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In this article, we investigate our early attempts at building an ontology describing rehabilitation therapies following brain injury. These therapies are wide-ranging, involving interventions of many different kinds. As a result, these therapies are hard to describe. As well as restricting actual practice, this is also a major impediment to evidence-based medicine as it is hard to meaningfully compare two treatment plans. Ontology development requires significant effort from both ontologists and domain experts. Knowledge elicited from domain experts forms the scope of the ontology. The process of knowledge elicitation is expensive, consumes experts' time and might have biases depending on the selection of the experts. Various methodologies and techniques exist for enabling this knowledge elicitation, including community groups and open development practices. A related problem is that of defining scope. By defining the scope, we can decide whether a concept (i.e. term) should be represented in the ontology. This is the opposite of knowledge elicitation, in the sense that it defines what should not be in the ontology. This can be addressed by pre-defining a set of competency questions. These approaches are, however, expensive and time-consuming. Here, we describe our work toward an alternative approach, bootstrapping the ontology from an initially small corpus of literature that will define the scope of the ontology, expanding this to a set covering the domain, then using information extraction to define an initial terminology to provide the basis and the competencies for the ontology. Here, we discuss four approaches to building a suitable corpus that is both sufficiently covering and precise., Comment: Accepted at the International Conference for Biomedical Ontologies 2017(ICBO 2017), 4 pages, 3 figures, 1 table

Cardiac experimental electrophysiology is in need of a well-defined Minimum Information Standard for recording, annotating, and reporting experimental data. As a step towards establishing this, we present a draft standard, called Minimum Information about a Cardiac Electrophysiology Experiment (MICEE). The ultimate goal is to develop a useful tool for cardiac electrophysiologists which facilitates and improves dissemination of the minimum information necessary for reproduction of cardiac electrophysiology research, allowing for easier comparison and utilisation of findings by others. It is hoped that this will enhance the integration of individual results into experimental, computational, and conceptual models. In its present form, this draft is intended for assessment and development by the research community. We invite the reader to join this effort, and, if deemed productive, implement the Minimum Information about a Cardiac Electrophysiology Experiment standard in their own work.

One of the most pervasive classes of services needed to support e-Science applications are those responsible for the discovery of resources. We have developed a solution to the problem of service discovery in a Semantic Web/Grid setting. We do this in the context of bioinformatics, which is the use of computational and mathematical techniques to store, manage, and analyse the data from molecular biology in order to answer questions about biological phenomena. Our specific application is myGrid (http://www.mygrid.org.uk) that is developing open source, service-based middleware upon which bioinformatics applications can be built. myGrid is specifically targeted at developing open source high-level service Grid middleware for bioinformatics.