Catálogo de publicaciones - libros

Semantic Web technologies have started to make a difference in enterprise settings and have begun to creep into use in limited parts of the World Wide Web. As is common in overview articles, it is easy to imagine scenarios in which the Semantic Web could provide important infrastructure for activities across the broader Internet. Many of these seem to be focused on improvements to what is essentially a search function (e.g., “list the prices of flat screen HDTVs larger than 40 inches with 1080p resolution at shops in the nearest town that are open until 8pm on Tuesday evenings” [http://en.wikipedia.org/wiki/Semantic_ Web]), and such capabilities will surely be of use to future Internet users. However, if one looks closely at the research agendas of some of the largest Internet companies, it is not clear that the staples of SW thinking will intersect the most important paths of the major broad-spectrum service providers. Some of the emerging trends in the research labs of key industry players indicate that SW goals generally taken for granted may be less central than envisioned and that the biggest opportunities may come from some less obvious directions. Given the level of investment and the global reach of big players like Yahoo! and Google, it would pay us to look more closely at some of their fundamental investigations.

This work presents a retrospective analysis of how we have addressed new challenges in Web technologies and applications. WebML, which was first defined about 10 years ago, has been an incubator for research concerning abstractions, methods, tools, and technologies, acting as a glue within a group of people spread among universities, technology transfer centres, and a spin-off. In this paper, we first illustrate the common approach to innovation, and then show such approach at work in two contexts. One of them, dealing with “Service-Oriented Architectures” (SOA), has reached a mature state; the other one, “Semantic Web Services” (SWS), is at its infancy, but promises to deliver very interesting results in the forthcoming years.

This paper shows how technologies for Web data extraction, syndication and integration allow for new applications and services in the Business Intelligence and the Semantic Web domain. First, we demonstrate how knowledge about market developments and competitor activities on the market can be extracted dynamically and automatically from semi-structured information sources on the Web. Then, we show how the data can be integrated in Business Intelligence Systems and how data can be classified, re-assigned and transformed with the aid of Semantic Web ontological domain knowledge. Existing Semantic Web and Business Intelligence applications and scenarios using our technology illustrate the whole process.

In this paper, we briefly investigate several ways to develop human-level Web intelligence (WI) from a brain informatics (BI) perspective. BI can be regarded as brain sciences in WI centric IT age and emphasizes on a systematic approach for investigating human information processing mechanism. The recently designed instrumentation (fMRI etc.) and advanced IT are causing an impending revolution in both WI and BI, making it possible for us to understand intelligence in depth and develop human-level Web intelligence.

Software maintainers routinely have to deal with a multitude of artifacts, like source code or documents, which often end up disconnected, due to their different representations and the size and complexity of legacy systems. One of the main challenges in software maintenance is to establish and maintain the semantic connections among all the different artifacts. In this paper, we show how Semantic Web technologies can deliver a unified representation to explore, query and reason about a multitude of software artifacts. A novel feature is the automatic integration of two important types of software maintenance artifacts, source code and documents, by populating their corresponding sub-ontologies through code analysis and text mining. We demonstrate how the resulting “Software Semantic Web” can support typical maintenance tasks through ontology queries and Description Logic reasoning, such as security analysis, architectural evolution, and traceability recovery between code and documents.

This paper presents a minimalist program for RDF, by showing how one can do without several predicates and keywords of the RDF Schema vocabulary, obtaining a simpler language which preserves the original semantics. This approach is beneficial in at least two directions: (a) To have a simple abstract fragment of RDFS easy to formalize and to reason about, which captures the essence of RDFS; (b) To obtain algorithmic properties of deduction and optimizations that are relevant for particular fragments. Among our results are: the identification of a simple fragment of RDFS; the proof that it encompasses the main features of RDFS; a formal semantics and a deductive system for it; sound and complete deductive systems for their sub-fragments; and an complexity bound for ground entailment in this fragment.

The semantic web vision will facilitate automation of many tasks, including the location and dynamic reconfiguration of web services. In this article, we are concerned with a specific stage of web service location, called, by some authors, . We address contracting both at the operational level and at the semantic level. We present a framework encompassing communication and reasoning, in which web services exchange and evaluate goals and policies. Policies represent behavioural interfaces. The reasoning procedure at the core of the framework is based on the abductive logic programming SCIFF proof-procedure. We describe the framework, show by examples how to formalise policies in the declarative language of SCIFF, and give the framework a model-theoretic and a sound proof-theoretic semantics.

Dynamic discovery based on semantic description of services is an essential aspect of the Semantic Web services integration process. Since not all data required for service discovery can always be included in service descriptions, some data needs to be obtained during run-time. In this paper we define a model for service interface allowing required data to be fetched from the service provider during discovery process. We also provide a specification of such interface for WSMO and demonstrate the model on a case scenario from the SWS Challenge implemented using WSMX – a middleware platform built specifically to enact semantic service oriented architectures.

Discovery is a central reasoning task in service-oriented architectures, concerned with detecting Web services that are usable for solving a given request. This paper presents two extensions in continuation of previous works towards goal-based Web service discovery with sophisticated semantic matchmaking. At first, we distinguish goal templates as generic objective descriptions and goal instances that denote concrete requests as an instantiation of a goal template. Secondly, we formally describe requested and provided functionalities on the level of state transitions that denote executions of Web services, respectively solutions for goals. Upon this, we specify a two-phase discovery procedure along with semantic matchmaking techniques that allow to accurately determine the usability of a Web service. The techniques are defined in the Abstract State Space model that supports several languages for describing Web services.

WSML is an ontology language specifically tailored to annotate Web Services, and part of its semantics adheres to the rule-based knowledge representation paradigm of logic programming. We present a framework to support reasoning with rule-based WSML language variants based on existing Datalog inference engines. Therein, the WSML reasoning tasks of knowledge base satisfiability and instance retrieval are implemented through a language mapping to Datalog rules and Datalog querying. Part of the WSML semantics is realized by a fixed set of rules that form meta-level axioms. Furthermore, the framework exhibits some debugging functionality that allows for identifying violated constraints and for pointing out involved instances and problem types. Its highly modular architecture facilitates easy extensibility towards other language variants and additional features. The available implementation of the framework provides the first reasoners for the WSML language.