BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.osgeo.org//foss4g-2026//talk//VZMXCF BEGIN:VTIMEZONE TZID:JST BEGIN:STANDARD DTSTART:20000101T000000 RRULE:FREQ=YEARLY;BYMONTH=1 TZNAME:JST TZOFFSETFROM:+0900 TZOFFSETTO:+0900 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-2026-VZMXCF@talks.osgeo.org DTSTART;TZID=JST:20260902T130000 DTEND;TZID=JST:20260902T133000 DESCRIPTION:The increasing volume and heterogeneity of digital research dat a have intensified the need for integrated research data management (RDM) infrastructures that support the full lifecycle of data stewardship across scientific domains. In agricultural and environmental sciences\, datasets commonly combine geospatial information\, experimental measurements\, tab ular records\, and model outputs\, demanding systems that align with the F AIR principles—ensuring data are findable\, accessible\, interoperable\, and reusable. While many research repositories provide strong metadata an d archival capabilities\, they often lack interactive exploration tools\, whereas geospatial platforms\, though rich in visualization features\, are typically not designed for comprehensive RDM workflows. This disconnect h inders data reuse\, as users cannot assess dataset content\, structure\, o r spatial context without downloading data or using specialized software. To bridge this gap\, this work presents the adaptation of GeoNode as a uni fied RDM infrastructure that integrates robust repository functionalities —such as persistent identifiers\, extended metadata models\, and structu red publication workflows—with advanced web-based visualization and inte ractive exploration capabilities. By enabling users to inspect both geospa tial and non-geospatial datasets directly in the browser\, the platform fa cilitates early understanding of data context and quality\, significantly improving discoverability and reusability. This approach demonstrates how GeoNode can be extended beyond its traditional role to serve as a scalable \, FAIR-compliant foundation for managing diverse research data in agricul tural and environmental sciences.\nThe presented platform has been develop ed at the Leibniz Centre for Agricultural Landscape Research to operate th e BonaRes Repository\, a research data repository supporting the German ag ricultural research community. The repository was originally established w ithin the BonaRes research initiative (meaning soil as a sustainable resou rce) and has since become part of the national research data management in itiative FairAgro\, which aims to build a FAIR-compliant data infrastructu re for agricultural research in Germany. The system currently hosts more t han one thousand datasets and is accessible to researchers across the Germ an agricultural research community.\nOne objective of this work was to inv estigate how a geospatial data platform can be adapted and extended to sup port the requirements of a domain-specific research data management infras tructure. Particular attention is given to the architectural integration o f repository workflows\, metadata interoperability\, data validation mecha nisms\, and scalable deployment infrastructure.The objective of this work is to investigate how an open-source geospatial data platform can be adapt ed and extended to support the requirements of a domain-specific research data management infrastructure. This work should motivate others to follow our path. \nA central requirement for research data infrastructures is th e support of interoperable and domain-relevant metadata models. The BonaRe s Repository integrates multiple metadata standards\, including the DataCi te Metadata Schema\, together with the ARC metadata model developed within the NFDI4Plants initiative to represent annotated research context. Furth er requirements are addressed through the BonaRes Metadata Schema\, an ext ended INSPIRE-oriented metadata schema for soil and agricultural research. \nSupporting efficient data ingestion while ensuring high data quality re mains a critical challenge for research data repositories. To address this \, we developed an open-source upload tool (https://github.com/zalf-rdm/up load-tool) that interfaces with the GeoNode backend via its REST API\, of fering researchers a structured\, guided workflow for dataset submission. The tool enables users to prepare datasets locally\, validate data structu res and metadata prior to upload\, and publish datasets through a transpar ent and reproducible process. A key enhancement to the workflow is the int egration of a data steward review process\, which allows data stewards to inspect uploaded datasets and request revisions to metadata or data struct ure to improve quality\, consistency\, and FAIRness before final publicati on. This collaborative feedback loop strengthens data governance and ensur es adherence to domain-specific standards. Implementing this workflow requ ired significant extensions to the GeoNode 4.x REST API to support program matic dataset management\, extended metadata handling\, and multi-step pub lication states\, including draft\, review\, and public release stages. To further enhance interoperability and automation\, we developed geonodectl (https://github.com/GeoNodeUserGroup-DE/geonodectl)\, a dedicated Python client and commandline client for the GeoNode API. Geonodectl provides a c lean\, structured interface for managing datasets\, metadata\, and publica tion workflows\, enabling seamless integration with external tools and aut omated ingestion systems.\nAdditional extensions in GeoNode enhance suppor t for research data workflows. Native non-geospatial dataset support—all ows tabular data (e.g.\, crop trials\, sensor records) to be managed along side spatial datasets. These datasets are visualized as interactive tables and grouped into a Tabular Collection\, a tabbed interface enabling seaml ess exploration of related data. The metadata model was extended for domai n-specific fields\, and the publication workflow now includes multi-stage curation with review and embargo. ORCID integration ensures persistent res earcher attribution. To improve usability for non-GIS experts\, the web UI was streamlined by hiding advanced features and enhancing visual clarity\ , making the platform more accessible to researchers without geospatial ex pertise. These improvements foster broader adoption across agricultural an d environmental research.\nReliable and scalable operation of the research data repository is essential for sustained use in research environments. To meet this requirement\, we adopted a Kubernetes-based deployment archit ecture using the geonode-k8s (https://github.com/GeoNodeUserGroup-DE/geono de-k8s) Helm chart\, a production-ready\, open-source deployment solution developed and maintained by the GeoNodeUserGroup-DE. This Helm chart provi des a fully automated\, declarative\, and reproducible way to deploy GeoNo de on Kubernetes clusters. By leveraging Kubernetes\, the infrastructure c an dynamically scale based on user demand\, ensuring consistent performanc e during peak usage\, shown in FoSS4g 2024 (Performance Benchmarking for R esource Allocation Optimization in GeoNode Ecosystems on Kubernetes Clouds ). This approach not only enhances system reliability and maintainability but also enables deployment across diverse environments—from local devel opment to cloud-based research infrastructures. \nThe presented work demon strates that GeoNode can serve as a foundation for domain-specific researc h data management infrastructures when complemented by targeted architectu ral extensions. By combining repository workflows with interactive geospat ial exploration capabilities\, the platform enables researchers to both pu blish and explore datasets within a unified environment.This approach sup ports improved dataset discoverability and practical data reuse\, while th e architectural patterns and open-source components developed in this proj ect provide a reference for other institutions seeking to implement intero perable research data infrastructures based on free and open-source geospa tial technologies. DTSTAMP:20260717T234908Z LOCATION:Cosmos1 SUMMARY:Extending GeoNode as a Foundation for Research Data Management Infr astructures in Agricultural Research - Marcel Wallschläger\, Igo Silva de Almeida URL:https://talks.osgeo.org/foss4g-2026/talk/VZMXCF/ END:VEVENT END:VCALENDAR