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However, many of these approaches are either specifically targeted at <jats:italic>open-domain<\/jats:italic> question answering using DBpedia, or require <jats:italic>large training datasets<\/jats:italic> to translate a natural language question to SPARQL in order to query the knowledge graph. Hence, these approaches often cannot be applied directly to complex <jats:italic>scientific datasets<\/jats:italic> where no prior training data is available. In this paper, we focus on the challenges of natural language processing over knowledge graphs of scientific datasets. In particular, we introduce Bio-SODA, a natural language processing engine that does not require training data in the form of question-answer pairs for generating SPARQL queries. Bio-SODA uses a generic graph-based approach for translating user questions to a ranked list of SPARQL candidate queries. Furthermore, Bio-SODA uses a novel ranking algorithm that includes node centrality as a measure of relevance for selecting the best SPARQL candidate query. Our experiments with real-world datasets across several scientific domains, including the official <jats:italic>bioinformatics<\/jats:italic> Question Answering over Linked Data (QALD) challenge, as well as the CORDIS dataset of European projects, show that Bio-SODA outperforms publicly available KGQA systems by an F1-score of least 20% and by an even higher factor on more complex bioinformatics datasets. Finally, we introduce Bio-SODA UX, a graphical user interface designed to assist users in the exploration of large knowledge graphs and in dynamically disambiguating natural language questions that target the data available in these graphs.<\/jats:p>","DOI":"10.1007\/s10619-022-07414-w","type":"journal-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T13:03:26Z","timestamp":1657976606000},"page":"409-440","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Bio-SODA UX: enabling natural language question answering over knowledge graphs with user disambiguation"],"prefix":"10.1007","volume":"40","author":[{"given":"Ana Claudia","family":"Sima","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tarcisio","family":"Mendes de Farias","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria","family":"Anisimova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christophe","family":"Dessimoz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marc","family":"Robinson-Rechavi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erich","family":"Zbinden","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kurt","family":"Stockinger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,16]]},"reference":[{"key":"7414_CR1","first-page":"1","volume":"2018","author":"D Diefenbach","year":"2018","unstructured":"Diefenbach, D., Both, A., Singh, K., Maret, P.: Towards a question answering system over the semantic web. 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