Use of conceptual relations for semantic integration of scientific publications and research data

The context of this research is the 4th Scientific Paradigm, better known as e-Science. E-Science is characterized by the intensive use of computer networks, distributed digital repositories, and the reuse of research data. This study argues that a scientific publication can be enriched and be closer to the new forms of modern scientific knowledge generation if it is configured according to a model that, through semantic relations, links research data and datasets to conventional publication. Such a publication model that integrates scientific data and search information with results through semantic relations is called an enhanced publication. This paper will present a methodology used for the semantic integration of data and publications made available in a distributed environment. This approach is based on the use of conceptual relations to establish links between distributed digital objects. The results are a taxonomy of relations and an interface model to be computationally implemented. 1. Context This research is developed within the context of an emerging scientific paradigm, known as e-Science or the 4th Scientific Paradigm. This new way of doing science is characterized by the intensive use of computer networks, distributed digital repositories, and the intensive generation and reuse of research data. The informational environment that has arisen as a consequence of these changes has had a significant impact on patterns of scientific communication, especially in terms of the means of communicating and disseminating research results. This work is the result of a doctoral thesis research project which is based on two premises: the first raises the need for a scientific publication model that can express and reflect the new pattern of generating scientific knowledge, rich in data, which can be integrated into publications; the second proposes that this can be accomplished according to the technological possibilities and patterns derived from theories of knowledge organization. These two premises embody the formulation of a hypothesis which argues that a scientific publication can be enriched and be closer to the new forms of modern scientific knowledge generation if it is configured according to a model that, through semantic relations, links research data and datasets to conventional publication. Such a publication model that integrates data and search information with results through semantic relations is called an enhanced publication.