"intern" Employee Magazine Jülich Research Center 1/2022: The great data treasure
Exhausting all means
“Why do we need to go full throttle on data management? Because climate change and other global challenges are not waiting for us! If we want to make a decisive contribution to solutions at Jülich, we must exhaust all means. Putting it simply: the more accurate the metadata, the more valuable the research data. Therefore, we also need to make progress on metadata as quickly and consistently as possible in order to better combine scientific forces worldwide. If we succeed in doing this, we’ll be conducting a completely different kind of research in as little as ten years’ time – with high-quality data sets that are not yet available on a large scale today. I expect completely new branches of science to emerge – with huge gains in knowledge! However, a long, joint major effort is needed in order to get there. We can’t do without highly visible role models here who set an example of RDM in all institutes, showing how great the added value is if complete and clean metadata is the norm in all areas. This is particularly important for artificial intelligence and machine learning: such analytical methods require large masses of data, some of which come from different disciplines. Here, only metadata can tell us in which cases it is reasonable at all to use data sets together.
All this is well known, yet good RDM is still a big challenge for many researchers in their daily routine. Why’s that and how can the problem be fixed? With the Helmholtz Metadata Collaboration, or HMC for short, we are currently trying to find this out – for example through surveys in all Helmholtz Centers. With almost nine positions at the HMC for the research field of information, we have a pretty powerful force at Jülich alone to advance the topic throughout the Helmholtz Association. For the first time, we are currently getting a systematic overview of how researchers at all Helmholtz Centers deal with metadata. However, we also want to promote the topic in everyday work: we advise and train, develop software and create concepts for concrete use cases in our research – from microscopy at ER-C and data analysis at JSC to simulations at INM and IAS. Of course, as a scientist, I have great understanding for the fact that between experiments, conferences and publications, one hardly has time for other things. But we must not continue to conduct research on the principle of ‘producing data, publishing it and then forgetting it’!”
The entire journal can be accessed here.