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Description: Semantic technologies can describe data, map, and link distributed datasets for people and machines. Over the years, many semantic data repositories have been made available on the web. However, this has created new challenges regarding exploiting these resources efficiently. Usually, querying services use formal query languages requiring knowledge beyond the standard user's expertise, which is critical in adopting semantic solutions. Several proposals to overcome this difficulty have suggested using question-answering systems that provide user-friendly interfaces allowing natural language inputs. On the other hand, processing and integrating the results in the usual tabular forms does not help to understand the retrieved information better. This thesis proposes solutions and methods to facilitate access and retrieval of information in the context of semantic data repositories. A first contribution concerns the proposal of a strategy for creating and publishing semantic data for different application domains, emphasising biomedical data. A second contribution proposes a new method to access semantic data using natural language as input. Finally, several possibilities for visualising semantic data to facilitate their understanding and exploitation are analysed. The proposals were validated considering use cases in the biomedical domain using data and metadata from patients with Alzheimer's and patients with Huntington's disease.