The EnviDat Concept for an Institutional Environmental Data Portal

EnviDat is the environmental data portal developed by the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. The strategic initiative EnviDat highlights the importance WSL lays on Research Data Management (RDM) at the institutional level and demonstrates the commitment to accessible research data in order to advance environmental science. EnviDat focuses on registering and publishing environmental data sets and provides unified and efficient access to the WSL’s comprehensive reservoir of environmental monitoring and research data. Research data management is organized in a decentralized manner where the responsibility to curate research data remains with the experts and the original data providers. EnviDat supports data producers and data users in registration, documentation, storage, publication, search and retrieval of a wide range of heterogeneous data sets from the environmental domain. Innovative features include (i) a flexible, three-layer metadata schema, (ii) an additive data discovery model that considers spatial data and (iii) a DataCRediT mechanism designed for specifying data authorship. In addition, the overall user-friendly appearance in EnviDat provides an important opportunity for showcasing WSL research activities and results. The EnviDat portal builds on a conceptual system consisting of a core system, a set of guiding principles and a number of key services. Its development closely follows the conceptual framework, being guided by principles towards the ultimate goal of providing useful services for researchers

Cloud-Based Architectures for Auto-Scalable Web Geoportals towards the Cloudification of the GeoVITe Swiss Academic Geoportal

Cloud computing has redefined the way in which Spatial Data Infrastructures (SDI) and Web geoportals are designed, managed, and maintained. The cloudification of a geoportal represents the migration of a full-stack geoportal application to an internet-based private or public cloud. This work introduces two generic and open cloud-based architectures for auto-scalable Web geoportals, illustrated with the use case of the cloudification efforts of the Swiss academic geoportal GeoVITe. The presented cloud-based architectural designs for auto-scalable Web geoportals consider the most important functional and non-functional requirements and are adapted to both public and private clouds. The availability of such generic cloud-based architectures advances the cloudification of academic SDIs and geoportals

Cloud-Based Architectures for Auto-Scalable Web Geoportals towards the Cloudification of the GeoVITe Swiss Academic Geoportal

Cloud computing has redefined the way in which Spatial Data Infrastructures (SDI) and Web geoportals are designed, managed, and maintained. The cloudification of a geoportal represents the migration of a full-stack geoportal application to an internet-based private or public cloud. This work introduces two generic and open cloud-based architectures for auto-scalable Web geoportals, illustrated with the use case of the cloudification efforts of the Swiss academic geoportal GeoVITe. The presented cloud-based architectural designs for auto-scalable Web geoportals consider the most important functional and non-functional requirements and are adapted to both public and private clouds. The availability of such generic cloud-based architectures advances the cloudification of academic SDIs and geoportals

Cloud Optimized Raster Encoding (CORE): A Web-Native Streamable Format for Large Environmental Time Series

The Environmental Data Portal EnviDat aims to fuse data publication repository functionalities with next-generation web-based environmental geospatial information systems (web-EGIS) and Earth Observation (EO) data cube functionalities. User requirements related to mapping and visualization represent a major challenge for current environmental data portals. The new Cloud Optimized Raster Encoding (CORE) format enables an efficient storage and management of gridded data by applying video encoding algorithms. Inspired by the cloud optimized GeoTIFF (COG) format, the design of CORE is based on the same principles that enable efficient workflows on the cloud, addressing web-EGIS visualization challenges for large environmental time series in geosciences. CORE is a web-native streamable format that can compactly contain raster imagery as a data hypercube. It enables simultaneous exchange, preservation, and fast visualization of time series raster data in environmental repositories. The CORE format specifications are open source and can be used by other platforms to manage and visualize large environmental time series