- GEOSS Platform - Data knowledg...
GEOSS Platform - Data knowledge
26 Nov 2019
Combatting Climate Change, realising the 2030 Agenda on Sustainable Development, and reducing Disaster Risk can benefit largely from the ever-growing quantities of EO data. Their size, diversity and scattering require, however, sophisticated tools that enable easy access and handling of data, derived products and background information like data origin, reliability, models and algorithms used for processing.
The GEOSS Platform considers this, and is testing evolved capabilities implementing a series of scenarios that illustrate its potential to support access and use of Data and Knowledge as a possible contribution to the implementation of a results-oriented GEOSS. These scenarios were demonstrated during the GEO Week 2019 in Canberra (Australia) from 4 to 9 November and are shown in this presentation. Moving these to operations could be a next step, but first requires agreement with main GEO Stakeholders e.g. regarding an evolved GEOSS architecture.
This article elaborates on one of the scenarios. It shows how the GEOSS Platform could potentially provide value to different categories of users, including Earth scientists and policy makers, in finding, producing and analysing information, ultimately supporting the process of knowledge acquisition by the final consumers.
The demonstrated GEOSS Platform capabilities enable:
- Harmonised discovery and access of data, information and knowledge from heterogeneous distributed sources
- Analytical comparison of resources
- Value added products generation and sharing
- Knowledge building through mediated collaboration (registration of models, algorithms, data; curation of relations between data, services and publications)
Sustainable Development Goal (SDG) 15.3.1 Indicator Computation and Inspection
This scenario shows how the GEOSS Platform can support an Earth scientist in computing Sustainable Development Goal (SDG) indicator 15.3.1 "Proportion of land that is degraded over total land area" through reproduction of a scientific experiment conducted in the context of the EC co-funded project GEO Essential and described in a scientific paper. Policy makers may access both the results of this exercise and the SDG indicator value provided by the UN Statistics Division, which is the custodian agency, to perform their analyses or e.g. compare them.
Land degradation is a real-life problem and is defined as the reduction or loss of the biological or economic productivity and complexity of rain fed cropland, irrigated cropland, or range, pasture, forest and woodlands resulting from a combination of pressures, including land use and management practices. Total land area is the total surface area of a country less the area covered by inland waters, like major rivers and lakes. The indicator is expressed as a percent of the degraded land over this total area.
To assess the area degraded, SDG Indicator 15.3.1 integrates information from three sub-indicators: Vegetation productivity, Land cover, and Soil organic carbon. In the GEOSS Platform, this indicator is generated using the Trends.Earth model, which computes the sub-indicators and integrates them into a final SDG 15.3.1 indicator. This is produced in the form of a map and of a table reporting areas potentially improved and degraded for the area of analysis (Europe in the present example).
The GEOSS Portal interprets and represents this information, thus addressing the needs of scientists and facilitating the generation of knowledge for evidence-based decision-making as shown in the image below, and this land degradation video.
Through the GEOSS Platform, an Earth scientist can search for the indicator in question for the area of interest "SDG 15.3.1 in Europe" and browse through the results of this search. They can then select the result item regarding "GEO Essential SDG 15.3.1". This selection will already enable the retrieval of relevant information regarding the experiment conducted by GEO Essential, in particular, the scientific publication Synergising global tools to monitor progress towards land degradation neutrality, which describes the experiment (in this case available on ScienceDirect.com).
At this point, the Platform allows the user to select a specific model (among the ones associated to the selected search result); the European one (as demonstrated in the image below) can be selected to compute the indicator for Europe. The Platform associates the model to the actual processing services that enable its computation, which the user can access and run in a user-friendly way.
The process workflow can be inspected and data can be searched and selected as input to the service (the above mentioned three sub-indicators). In addition, a Cloud computing platform of preference (among a set that includes the DIAS platforms and AWS) can be chosen. The user can then start the computation on the selected platform and eventually obtain and possibly visualise the results.
If desired, results can be published in the GEOSS Platform for use by others, e.g. policy makers. In fact, policy makers performing a search for SDG 15.3.1 can find and retrieve (e.g. visualised on a map or in table format) the indicator values previously published by the Earth scientist (shown above) and possibly compare them with the values provided by the UN Statistics Division (as shown below). The GEOSS Platform would then offer tools that harmonize heterogeneous resources to allow their analytical comparison.
The GEOSS Platform is implemented and operated by various GEO members including ESA who is responsible for implementation and operations of the GEOSS Portal, CNR-IIA who is responsible for the implementation and operations of the Discovery and Access Broker, the University of Geneva who is responsible for the implementation and operations of the Yellow Pages and United States Geological Survey.- Federal Government Data Center who is responsible for the implementation and operations of the Status Checker. Large parts of the GEOSS Platform developments are co-funded via the EDGE project, a project receiving funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 776136.
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