By 2007, our infrastructure was in place and was ready to be used by undergraduate students as well as researchers. A typical presentation of the ELN to the student or researcher is shown in Figure illustrating from left to right what might be called the flow of the data pipeline and was starting to be used for student research projects. One student's experiences were included in the article describing the operation of the ELN. The final project outputs in the form of PIDs for the computational research data were incorporated into the article describing the actual science (Figure ). By the time this particular student project was undertaken, we had added the capability of publishing from the ELN not only to our SPECTRa repository but also to the new external service started in 2012 by Figshare 10 (Figure ).The system was also used for laboratory experiments in which bench chemistry was merged with computational modelling, the latter including e.g. predictive calculations of C spectra of molecules synthesized by the students and prediction of expected optical rotations for molecules made by enantioselective reactions such as Jacobsen and Shi epoxidations. For some of the more computationally intensive models which would take more time than allocated for the laboratory, we stored pre-computed results in a repository for students to Reuse and derive conclusions from (Figure ). In 2012, we extended the use of Handles as data repository identifiers to the now more familiar DOI (digital object identifier), in this instance issued by the DataCite registration authority. Such DOIs until then had been associated exclusively with journal articles and the CrossRef registry, but their use to identify data was now being extended to join the more general identifier or PID ecosystem. This allowed a larger and more flexible metadata record designed specifically to describe data to be associated with each item, as defined by the DataCite schema. 12 This meant that the metadata could Found or searched using the globally aggregated and indexed DataCite metadata store. These DOIs were included by students in their final laboratory report as a means of facilitating Access to their data to the assessor of their report. It also enabled the data to be cited in any resulting journal publication (Figure ). Another unique feature for that time was the inclusion of calculation checkpoint files as part of the fileset associated with a quantum calculation (Figure ), which in turn allowed facile (re)generation of properties associated with the calculation such as e.g. non-covalent interaction surfaces (as seen in Figure ). The strategy here was to allow the data retrieved from a repository to be repurposed or Interoperated. Here and in preceding paragraphs, we have already referred to attributes such as Finding, Accessing and Reusing and these became collectively known as FAIR data in 2015. FAIR data in turn is increasingly required by e.g. funders and recently journals, making it nowadays an essential component of a taught laboratory in an experimental science such as chemistry.