Querying and Visualisation of Semantic Data

Abstract

Semantic technologies can describe data, map, and link distributeddatasets for people and machines. Over the years, many semanticdata repositories have been made available on the web. However, thishas created new challenges regarding exploiting these resources effi-ciently. Usually, querying services use formal query languages requiringknowledge beyond the standard user’s expertise, which is critical inadopting semantic solutions. Several proposals to overcome this dif-ficulty have suggested using question-answering systems that provideuser-friendly interfaces allowing natural language inputs. On the otherhand, processing and integrating the results in the usual tabular formsdoes not help to understand the retrieved information better.This thesis proposes solutions and methods to facilitate access and re-trieval of information in the context of semantic data repositories. Afirst contribution concerns the proposal of a strategy for creating andpublishing semantic data for different application domains, emphasis-ing biomedical data. A second contribution proposes a new method toaccess semantic data using natural language as input. Finally, severalpossibilities for visualising semantic data to facilitate their understand-ing and exploitation are analysed. The proposals were validated con-sidering use cases in the biomedical domain using data and metadatafrom patients with Alzheimer’s and patients with Huntington’s disease