Insights into data sharing from GEO-XII
The XII intergovernmental Group on Earth Observations (GEO) was held in Mexico City from November 9-13, 2015. The main topic was the commitment to share Earth Observation data and the main challenge is how to share observations in an era where data grows exponentially and big issues such as human development and climate change do require these data.
This was the first time that I have had the opportunity to participate in a high level meeting where the quorum was dominated by politicians and not scientists. There were around 400 delegates from 41 GEO governments and 39 partners organizations. They spend the week in closed meetings where only delegates can address to the assembly and participate into the regional caucuses. Being from North America (Mexico!) I could snoop a little into the Americas caucus and saw how different the political language is from the scientific language we are used to. I have been in the geomatics/geocomputing business for a while and what I heard it was the same, or very similar, as in the first big conference I attended a Latin-American remote sensing and GIS conference 11 years ago in Santiago, Chile – sustainable growth – how can Latin-America focus in critical environmental observations to allow leaders to make the best informed decisions to benefit the humanity. I do not know what where the main topics in the other caucuses and the promises of every candidate but I am sure the topics where very close to ones in Latin-American.
The very first day Gary Holmes and myself had the opportunity to participate in the Data Sharing Principles, Requirements and Implementation in Lower and Middle Income Countries (LMICs) side event. The take-home message was that we must actually put in practice the GEO and the Committee on Data for Science and Technology (CODATA) data sharing principles: data to be open and unrestricted, free to end users, informative and assessed for quality, easy to access, interoperable, sustainable and restricted for a limited time if justified; data sharing to be timely; credit to be given to data contributors; and data access to be equitable.
I participated in another relevant side event: Land Cover: Harmonized Pathways Towards Policy Needs. It was very beneficial especially for the MELODIES WP3 since part of our work is to create a Land Cover (LC) map to improve the GHG inventories due to LC changes. In here, the demand for yearly global LC information was highlighted but even more important were the demand for the standardization of legends, classifications and accuracy. We do not have to go far away to see that this is not happening (yet). Here in Europe several countries still have their own methodology to derive their national LC products and therefore harmonization of the final European datasets is not only a matter of merging two datasets.
During the second day I had the opportunity to present the citizen science related work that the MELODIES partners have been doing as part of the Citizen GEOSS session. The MELODIES video helped a lot when having 5 minutes to present the project and a couple of examples (crisis mapping and groundwater modeling services)! Several live demos of mobile apps were also on show - these were developed for citizen-based observations as part of MYGEOSS' first call for innovative apps that address citizens’ needs from MYGEOSS. The 3rd call will open on 15th March.
One of the most relevant sessions for my personal research interests was the GEO Biodiversity Observations Network (GEO BON) session. They acknowledged that more data doesn’t translate necessarily into better monitoring and proposed a global framework that measures Essential Biodiversity Variables all the way from genetic composition, species population to ecosystem structure. They are developing global indicators integrating biodiversity observations, remote sensing data and models (all the things I do like!) to assess specific goals of the Convention on Biological Diversity plan 2011-2020. The outstanding fact is that all GEO BON participants agreed to use complementary data, for instance, in-situ and EO data, to fill geographical and taxonomical gaps and put everything into a 1km resolution grid. This for instance has never been achieved in other scientific communities and is indeed a good example of standardization and open data to solve specific issues and make data comparable and therefore truly useable.