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In the INAS project ([https://inas-argumentation.github.io/ https://inas-argumentation.github.io/]; [https://doi.org/10.3897/rio.8.e80457 Heger et al. 2022]), which is part of the [https://spp-ratio.de/ Robust Argumentation Machines] program by the DFG, we investigate basic questions related to knowledge synthesis in invasion biology. In an interdisciplinary team, we combine methods from natural language processing, knowledge representation and the semantic web to explore how to | In the INAS project ([https://inas-argumentation.github.io/ https://inas-argumentation.github.io/]; [https://doi.org/10.3897/rio.8.e80457 Heger et al. 2022]), which is part of the [https://spp-ratio.de/ Robust Argumentation Machines] program by the DFG, we investigate basic questions related to knowledge synthesis in invasion biology. In an interdisciplinary team, we combine methods from natural language processing, knowledge representation and the semantic web to explore how to: (i) represent concrete and more abstract knowledge on hypotheses and their underlying concepts; (ii) automatically compute semantic relations between hypotheses made in scientific publications, and between hypotheses and datasets; and (iii) interactively support users in developing their own hypothesis based on these resources. | ||
(i) represent concrete and more abstract knowledge on hypotheses and their underlying concepts; (ii) automatically compute semantic relations between hypotheses made in scientific publications, and between hypotheses and datasets; and (iii) interactively support users in developing their own hypothesis based on these resources. | |||
Revision as of 15:11, 24 June 2024
In the INAS project (https://inas-argumentation.github.io/; Heger et al. 2022), which is part of the Robust Argumentation Machines program by the DFG, we investigate basic questions related to knowledge synthesis in invasion biology. In an interdisciplinary team, we combine methods from natural language processing, knowledge representation and the semantic web to explore how to: (i) represent concrete and more abstract knowledge on hypotheses and their underlying concepts; (ii) automatically compute semantic relations between hypotheses made in scientific publications, and between hypotheses and datasets; and (iii) interactively support users in developing their own hypothesis based on these resources.