In semantic annotation, semantic concepts are linked to natural language. Semantic annotation helps in boosting the ability to search and access resources and can be used in information retrieval systems to augment the queries from the user. In the research described in this paper, we aimed to identify ontological concepts in scientific text contained in spreadsheets. We developed a tool that can handle various types of spreadsheets. Furthermore, we used the NCBO Annotator API provided by BioPortal to enhance the semantic annotation functionality to cover spreadsheet data. Table2Annotation has strengths in certain criteria such as speed, error handling, and complex concept matching.

In semantic annotation, semantic concepts are linked to natural language. Semantic annotation helps in boosting the ability to search and access resources and can be used in information retrieval systems to augment the queries from the user. In the research described in this paper, we aimed to identify ontological concepts in scientific text contained in spreadsheets. We developed a tool that can handle various types of spreadsheets. Furthermore, we used the NCBO Annotator API provided by BioPortal to enhance the semantic annotation functionality to cover spreadsheet data. Table2Annotation has strengths in certain criteria such as speed, error handling, and complex concept matching.