LabTrove

The Smart Research Framework (SRF) – LabTrove what the software enables and facilitates

Building on the insight gained from our e-Science research [e.g. CombeChem, eBank, eCrystals, R4L, Smart Tea & oreChem], we have extended the model of a digital infrastructure for supporting research (repositories, LIMS, pervasive computing & basic RDF underpinning) to incorporate the equally familiar social networking paradigm of the online blog. The needs of the researcher are however different from those of the prototypical members of the Blogosphere – a data centric system with control over visibility and sharing are essential.

The difference between our system and other approaches is that the data is associated with the proposed scientific endeavour prior to or at the point of creation rather than by annotating the data with commentary after the experiment has taken place. This means that scientists and their peers can recreate and adapt the experiment repeatedlyhaving already automated the processes and instrument settings. Crucially this approach also provides the potential for a data management and curation framework applicable for all disciplines and scalable from the research group to entire communities. The SRF supports and encourages a tight integration between the experimental process and the data generated, linking between these to provide the basis for provenance, reproducibility and re-use.

These principles formed the origin of the LabTrove system. The LabTrove application enables researchers to share their experimental plans, thoughts, observations and achievements with the wider online community in a secure, semantically rich and extensible manner. The SRF encompasses this software and other associated repository systems for LIMS and environmental (eg sensor) data and can also be coupled with pervasive and non invasive approaches to capturing this data. The SRF enables scientists to follow a method much closer to the original concept of experimental science in terms of declaring a hypothesis, recording data and analysing results. Furthermore, scientists will no longer have to print out data results to insert into conventional lab books; instead, results will be logically associated with the experiment and therefore accessible as required. Thus it is possible to pivot the material and view the data in a chronological diary form for example or data-centrically in terms of the scientific argument.