Oussama Annad
ABSTRACT
With the increasing volume of online geosciences data, geoscientists are now facing huge challenges in rapidly discovering and extracting valuable information from a large number of documents. Nowadays, it has become crucial to develop flexible and efficient tools that can help geoscientists to quickly navigate through unstructured texts to reveal hidden patterns and trends. This paper presents a workflow for the multidimensional analysis of geosciences literature. NLP techniques and ontologies are used to automatically identify and extract domain-specific concepts and entities buried in unstructured text. Based on these extracted data, we defined a multidimensional representation form of geosciences text documents which facilitates quantitative and exploratory analysis for knowledge discovery. To illustrate the potential of the proposed workflow, we implemented a pilot system that allows the user to perform multidimensional analysis on large collection of documents through interactive and user-friendly visualizations. We have analyzed the rare earth elements and carbonatites research topic as an example. The obtained visualizations show the usefulness and the efficiency of the proposed system for discovering knowledge and identifying potential research gaps.
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