Swoogle is a crawler-based indexing and retrieval system designed for the Semantic Web, specifically for Web documents in RDF or OWL. It extracts metadata from discovered documents and computes relations between them. The system also indexes these documents using an information retrieval system that can use character N-Grams or URIFreqs as keywords to find relevant documents and compute their similarity. One of its key features is the computation of ranks, which measure the importance of Semantic Web documents. The introduction highlights the need for a specialized search engine for Semantic Web documents, particularly for ontologies, instance data, and characterizing the Semantic Web. Swoogle aims to facilitate these activities by providing a prototype search engine that can find appropriate ontologies, instance data, and provide insights into the structure of the Semantic Web. The architecture of Swoogle consists of four main components: SWD discovery, metadata creation, data analysis, and interface. The SWD discovery component uses heuristics to find potential Semantic Web Documents (SWDs) on the web, while the metadata creation component caches and generates metadata about SWDs. The data analysis component derives analytical reports, and the interface component provides a user-friendly web interface. The paper discusses the challenges of finding SWDs, the collection of metadata, and the ranking of SWDs using a rational random surfing model. It also describes the indexing and retrieval of SWDs using N-Grams or URIFrels as terms. The current status of Swoogle includes the ability to query with keywords and advanced constraints, and it has indexed about 11,000 SWDs. The conclusions emphasize the need for powerful search and indexing systems for the Semantic Web, and the potential of Swoogle to support researchers and software agents in their work. The system has discovered and analyzed over 11,000 Semantic Web documents, and a second version is being developed to handle more metadata and support millions of documents.Swoogle is a crawler-based indexing and retrieval system designed for the Semantic Web, specifically for Web documents in RDF or OWL. It extracts metadata from discovered documents and computes relations between them. The system also indexes these documents using an information retrieval system that can use character N-Grams or URIFreqs as keywords to find relevant documents and compute their similarity. One of its key features is the computation of ranks, which measure the importance of Semantic Web documents. The introduction highlights the need for a specialized search engine for Semantic Web documents, particularly for ontologies, instance data, and characterizing the Semantic Web. Swoogle aims to facilitate these activities by providing a prototype search engine that can find appropriate ontologies, instance data, and provide insights into the structure of the Semantic Web. The architecture of Swoogle consists of four main components: SWD discovery, metadata creation, data analysis, and interface. The SWD discovery component uses heuristics to find potential Semantic Web Documents (SWDs) on the web, while the metadata creation component caches and generates metadata about SWDs. The data analysis component derives analytical reports, and the interface component provides a user-friendly web interface. The paper discusses the challenges of finding SWDs, the collection of metadata, and the ranking of SWDs using a rational random surfing model. It also describes the indexing and retrieval of SWDs using N-Grams or URIFrels as terms. The current status of Swoogle includes the ability to query with keywords and advanced constraints, and it has indexed about 11,000 SWDs. The conclusions emphasize the need for powerful search and indexing systems for the Semantic Web, and the potential of Swoogle to support researchers and software agents in their work. The system has discovered and analyzed over 11,000 Semantic Web documents, and a second version is being developed to handle more metadata and support millions of documents.