Queryng and Visualization of Semantic Data

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Easing the questioning of semantic biomedical data

Publication . Pereira, Arnaldo; Lopes, Rui Pedro; Oliveira, José Luís

Researchers have been using semantic technologies as essential tools to structure knowledge. This is particularly relevant in the biomedical domain, where large dataset are continuously generated. Semantic technologies offer the ability to describe data and to map and linking distributed repositories, creating a network where the searching interface is a single entry point. However, the increasing number of semantic data repositories that are publicly available is creating new challenges related to its exploration. Despite being human and machine-readable, these technologies are much more challenging for end-users. Querying services usually require mastering formal languages and that knowledge is beyond the typical user's expertise, being a critical issue in adopting semantic web information systems. In particular, the questioning of biomedical data presents specific challenges for which there are still no mature proposals for production environments. This paper presents a solution to query biomedical semantic databases using natural language. The system is at the intersection between semantic parsing and the use of templates. It makes it possible to extract information in a friendly way for users who are not experts in semantic queries.

2021Conference paper

Open access

Discovery of biomedical databases through semantic questioning

Publication . Pereira, Arnaldo; Almeida, João Rafael; Lopes, Rui Pedro; Pazos, Alejandro; Oliveira, José Luís

Many clinical studies are greatly dependent on an efficient identification of relevant datasets. This selection can be performed in existing health data catalogues, by searching for available metadata. The search process can be optimised through questioning-answering interfaces, to help researchers explore the available data present. However, when searching the distinct catalogues the lack of metadata harmonisation imposes a few bottlenecks. This paper presents a methodology to allow semantic search over several biomedical database catalogues, by extracting the information using a shared domain knowledge. The resulting pipeline allows the converted data to be published as FAIR endpoints, and it provides an end-user interface that accepts natural language questions.

2022Conference paper

Open access