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Data publishing and archiving: paving the way to data-intensive science (co-organized)
Convener: Jens Klump  | Co-Convener: Michael Diepenbroek 
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During the last decades, geosciences and science in general, has entered a new mode of operation. Data science - defined as a combination of science, informatics, computer science, cyberinfrastructure, and information technology to process and analyse large corpora of data - has emerged as the "fourth paradigm" of science alongside empirical, theoretical, and computational approaches. This profoundly changes the way geoscientists work.

Confronted with this great amount of data available, several questions arise: How and where are these data stored? Does effective data exchange exists between scientists? Are the existing data sets available and accessible for the scientific community? It is evident that data supporting published research must be accessible, which today rarely is the case. A streamlined way of ensuring that data are made accessible, and in user-friendly formats, is sorely missing. One of the goals of this session is to assess the current state of data storage and exchange and indicate progress made to date and the challenges that presently exist.

Another important aspect of the use of data in scientific work is their traceability from publications back to the sources to allow independent verification and re-evaluation of results in case new interpretations are found. Publishing scientific data is therefore essential for the transparency of scientific work and also provides the necessary incentives for data producers. Persistent identifiers, such as Digital Object Identifiers (DOI) can be used to make reference published data entities and make them citeable, either as supplementary material to a classical publication, or as data publications of their own merit. Data publication services need to be integrated into the traditional science publication process, including assessment of data quality analogous to the classical peer-review process. Access to these data requires a coherent system of libraries, science publishers, and certified data repositories.