This paper describes the motivation, requirements, and challenges of integrating a geospatial infrastructure, based on standardized web services, into an earth observation (EO) data library. The design of harmonized data and information models of the EO and geospatial community is a precondition for interoperability at metadata, data and semantic levels. A major challenge arises from raising the awareness that interoperability is essential for an interdisciplinary use of EO data in Geographic Information System (GIS) and value-adding services.

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In the planetary sciences, the volume of remote sensing data and derived research products has been continuously increasing over the last five decades. The amount and complexity of data require growing sophistication in data analysis, data management, and data provision targeted at a growing research community. In order to efficiently manage and facilitate the reuse of research data and to provide stable and long-term access, sustainable research data solutions are needed. We here present a prototype for structured storage, management, and visualisation of planetary research data and discuss the particular benefits, as well as challenges of such an information system for data management, for establishing data references by cross-linking information, and for improving the visibility of data products. The prototype is a co-development of two research institutes of the German Aerospace Center (DLR) and is based on two components: the Earth Observation Center(EOC) Geoservice, which constitutes an infrastructure providing data storage and management capabilities, as well as an interface compliant with collaborative and web-based data access services, and the Environmental and Crisis Information Systems (UKIS), a framework for the implementation of geoscientific web applications.

Abstract. 3d visualisation of real spaces in the Internet is nowadays getting ready for all day usage. Because of higher complexity of 3d-compared to 2d visualisation, it is mostly used for high-end visualisations. The strategy of integrating them into existing spatial data infrastructures and making reuse of existing resources that are so far mostly used for 2d visualisation, created the opportunity to build 3d web-applications as an add-on. The recurring problems of web-based 3d visualisation raised the question, how special modules for 3d visualisation could also be made reuseable. We took a closer look especially on the so-called mappinglevel, which is essential for the type of visualisation, interactivity and some special analysis-tasks.

<p>We face unprecedented environmental challenges as a species, that threaten our existing way of life.  We are still learning to understand our planet, although we have a good idea how it works.  The speed of research needs to accelerate to provide information to decision makers, to better respond to our societal challenges.  To do this we need to move towards leveraging large datasets to speed up research, as proposed by Jim Grey in ‘The Fourth Paradigm’. In the world of research infrastructures we need to provide a means for scientists to access vast amounts of research data from multiple data sources in an easy and efficient way.  EOSC is addressing this but we are only scratching the surface when it comes to unleashing the full potential of the scientific community.  Datacubes have recently emerged as a technology in the Environmental and Earth system domain to store imagery data in a way that makes it easier and quicker for scientists to perform their research.  But with the scales of data volumes that are being considered, there are many challenges to curating, hosting, and funding this information in a centralised centre.  Our proposal seeks to leverage the existing National Research and Education (NRENs) infrastructures to store national repositories of regional Environmental and Earth system domain data, for this to be shared with scientists in an open, federated but secure way, conforming to FAIR principles.  This would provide levels of redundancy, data sovereignty and scalability for hosting global environmental datasets in an exascale world.</p>