BioASQ pushes for a solution to the information access problem of biomedical experts by setting up a challenge on biomedical semantic indexing and question answering (QA).
Biomedical knowledge is dispersed in hundreds of heterogeneous knowledge sources and databases; many of them are connected on the Linked Open Data cloud. Biomedical experts, on the other hand, are in constant need of highly specialized information, which they cannot easily obtain. To address their needs, an information system needs to "understand'' the data and answer efficiently the experts' questions. Often, however, experts need responses that cannot be answered by a single information source. To integrate information from disparate sources, semantic indexing of the vast quantities of information is needed to bridge the experts' needs with the available data sources.
Semantic indexing is currently achieved by manual annotation, and does not scale up. Automating this process requires large-scale classification of data into hierarchically organized concepts. QA methods capable of "interpreting'' questions in terms of the same concepts are also needed. BioASQ pushes towards improved biomedical semantic indexing and QA via ambitious, yet realistic challenge tasks. The challenge runs in two stages, designed to
- adapt traditional semantic indexing and QA methods to the needs of biomedical experts, and
- collect feedback and improve the experimental setting itself.
A large computational infrastructure, already available to the consortium, is used to evaluate competing systems. Evaluation measures have been established before the challenge. Biomedical experts participate in the consortium, both as partners and through a supporting network of third parties.