EGU23-7052, updated on 25 Feb 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

FAIRiCUBE: Enabling Gridded Data Analysis for All

Katharina Schleidt1 and Stefan Jetschny2
Katharina Schleidt and Stefan Jetschny
  • 1DataCove e.U., CEO, Austria (
  • 2NILU – Norwegian Institute for Air Research

Previously, collecting, storing, owning and, if necessary, digitizing data was vital for any data-driven application. Nowadays, we are swimming in data, whereby one could postulate that we are drowning. However, downloading vast data to local storage and subsequent in-house processing on dedicated hardware is inefficient and not in line with the big data processing philosophy. While the FAIR principles are fulfilled as the data is findable, accessible, and interoperable, the actual reuse of the data to gain new insights depends on the data user’s local capabilities. Scientists aware of the potentially available data and processing capabilities are still not able to easily leverage these resources as required to perform their work; while the analysis gap entailed by the information explosion is being increasingly highlighted, remediation lags.

The core objective of the FAIRiCUBE project is to enable players from beyond classic Earth Observation (EO) domains to provide, access, process, and share gridded data and algorithms in a FAIR and TRUSTable manner. To reach this objective, we are creating the FAIRiCUBE HUB, a crosscutting platform and framework for data ingestion, provision, analysis, processing, and dissemination, to unleash the potential of environmental, biodiversity and climate data through dedicated European data spaces.

In order to gain a better understanding of the various obstacles to leveraging available assets in regard to both data as well as analysis and processing modalities, several use cases have been defined addressing diverse aspects of European Green Deal (EGD) priority actions. Each of the use cases has a defined objective, approach, research question and data requirements.

The use cases selected to guide the creation of the FAIRiCUBE HUB are as follows:

  • Urban adaptation to climate change
  • Biodiversity and agriculture nexus
  • Biodiversity occurrence cubes
  • Drosophila landscape genomics
  • Spatial and temporal assessment of neighborhood building stock

Many of the issues encountered within the FAIRiCUBE project are formally considered solved. Catalogues are available detailing the available datasets, standards define how the datasets are to be structured and annotated with the relevant metainformation. A vast array of processing functionality has emerged that can be applied to such resources. However, while all this is considered state-of-the-art in the EO community, there is a subtle delta blocking access to wider communities that could make good use of the available resources pertaining to their own domains of work. These include, but are not limited to:

  • Identifying available data sources
  • Determining fitness for use
  • Interoperability of data with divergent spatiotemporal basis
  • Understanding access modalities
  • Scoping required resources
  • Providing non-gridded data holdings in a gridded manner

There is great potential in integrating the diverse gridded resources available from EO sources within wider research domains. However, at present, there are subtle barriers blocking this potential. Within FAIRiCUBE, these issues are being collected and evaluated, mitigation measures are being explored together with researchers not from traditional EO domains, with the goal of breaking down these barriers, and enabling powerful research and data analysis potential to a wide range of scientists.

How to cite: Schleidt, K. and Jetschny, S.: FAIRiCUBE: Enabling Gridded Data Analysis for All, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7052,, 2023.