Sprecher
Beschreibung
Experiments have per definition an unknown outcome and need adaption and improvement during their runtime. Especially user experiments are frequently changed or even just temporarily set up. On the other hand, policies develop towards open science what is undeniably useful in our field since drive lasers/facilities and experiments are cutting-edge but always have their peculiarities, hence general reproduction of results at other facilities is limited to their capabilities, manpower, funding and research programs.
If experiments could be stored in a generic data format with all data and metadata, that format could allow for analysis by the authoring group – as they would do without. However, that format could immediately serve for FAIR data storage without further effort for the user group. Especially interoperability and re-usability would be ensured because the authors of the data would have no other (privileged) access than everyone. Interoperability also enables machine learning-based data analysis, strengthening the potential outcome of the experiment. Having that ML processing online, live feedbacks are conceivable if the facility provides the required means. If many facilities would employ that format, users could re-use their analysis workflows, increasing productivity and enabling cross-facility studies.
We will illustrate this idea and discuss challenges.
