Implementing FAIR in a Collaborative Data Management Framework


Contact
Angela.Schäfer [ at ] awi.de

Abstract

Today's fast digital growth made data the most essential tool for scientific progress in Earth Systems Science. Hence, we strive to assemble a modular research infrastructure comprising a collection of tools and services that allow researchers to turn big data into scientific outcomes. Major roadblocks are (i) the increasing number and complexity of research platforms, devices, and sensors, (ii) the heterogeneous project-driven requirements towards, e. g., satellite data, sensor monitoring, quality assessment and control, processing, analysis and visualization, and (iii) the demand for near real time analyses. These requirements have led us to build a generic and cost-effective framework O2A (Observation to Archive) to enable, control, and access the flow of sensor observations to archives and repositories. By establishing O2A within major cooperative projects like MOSES and Digital Earth in the research field Earth and Environment of the German Helmholtz Association, we extend research data management services, computing powers, and skills to connect with the evolving software and storage services for data science. This fully supports the typical scientific workflow from its very beginning to its very end, that is, from data acquisition to final data publication. The key modules of O2A's digital research infrastructure established by AWI to enable Digital Earth Science are implementing the FAIR principles: Sensor Web, to register sensor applications and capture controlled meta data before and alongside any measurement in the field Data ingest, allowing researchers to feed data into storage systems and processing pipelines in a prepared and documented way, at best in controlled NRT data streams Dashboards, allowing researchers to find and access data and share and collaborate among partners Workspace, enabling researchers to access and use data with research software in a cloud-based virtualized infrastructure that allows researchers to analyse massive amounts of data on the spot Archiving and publishing data via repositories and Digital Object Identifiers (DOI)



Item Type
Conference (Talk)
Authors
Divisions
Primary Division
Programs
Primary Topic
Research Networks
Peer revision
Not peer-reviewed
Publication Status
Published
Event Details
EGU General Assembly 2020, 04 May 2020 - 08 May 2020, Online.
Eprint ID
52025
DOI 10.5194/egusphere-egu2020-19631

Cite as
Schäfer, A. , Anselm, N. , Eilers, J. , Frickenhaus, S. , Gerchow, P. , Glöckner, F. O. , Haas, A. , Herrate, I. , Koppe, R. , Macario, A. , Schäfer-Neth, C. , Silva, B. and Fischer, P. (2020): Implementing FAIR in a Collaborative Data Management Framework , EGU General Assembly 2020, Online, 4 May 2020 - 8 May 2020 . doi: 10.5194/egusphere-egu2020-19631


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