How do we use space weather data effectively and optimally?

Space weather research community is consistently looking to improve the data landscape to better characterize the space weather. While it is true that there is general data sparseness to study space weather, the data that we do have available is vast, varied and usually continuous. At the moment, we have more continuous data available from both ground and space-based instruments than ever before, and it doesnt get used optimally. We tend to focus either on statistical analyses that tend to smooth smaller-scale variabilities or study explosive events like big solar storms really well. Since it is challenging to pay consistent attention to continuously generating data, this leads to missing interesting physics that takes place when we arent looking. To ensure a future where the continuously generating data allows us to characterize the space weather in useful time scales, we need to change our approach. The focus of this panel presentation will be on using some of the modern data science methods to mitigate this problem.