Language technologies and the evolution of the semantic web

The availability of huge amounts of semantic markup on the Web promises to enable a quantum leap in the level of support available to Web users for locating, aggregating, sharing, interpreting and customizing information. While we cannot claim that a large scale Semantic Web already exists, a number of applications have been produced, which generate and exploit semantic markup, to provide advanced search and querying functionalities, and to allow the visualization and management of heterogeneous, distributed data. While these tools provide evidence of the feasibility and tremendous potential value of the enterprise, they all suffer from major limitations, to do primarily with the limited degree of scale and heterogeneity of the semantic data they use. Nevertheless, we argue that we are at a key point in the brief history of the Semantic Web and that the very latest demonstrators already give us a glimpse of what future applications will look like. In this paper, we describe the already visible effects of these changes by analyzing the evolution of Semantic Web tools from smart databases towards applications that harness collective intelligence. We also point out that language technology plays an important role in making this evolution sustainable and we highlight the need for improved support, especially in the area of large-scale linguistic resources

Using Semantic Web technologies in the development of data warehouses: A systematic mapping

The exploration and use of Semantic Web technologies have attracted considerable attention from researchers examining data warehouse (DW) development. However, the impact of this research and the maturity level of its results are still unclear. The objective of this study is to examine recently published research articles that take into account the use of Semantic Web technologies in the DW arena with the intention of summarizing their results, classifying their contributions to the field according to publication type, evaluating the maturity level of the results, and identifying future research challenges. Three main conclusions were derived from this study: (a) there is a major technological gap that inhibits the wide adoption of Semantic Web technologies in the business domain;(b) there is limited evidence that the results of the analyzed studies are applicable and transferable to industrial use; and (c) interest in researching the relationship between DWs and Semantic Web has decreased because new paradigms, such as linked open data, have attracted the interest of researchers.This study was supported by the Universidad de La Frontera, Chile, PROY. DI15-0020. Universidad de la Frontera, Chile, Grant Numbers: DI15-0020 and DI17-0043

Linked Data - the story so far

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward

05371 Abstracts Collection -- Principles and Practices of Semantic Web Reasoning

From 11.09.05 to 16.09.05, the Dagstuhl Seminar 05371 ``Principles and Practices of Semantic Web Reasoning\u27\u27 % generate automaticall was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

The Semantic Web Framework: a component-based framework for the development of Semantic Web applications

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Spatial groundings for meaningful symbols

The increasing availability of ontologies raises the need to establish relationships and make inferences across heterogeneous knowledge models. The approach proposed and supported by knowledge representation standards consists in establishing formal symbolic descriptions of a conceptualisation, which, it has been argued, lack grounding and are not expressive enough to allow to identify relations across separate ontologies. Ontology mapping approaches address this issue by exploiting structural or linguistic similarities between symbolic entities, which is costly, error-prone, and in most cases lack cognitive soundness. We argue that knowledge representation paradigms should have a better support for similarity and propose two distinct approaches to achieve it. We first present a representational approach which allows to ground symbolic ontologies by using Conceptual Spaces (CS), allowing for automated computation of similarities between instances across ontologies. An alternative approach is presented, which considers symbolic entities as contextual interpretations of processes in spacetime or Differences. By becoming a process of interpretation, symbols acquire the same status as other processes in the world and can be described (tagged) as well, which allows the bottom-up production of meaning

Querying Semantic Web Resources Using TRIPLE Views

Resources on the Semantic Web are described by metadata based on some formal or informal ontology. It is a common situation that casual users are not familiar with a domain ontology in detail. This makes it difficult for such users (or their user tools) to formulate queries to find the relevant resources. Users consider the resources in their specific context, so the most straightforward solution is to formulate queries in an ontology that corresponds to a user-specific view. We present an approach based on multiple views expressed in ontologies simpler than the domain ontology. This allows users to query heterogeneous data repositories in terms of multiple, relatively simple, view ontologies. Ontology developers can define such view ontologies and the corresponding mapping rules. These ontologies are represented in Semantic Web ontology languages such as RDFS, DAML+OIL, or OWL. We present our approach with examples from the e-learning domain using the Semantic Web query and transformation language TRIPLE

The Semantic Web … Sounds Logical!

The Semantic Web will be an enabling technology for the future because as all of life\u27s components continue to progress and evolve, the demand on us as humans will continue to increase. Work will expect more productivity; family will demand more quality time, and even leisure activities will be technologically advanced. With these variables in mind, I believe humans will demand technologies that help to simplify this treacherous lifestyle. As patterns already indicate, one of the driving forces of technological development is efficiency. Developers are consistently looking for ways to make life\u27s demands less strenuous and more streamlined. The benefits of the semantic web are two-fold. Conceptually, it will enable us to be productive at home while at work, and productive at work while at home. The Semantic Web will be a technology that truly changes our lifestyle. The Web has yet to harness its full potential. We have yet to realize that in addition to computers, other machines can actually participate in the decision-making process via the Internet. This will allow virtually all devices the opportunity to be a helpful resource for humans via the Web. It must be taken into consideration that the Semantic Web will not be separate from the World Wide Web, but an extension of it. It will allow information to be given a well-defined meaning, which will allow computers and people to work in cooperation. With this technology, humans will be able to establish connections to machines that are not currently connected to the World Wide Web. For the Semantic Web to function, computers must have access to structured collections of information and sets of inference rules that they can use to conduct automated reasoning (Scientific American: Feature Article: The Semantic Web, 3). Using rules to make inferences, choosing a course of action, and answering questions will add functional logic to the Web. Currently the Semantic Web community is developing this new Web by using Extensible Markup Language (XML) and Resource Description Framework (RDF) and ultimately, Ontologies