Ontologies for Describing the Context of Scientific Experiment Processes

Abstract

The re-usability and repeatability of e-Science experiments is widely understood as a requirement of validating and reusing previous work in data-intensive domains. Experiments are, however, often complex chains of processing, involving a number of data sources, computing infrastructure, software tools, or external and third-party services, rendering repeatability a challenging task. Another important aspect of many experiments is in the social and organisational dimension - very often, knowledge on how experiments are performed is tacit and remains with the researcher, and the collaborative and distributed aspects especially of larger collaborative experiments adds to this challenge. Therefore, a number of approaches have tackled this issue from various angles - initiatives for data sharing, code versioning and publishing as open source, the use of workflow engines to formalise the steps taken in an experiment, to ways to describe the complex environment an experiment is executed in, e.g. via Research Objects. In this paper, we present a model that has a specific focus on the technical infrastructure that is the basis of the research experiment. We demonstrate how this model can be applied to describe e-Science experiments, and align and compare it to Research Objects.

The re-usability and repeatability of e-Science experiments is widely understood as a requirement of validating and reusing previous work in data-intensive domains. Experiments are, however, often complex chains of processing, involving a number of data sources, computing infrastructure, software tools, or external and third-party services, rendering repeatability a challenging task. Another important aspect of many experiments is in the social and organisational dimension - very often, knowledge on how experiments are performed is tacit and remains with the researcher, and the collaborative and distributed aspects especially of larger collaborative experiments adds to this challenge. Therefore, a number of approaches have tackled this issue from various angles - initiatives for data sharing, code versioning and publishing as open source, the use of workflow engines to formalise the steps taken in an experiment, to ways to describe the complex environment an experiment is executed in, e.g. via Research Objects. In this paper, we present a model that has a specific focus on the technical infrastructure that is the basis of the research experiment. We demonstrate how this model can be applied to describe e-Science experiments, and align and compare it to Research Objects.