Acquisition and analysis of data in the laboratory are pervasive in the Earth, environmental, and planetary sciences. Analytical and experimental laboratory data, often acquired with sophisticated and expensive instrumentation, are fundamental for understanding past, present, and future processes in natural systems, from the interior of the Earth to its surface environments on land, in the oceans, and in the air, to the entire solar system. Despite the importance of provenance information for analytical data including, for example, sample preparation or experimental set up, instrument type and configuration, calibration, data reduction, and analytical uncertainties, there are no consistent community-endorsed best practices and protocols for describing, identifying, and citing laboratory instrumentation and analytical procedures, and documenting data quality. This session is intended as a kick-off working session to engage researchers, data managers, and system engineers, to contribute ideas how to move forward with and accelerate the development of global standard protocols and the promulgation of best practices for analytical laboratory data.
How to Prepare for this Session:Presentations:
View Recording: https://youtu.be/LOfb_4r7DBA
Takeaways- Analytical and experimental data are collected widely in both the field and laboratory settings from a variety of earth environmental and planetary sciences, spanning a variety of disciplines. FAIR use of such data is dependent of data provenance.
- Need community exchange of such data consider use of data is broader than the original use of data in the domain. Brings to mind interoperability of such data. Need networks of these data to be plugged into evolving CI systems. In seismology a common standard for data implemented by early visionaries was a massive boon to the field.
- Documentation of how analytical data were generated is time consuming for data curators providers etc. Having standards/protocols for data exchange protocols is urgently required for emerging global data networks. OneGeochemistry as example use case for international research group to establish a global network for discoverable geochemical data.
