BioScholar is a Knowledge Engineering and Management system to support a single scientific worker (at the level of a graduate student or postdoctoral worker) to design, construct and manage a shared knowledge repository for a research group by curating and processing knowledge from the biomedical scientific literature. In particular, we use BioScholar as the platform for our work in the DARPA Big Mechanisms program.
The first sentence to appear in the journal `Trends in Neuroscience’ was “Even the most active neuroscientist spends more working hours in reading, reviewing, and writing scientific reports than on direct experimental effort” (Bloom 1978). Seventeen years later, the same author reaffirmed his previous claim and anticipated the development of knowledge management systems to address the problem (Bloom 1995). At this present time, a further eighteen years later, only a handful of neuroinformatics systems provide support for neuroscience knowledge supplied from the literature and none of them provide widespread, practical support beyond the process of simple citation management (such as Endnote, Mendeley, Zotero, Papers, etc.). The primary challenge for developers of these systems is the complexity and heterogeneity of experimental neuroscience mechanisms that directly incorporate detailed anatomical and physiological knowledge at the widespread spatial (molecular to behavioral) and temporal (electrochemical to evolutionary) scales. Neuroinformatics systems derived from the literature are typically one-off systems developed by neuroscientists to manage a specific domain specific challenge problem. The systems thus built tend to be (a) non-portable, (b) manually-curated, (c) lacking a detailed provenance trail and (d) small.
In this project, we build on extensive previous work in this field tol develop knowledge engineering support for graduate students for capturing the data of papers that they read. This will focus on supporting the activity of Journal Clubs within the graduate student population. The uptake of our software by users in the field will be determined by high-quality user feedback to guide the process of development directly and so our primary point of contact with students is crucial. Journal clubs provide a well-structured framework to (a) train students in good scholarly practice, (b) provide community-based support for the process of studying the literature and (c) teach critical evaluation of other people’s work. We see it as an ideal, pre-existing context for the careful introduction of a new system into students’ repertoire of knowledge management tools. Each meeting will involve a single student presenting an experimental paper of interest to the relevant graduate student community who we will work with to construct a populated knowledge engineering model for the paper they wish to present.
- Bloom, F.E. (1978). New solutions for science communication problems needed now. Trends in Neurosciences 1
- Bloom, F.E. (1995). Neuroscience-knowledge management: slow change so far. Trends Neurosci 18, 48–49.