The development of e-Science is a response to these emerging trends in scientific research. E-science was originally conceived as the application of computing to traditional science (mostly empirical, although in some cases theoretical as well) in order to empower scientists with their research in traditional activities such as modeling, simulation and prediction, among others. However, now e-Science can be considered to have gone further than that, and is even being considered as a third leg of the scientific method, together with the theoretical and empirical ones, by introducing a new environment in scientific research that has also led to new research methods that may potentially lead to better science.
Giving support to some of these new requirements arising from this new approach to Science requires in some cases the explicit definition of the meaning of data about these different domains. This is the role that explicit semantics and their associated technologies, models and methods can play, in the context of what it is known as Semantic e-Science. That is, while traditionally e-Science has mainly addressed issues of data and computation distribution, interoperation and high-performance in traditional and non-traditional scientific research tasks, the main focus of Semantic e-Science is on the application of explicit semantics over the e-Science infrastructure to drive more accurate information interpretation, more efficient scientific analyses, and better collaboration among scientists, among others.
Achieving computational experiment conservation and reproducibility in eScience is a multidisciplinary work in which several aspects have to be considered. Among them we focus on the conservation and reproduction of the execution environment of in-silico scientific experiments, trying to develop approaches for guaranteeing that an experiment that can be run today in a computational infrastructure could be run again in the future in an equivalent one. We explore how semantics can be applied to this end, developing ontologies for describing computational infrastructures and tools for reproducing them based on their descriptions. To this end we are also exploring the uses of virtualization techniques as a flexible and dynamic way for setting up and managing computational resources on demand.
Currently we are involved in a European project in this area, DrInventor, which started in January 2014, and we are actively participating in the W3C Community Group on Research Objects for Scholarly Communication, and maintaining the researchobject.org site.
The work done in this research area has mainly focused on:
This research area is led by Oscar Corcho, and the team is also composed of María Pérez Hernández, the postdoc Rafael González, the PhD students Daniel Garijo, Idafen Santana and Olga Giraldo, and the MSc student Carlos Badenes.
Some readings related with the e-Semantic Science:
There are currently no job offers or studentships available in this research area. For offers in other areas of the group, please check our job opportunities section. However, you may contact Oscar Corcho to check whether there are any potential open positions in the near future.
Created under Creative Commons License - 2015 OEG.