Introduction: In the recent years, discussions and demands came up to push the sustainability, reusability and, last but not least, the interoperability of research data within different scientific disciplines. In order to provide platforms to a) facilitate use and reuse of data in a transparent and sustainable way and to b) comply with recommendations and guidelines, research initiatives such as [1-3] have been established. Besides this, [4-6] were founded in order to provide the scientific community with platforms to archive sharable, discoverable and citable research data. Furthermore, initiatives like Nationale Forschungsdateninfrastruktur (NFDI) on a German national and the European Open Science Cloud (EOSC) on a European level were established in order to provide a trusted and virtual environment that cuts across borders and scientific disciplines. All these initiatives are based on the FAIR principles in order to create findable, accessible, interoperable and reusable data [7]. Within missions e.g. to Mercury (BepiColombo), the Outer Solar System moons (JUICE), and asteroids (NASA`s Dawn mission) one way of scientific analysis is the systematic surface analyses based on the numeric and visual comparison and combination of different remote sensing data sets, such as optical image data, spectral-/hyperspectral sensor data, radar images, and/or derived products like digital terrain models (here: primary research data). The long-term storage of this mission data is guaranteed through the Planetary Data System (PDS) and Planetary Science Archive (PSA). Conditioned by the spatial component, the analyses mainly result in derived research data such as map(-like) figures, profiles/diagrams as well as models, and finally serve for describing research investigations within scientific publications. Hence, cross-links between different missions, surfaces, bodies and topics are possible and thematical analogies could be extracted by the spatial context. This includes a great potential to create a sustainable reuse of historical, current and future information. Aim: We here present a project that aims at a prototypical system for the structured storage, accessibility and visualization of planetary data compiled and developed within or with the contribution of Institute for Planetary Research (PF) at German Aerospace Center (DLR). The goal is to enable different user groups (currently limited to DLR) to store and spatially explore derived research data centrally, sustainably across multiple missions and scientific disciplines in planetary science for future investigations. Method and Implementation: Technically, the prototype is built upon well-established stack of open source software [8-10]. Furthermore, standards like [11] and [12], developed by the Open Geospatial Consortium (OGC), serve as communication between user interface and the server. This software and standards are already combined within two software frameworks developed at the German Remote Sensing Data Center (DFD): 1. data storage and management capabilities as well as OGC-compliant interfaces for collaborative and web-based data access services (EOC Geoservice) [13]. 2. UKIS (Environmental and Crisis Information Systems), a framework developed at DFD or the implementation of geoscientific web applications [14]. Starting the development of the prototype, as first step a user analysis and inventory of the available data and information diversity in PF is needed (cf. requirement analysis). The second step will be the data storage and management within EOC Geoservice which combines a PostgreSQL database and a data management via GeoServer. Therefore, a representative and exemplary data collection is used, based on a recent approach developed within PF [15]. Here, an existing database established at Planetary Spectroscopy Laboratory (PSL), handling different kinds of spatial data, meets a vector-based data collection of thematic, mainly geologic and geomorphologic mapping results [e.g. 16, 17], and raster-based global mosaics in different resolutions [18, 19]. This data merging enables a multi-parameterized querying across different data types, multiple missions and scientific disciplines in planetary science. The third step will be the implementation of a geospatial information system based on UKIS. Within this, the visualization and utilization of the exemplary data package will be realized in an interactive, web-based system that displays all different datasets within the individual spatial reference system. For the already existing framework of UKIS this means an adaptation for planetary usage. With the integration of a user management system, the prototype could also integrate rules for data access restriction, needed for ongoing missions. The fourth and currently final step is to configure generic interfaces. These will enable a connection to other DLR systems and databases like the electronic library (ELIB) on the one hand. On the other hand, other archives and repositories outside DLR, which are substantially related to the internal stored data, could be linked. Summary: UKIS, as DFD-developed software framework for web-based geographic information systems, together with a geospatial data access and data management services, such as the DFD-hosted EOC Geoservice, are the ideal basis for such a spatial platform due to their stable architecture. Both can adapt to other spatial reference systems, as well as provide and visualize the planetary data after individual system configuration. A research data information system of this kind is essential to ensure the efficient and sustainable utilization of the information already obtained and published by previous research. This is considered a prerequisite for guaranteeing a continuous and long-term use of scientific information and knowledge within the departments, the institute and potentially also outside of DLR. References: [1] RDA, www.rda-alliance.org; [2] GoFAIR, www.go-fair.org; [3] CODATA, www.codata.org; [4] figshare, www.figshare.com/; [5] zenodo, www.zenodo.org; [6] pangea www.pangaea.de [7] Wilkinson M. et al. (2015) Scientific Data, 3. 1-9, doi:10.1038/sdata.2016.18, [8] postgresql.org/, [9] geoserver.org/, [10] ecma-international.org/publications/files/ECMA-ST/Ecma-262.pdf, [11] opengeospatial.org/standards/wfs, [12] opengeospatial.org/standards/wms, [13] Dengler, K. et al. (2013) PV 2013, elib.dlr.de/86351/, [14] Muehlbauer, M. (2021) dlr.de/eoc/en/desktopdefault.aspx/tabid-5413/10560_read-21914/, [15] Nass, A. et al. (2017), [16] Nass, A. and the Dawn Science Team (2019)EPSC #1304, [17] Williams D.A. et al. (ed.), 2018, Icarus, 316, 1-204, [18] Roatsch et al, (2016) PSS doi:10.1016/j.pss.2016.05.011, [19] Roatsch et al., (2017) doi:10.1016/j.pss.2017.04.008

