Using ontology in query answering systems: Scenarios, requirements and challenges

Equipped with the ultimate query answering system, computers would finally be in a position to address all our information needs in a natural way. In this paper, we describe how Language and Computing nv (L&C), a developer of ontology-based natural language understanding systems for the healthcare domain, is working towards the ultimate Question Answering (QA) System for healthcare workers. L&C’s company strategy in this area is to design in a step-by-step fashion the essential components of such a system, each component being designed to solve some one part of the total problem and at the same time reflect well-defined needs on the prat of our customers. We compare our strategy with the research roadmap proposed by the Question Answering Committee of the National Institute of Standards and Technology (NIST), paying special attention to the role of ontology

Towards structured sharing of raw and derived neuroimaging data across existing resources

Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery

Applying Semantic Web Technologies to Medieval Manuscript Research

Medieval manuscript research is a complex, fragmented, multilingual field of knowledge, which is difficult to navigate, analyse and exploit. Though printed sources are still of great importance and value to researchers, there are now many services on the Web, some commercial and many in the public domain. At present, these services have to be consulted separately and individually. They employ a range of different descriptive standards and vocabularies, and use a variety of technologies to make their information available on the Web. This chapter proposes a new approach to organizing the international collaborative infrastructure for interlinking knowledge and research about medieval European manuscripts, based on technologies associated with the Semantic Web and the Linked Data movement. This collaborative infrastructure will be an open space on the Web where information about medieval manuscripts can be shared, stored, exchanged and updated for research purposes. It will be possible to ask large-scale research questions across the virtual global manuscript collection, in a quicker and more effective way than has ever been feasible in the past. The proposed infrastructure will focus on building links between data and will provide the basis for new kinds of services which exploit these data. It will not aim to impose a single metadata standard on existing manuscript services, but will build on existing databases and vocabularies. The article describes the architecture, services and data which will comprise this infrastructure, and discusses strategies for making th challenging and exciting goal a reality