The fast advances of technologies transform the way scientific research is performed. Data analysis and storage has moved from a paper-based, manual affair to an activity in which computers are vital. As a result, a vast amount of scientific data is being daily collected or produced by computational equipment. No single research organization has enough resources to collect everything; hence the data gathering and archiving processes are distributed and scattered at different places. Neither any single research group has the computational power to process all these data. Besides, collaboration among scientists from different institutions or disciplines is necessary in many occasions to apply a spectrum of methods and models to analyze and process this deluge of information, and the ability to access and reuse datasets, methods, models and results of existing scholarly publications generally ensures more effectiveness and better quality in the research that can be done.

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.

Projects

Currently we have two EU projects in execution in this area: Wf4Ever and ADMIRE STREP, Red de Excelencia PlanetData and the Marie Curie Initial Training Network SCALUS. As well, we also have a nacional project, myBigData,  in execution.

Previous projects in this area include OntoGrid.

Main results

The work done in this research area has mainly focused on the ontology-based integration of heterogeneous scientific and non-scientific data sources. Important steps towards this goal are the provision of SPARQL querying support over distributed SPARQL endpoints, with a testbed in the bioinformatics domain that makes use of Bio2RDF endpoints and some initial results in query planning over distributed data sources. Previous results, which are still being used in several semantic e-Science projects, are the S-OGSA architecture and its related technological infrastructure.

Some of the most relevant publications in this area are:

• Buil-Aranda, C., Corcho, O. (2010) Federating Queries to RDF repositories. Technical Report. Facultad de Informática (UPM), Madrid, Spain.
• Corcho, O., Alper, P., Kotsiopoulos, I., Missier, P., Bechhofer, S., Goble, C. (2006) An overview of S-OGSA: A Reference Semantic Grid Architecture. Journal of Web Semantics, 4 (2). pp. 102-115. ISSN 1570-8268

Members

This research area is led by Oscar Corcho, and the team is formed by the associate professor María Pérez Hernández, PhD students Carlos Buil, José Mora, Freddy Priyatna, Daniel Garijo Verdejo and Rafael González and by the MSc student Alex de León.

Recommended Reading

Some readings related with the e-Semantic Science:

• The Fourth Paradigm: Data-Intensive Scientific Discovery

• Riding the Wave: How Europe can gain from the rising tide of scientific data. Final report of the High Level Expert Group on Scientific Data. October 2010.

Job opportunities

There are currently no job offers or studentships available in this research area. For offers in other areas of the group, please check in our job opportunities section.

However, you may contact Oscar Corcho to check whether there are any potential open positions in the near future.