In the planetary sciences, the amount of remote sensing data and derived research products has been continuously increasing over the last few decades. The amount and complexity of the data require growing sophistication in data analysis, data management and data provision targeted at a wider research community. Here we present a prototype for structured storage and visualization of planetary data based on technology originally developed for Earth-based applications. This includes a centralized system for storing scientific findings and data products in order to efficiently manage, cross-link and enhance visibility of data products, including interim findings and source code. The aim here is to facilitate transparent management and re-use of research data and scientific results for long-term access and sustainable research data management.

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.

Imaging the environment is an essential method in spatial science when studying the Earth or any other planet. Thus, this method is also a crucial component in the exploration of the ocean floor but also of planetary surfaces. In both domains, this is applied at various scales – from microscopy through ambient imaging to remote sensing – and provides rich information for science. Due to recent the increasing number data acquisition technologies, advances in imaging capabilities, and number of platforms that provide imagery and related research data, data volume in nature science, and thus also for ocean and planetary research, is further increasing at an exponential rate. Although many datasets have already been collected and analyzed, the systematic, comparable, and transferable description of research data through metadata is still a big challenge in and for both fields. However, these descriptive elements are crucial, to enable efficient (re)use of valuable research data, prepare the scientific domains e.g. for data analytical tasks such as machine learning, big data analytics, but also to improve interdisciplinary science by other research groups not involved directly with the data collection. In order to achieve more effectiveness and efficiency in managing, interpreting, reusing and publishing imaging data, we here present a project to develop interoperable metadata recommendations in the form of FAIR [1] digital objects (FDOs) [2] for 5D (i.e. x, y, z, time, spatial reference) imagery of Earth and other planet(s). An FDO is a human and machine-readable file format for an entire image set, although it does not contain the actual image data, only references to it through persistent identifiers (FAIR marine images [3]). Thus, the FDOs for spatial sciences are characterized at their core by 5D navigation data mentioned above which discriminates them from imagery of other domains (e.g., medical). In addition to these core metadata, further descriptive elements are required to describe and quantify the semantic content of imaging research data. Such semantic FDOs are similarly domain-specific but again synergies are expected between Earth and planetary research. Subsequent, by developing ontology concepts for these two imaging domains, scientific analogies and causal connections between the two research domains can be illuminated. The main benefit expected by this project is to (1) improve the quality and reusability of future research data, (2) support a sustainable research data environment by closing the life cycle of the research data, (3) increase the inter- and transdisciplinary comparability of data sets, and (4) enable further scientific communities in transference of their own vocabularies, and in the use of the ontology concepts within other natural science applications. We here present the current status of the project, with the specific tasks on joint metadata description of planetary and oceanic data outlined. In particular we show how we intend to implement metadata for valuable research data in both domains in the future, and demonstrate where these developments should be adopted. [1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016), doi:10.1038/sdata.2016.18. [2] https://fairdigitalobjectframework.org/ [3] https://marine-imaging.com/fair/ifdos/iFDO-overview/