept Development Study Report: https://docs.ogc.org/per/21-023.html
• Big Earth data: disruptive changes in Earth observation data management and analysis? https://www.tandfonline.com/doi/full/10.1080/17538947.2019.1585976
• Enabling the Big Earth Observation Data via Cloud Computing and DGGS: Opportunities and Challenges: https://www.mdpi.com/2072-4292/12/1/62
• An Overview of Platforms for Big Earth Observation Data Management and Analysis: https://www.mdpi.com/2072-4292/12/8/1253
• The openEO API–Harmonising the Use of Earth Observation Cloud Services Using Virtual Data Cube Functionalities: https://www.mdpi.com/2072-4292/13/6/1125
• ESA Earth Observation Exploitation Platform Common Architecture (EOEPCA): https://eoepca.org

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1.2 What is a Data Cube?

Further Reading

• David Montero Loaiza et al (2023). Data Cubes for Earth System Research: Challenges Ahead. Earth ArXiv (Preprint). https://doi.org/10.31223/X58M2V
• Popular Data Cube Management Systems:
  • Open Data Cube
  • Rasdaman:
  • GDAL Cubes

References

• openeo.org (2022). What are Data Cubes.
• ESA (2018). Earth System Data Lab.
• Maximilian Söchting (2022). LexCube – Leipzig Explorer of Earth Data Cubes

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1.3 Open Science, Open Data and the FAIR Principles

Further Reading

Help for understanding licenses and choosing the right Open Source license

• Legal (FOSSA) (2023). Software Licencses In Plain English.
• GitHub Inc. (2023) Choose an open source license.

And plentiful resources on open source projects, how to contribute and incorporate them into your work

• opensource.com (2023). Open Source resources.

References

• European Commission (2022). What is open data?. https://data.europa.eu/elearning/en/module1/#/id/co-01 – 
  This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
• Open Knowledge Foundation (2022). Open Data Handbook.
• Fürst, Elena, Gänsdorfer, Nikos, Kalová, Tereza, Macher, Therese, Schranzhofer, Hermann, Stork, Christiane, & Thöricht, Heike (2022). Open Educational Resources Research Data Management. DOI: 10.5281/zenodo.6923397
• ARDC Ltd. (2022). How to Make Your Data FAIR. DOI: 10.5281/zenodo.7426145.
• GO FAIR (2022). The FAIRification Process.
• Mapscaping Podcast with Paul Ramsey (2021). GDAL – Geospatial Data Abstraction Library
• CEOS (2022). CEOS Analysis Ready Data.

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2.1 Data Discovery

Further Reading

• STAC tutorials
• Echoes in space course

References

• STAC
• OWSLib
• STAC Python Client (pystac_client)
• radiantearth.github.io/stac-browser
• OpenSearch specification

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2.2 Data Properties

Further Reading

• Standartized data management with STAC
• STAC sessions from FOSS4G 2023

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2.3 Data Access

References

• openeo.org – About OpenEO
• Edzer Pebesma, Wolfgang Wagner, Jan Verbesselt, Erwin Goor, Christian Briese, Markus Neteler (2016). OpenEO: a GDAL for Earth Observation Analytics. https://r-spatial.org/2016/11/29/openeo.html
• openeo.org – Project Deliverable 22
• openeo.org (2022). Processes on Datacubes

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3.2 Result Validation

Further Reading

• Video: Meyer, Hanna: Machine learning-based maps of the environment: challenges of extrapolation and overfitting. OpenGeoHub Summer School 2022 – KISTE project workshop, OpenGeoHub Foundation, 2022. https://doi.org/10.5446/59412

References

• Meyer, H., Pebesma, E. Machine learning-based global maps of ecological variables and the challenge of assessing them. Nat Commun 13, 2208 (2022). https://doi.org/10.1038/s41467-022-29838-9
• Meyer, H., & Pebesma, E. (2021). Predicting into unknown space? Estimating the area of applicability of spatial prediction models. Methods in Ecology and Evolution, 12, 1620–1633. https://doi.org/10.1111/2041-210X.13650
• Loew et al. (2017): https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1002/2017RG000562
• Brenning et al. (2012): https://doi.org/10.1109/IGARSS.2012.6352393
• Valavi et al. (2019): https://doi.org/10.1111/2041-210X.13107
• Roberts et al. (2017): https://doi.org/10.1111/ecog.02881
• Ploton et al. (2020): https://doi.org/10.1038/s41467-020-18321-y
• Milà et al. (2022): https://doi.org/https://doi.org/10.1111/2041-210X.13851
• Linnenbrink et al. (2023): https://doi.org/10.5194/egusphere-2023-1308
• Sabatini et al. (2022): https://doi.org/10.1038/s41467-022-32063-z