Theme C: Medical information systems and databases - results and future work

International audienceThis paper presents the activities of the theme C “medical information systems and databases” in the GDR Stic Santé. Six one-day workshops have been organized during the period 2011–2012. They were devoted to 1) sharing anatomical and physiological object models for simulation of clinical medical images, 2) advantages and limitations of datawarehouse for biological data, 3) medical information engineering, 4) systems for sharing medical images for research, 5) knowledge engineering for semantic interoperability in e-health applications, and 6) using context in health. In the future, our activities will continue with a specific interest on information systems for translational medicine and the role of electronic healthcare reports in decision-making. Workshops with other research groups will be organized in particular with the e-health research group

Proceedings of The Tenth International Workshop on Ontology Matching (OM-2015)

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Methods for Matching of Linked Open Social Science Data

In recent years, the concept of Linked Open Data (LOD), has gained popularity and acceptance across various communities and domains. Science politics and organizations claim that the potential of semantic technologies and data exposed in this manner may support and enhance research processes and infrastructures providing research information and services. In this thesis, we investigate whether these expectations can be met in the domain of the social sciences. In particular, we analyse and develop methods for matching social scientific data that is published as Linked Data, which we introduce as Linked Open Social Science Data. Based on expert interviews and a prototype application, we investigate the current consumption of LOD in the social sciences and its requirements. Following these insights, we first focus on the complete publication of Linked Open Social Science Data by extending and developing domain-specific ontologies for representing research communities, research data and thesauri. In the second part, methods for matching Linked Open Social Science Data are developed that address particular patterns and characteristics of the data typically used in social research. The results of this work contribute towards enabling a meaningful application of Linked Data in a scientific domain

Ontology Matching: OM-2018: Proceedings of the ISWC Workshop

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