Finding data, knowledge, and answers on the semantic Web

2005

Swoogle helps software agents and knowledge engineers find Semantic Web knowledge encoded in RDF and OWL documents on the Web. Navigating such a Semantic Web on the Web is difficult due to the paucity of explicit hyperlinks beyond the namespaces in URIrefs and the few inter-document links like rdfs: seeAlso and owl: imports.

The 15th International FLAIRS Conference, …, 2002

The machine understandable semantic of information, achieved by using an RDF(S) structure and common-shared vocabularies (ontologies) is the big step in enabling the machine-agent interoperability on the Web. Machine agents can crawl annotated web pages, search for ...

The amount of biological data available electronically is increasing at a rapid rate; for instance, over 16.500 specimens are available today in the National Institute for Amazonian Research (INPA) collections. However, this data is not semantically categorized and stored and thus is difficult to search. To tackle this problem, we present a semantic search architecture, implemented using state of the art semantic web tools, and test it on a set of representative data about biodiversity from INPA. This paper describes how the mechanism of mapping is designed so that the semantic search can find information, based on ontologies. We show a series of SPARQL queries and explain how the mapping mechanism works. Our experiments, using a prototype of the proposed architecture, showed that the prototype had better precision and recall then traditional keyword based search engines.

2005

Since its emergence in the early 1990s, the World Wide Web has rapidly evolved into a global information space of incomparable size. Keyword-based search engines such as GoogleTM index as many webpages as possible for the benefit of human users. Sophisticated as such search engines have become, they are still often unable to bridge the gap between HTML and the human. Tim Berners-Lee envisions the Semantic Web as the web of machineinterpretable information that complements the existing World Wide Web, providing an automated means for machines to truly traverse the Web on behalf of their human counterparts. A cornerstone application of the emerging Semantic Web is the search engine that is capable of tying components of the Semantic Web together into a traversable landscape. This paper describes both an architecture for and a prototype of a Semantic Web Search Engine (SWSE) using Jena that provides more sophisticated searching with more exacting results. To compare keyword-based searc...

Proceedings of the AAAI Fall Symposium on the Semantic Web for Collaborative Knowledge Acquisition, 2006

We describe our on-going work in using the semantic web in support of ecological informatics, and demonstrate a distributed platform for constructing end-to-end use cases. Specifically, we describe ELVIS (the Ecosystem Location Visualization and Information System), a suite of tools for constructing food webs for a given location, and Triple Shop, a SPARQL query interface which allows scientists to semi-automatically construct distributed datasets relevant to the queries they want to ask. ELVIS functionality is exposed as a collection of web services, and all input and output data is expressed in OWL, thereby enabling its integration with Triple Shop and other semantic web resources.

Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018

The Semantic Web promotes common data formats and exchange protocols on the web towards better interoperability among systems and machines. Although Semantic Web technologies are being used to semantically annotate data and resources for easier reuse, the ad hoc discovery of these data sources remains an open issue. Popular Semantic Web endpoint repositories such as SPARQLES, Linking Open Data Project (LOD Cloud), and LODStats do not include recently published datasets and are not updated frequently by the publishers. Hence, there is a need for a web-based dynamic search engine that discovers these endpoints and datasets at frequent intervals. To address this need, a novel web meta-crawling method is proposed for discovering Linked Data sources on the Web. We implemented the method in a prototype system named SPARQL Endpoints Discovery (SpEnD). In this paper, we describe the design and implementation of SpEnD, together with an analysis and evaluation of its operation, in comparison to the aforementioned static endpoint repositories in terms of time performance, availability, and size. Findings indicate that SpEnD outperforms existing Linked Data resource discovery methods. CCS CONCEPTS • Information systems → Web searching and information discovery;

2006

Web search engines like Google have made people “smarter” by providing ready access to the world's knowledge whenever they need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such information more accessible to computer programs by encoding it on the Web in machine understandable form.

Proceedings of the 3rd XTech …, 2008

Current web search engines return links to documents for user-specified keywords queries. Users have to then manually trawl through lists of links and glean the required information from documents. In contrast, semantic search engines allow more expressive queries over information integrated from multiple sources, and return specific information about entities, for example people, locations, news items. An entity-centric data model furthermore permits powerful query and browsing techniques. In this paper, we report on our experiences in ...

2011

In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data–loosely also known as Linked Data–which implies unique challenges for the system design, architecture, algorithms, implementation and user interface.

2002

The Resource Definition Framework (RDF) is designed to support agent communication on the Web, but it is also suitable as a framework for modeling and storing personal information. Haystack is a personalized information repository that employs RDF in this manner. This flexible semistructured data model is appealing for several reasons. First, RDF supports ontologies created by the user and tailored to the user's needs. At the same time, system ontologies can be specified and evolved to support a variety of high-level functionalities such as flexible organization schemes, semantic querying, and collaboration. In addition, we show that RDF can be used to engineer a component architecture that gives rise to a semantically rich and uniform user interface. We demonstrate that by aggregating various types of users' data together in a homogeneous representation, we create opportunities for agents to make more informed deductions in automating tasks for users. Finally, we discuss the implementation of an RDF information store and a programming language specifically suited for manipulating RDF.