This article assesses a key aspect of data sharing that has the potential to accelerate the progress and impact of medicinal chemistry. To achieve this the community needs to increase the outward flow of experimental results locked-up in millions of published PDFs into structured open databases that explicitly capture the connectivity between structures, documents and bioactivity results. But isn't there enough of this out there already? This can be answered in two parts. The first is that a conservative estimate of the capture backlog is that there is at least two-fold more data still entombed in PDFs not currently indexed in database records. The second part is the imperative to enable open science data mining at all scales. This applies not only to individual documents (small data) but scaling up to all papers and patents (big-data). The potential of the latter is huge, especially since Artificial Intelligence (AI) is being increasingly applied to knowledge distillation. This report will outline the principles of connectivity capture, sources, progress, impediments and prospects for their amelioration.