Federated Information Retrieval in Cross-Domain Information Systems

In humanities research projects, scholars examine written artefacts, such as manuscripts, for various purposes based on factors like language, textual content, provenance, codicological aspects, and other characteristics. While humanities scholars can make statements about different aspects of self-contained artefacts based on their expertise, there are instances where the statements are made without numerical verification due to limited research data that are available within a project. If a variable, e.g. the size of a book, is requested, classic search engines provide similar but not precise answers. Our thesis proposes that by combining various cross-domain information sources as a federated database system, these missing variables can be supplemented, thereby validating research questions in the humanities. The article proposes a cross-domain information system that enables efficient federated search for comprehensive research in the humanities. The system combines diverse information sources and provides efficient search capabilities by demonstrating an efficient data matching approach called indexing. This article also presents how users can define their queries in natural language by integrating GPT4all to generate SQL queries from natural language queries. The achieved result is a cross-domain information system that facilitates comprehensive research in the humanities by combining diverse information sources and providing efficient federated information retrieval.