Three-Valued Paraconsistent Reasoning for Semantic Web Agents

PurposeThe purpose of this paper is to explore useful Semantic Web technologies and ontology-based applications for digital libraries. It also investigates the perceptions of university librarians and academicians in Pakistan about Semantic Web technologies and their use in digital libraries.Design/methodology/approachAn exploratory research design based on Delphi research strategy was conducted to answer the research questions. Interviews were conducted with a purposive sample of 50 key informants including university librarians and academicians to explore their perceptions about Semantic Web technologies and their use in digital libraries. Thematic analysis of interview data was conducted to obtain results.FindingsThe results of this paper showed that DuraCloud, Semantic information mashup, OntoEdit and resource description framework (RDF) are the various Semantic Web applications which are useful for digital libraries to develop semantic relationships among digital contents and increase their accessibility in the web environment. Findings revealed that Semantic Web provides precise results and meets user information needs in an effective way. Results also showed that next-generation digital libraries use context-awareness technology, intelligent agent software and detecting sensors to analyze user information needs and provide dynamic information services. This paper recommended that librarians should embrace the use of emerging web technologies in libraries and offer library services through the medium of the web.Practical implicationsThis paper envisaged the future of digital library services and Semantic Web applications that can be used to re-structure metadata of digital library. This paper has practical implications for librarians to consider the useful applications of Semantic Web for digital library and enhance the interoperability of metadata among heterogeneous information systems. Practically, results obtained from this paper are highly useful for library schools and LIS teachers to up-date their curriculum by incorporating new contents related to web languages and Semantic Web applications for digital libraries.Originality/valueThis paper identifies various Semantic Web applications which are useful for developing Semantic Digital Libraries.

Answering regular path queries in expressive Description Logics via alternating tree-automata

Revising knowledge bases (KBs) in description logics (DLs) in a syntax-independent manner is an important, nontrivial problem for the ontology management and DL communities. Several attempts have been made to adapt classical model-based belief revision and update techniques to DLs, but they are restricted in several ways. In particular, they do not provide operators or algorithms for general DL KB revision. The key difficulty is that, unlike propositional logic, a DL KB may have infinitely many models with complex (and possibly infinite) structures, making it difficult to define and compute revisions in terms of models. In this paper, we study general KBs in a specific DL in the DL-Lite family. We introduce the concept of features for such KBs, develop an alternative semantic characterization of KBs using features (instead of models), define two specific revision operators for KBs, and present the first algorithm for computing best approximations for syntax-independent revisions of KBs.

Description logics (DLs) and rule-based systems are two prominent families of knowledge representation formalisms. While DLs are focused on describing and reasoning about conceptual knowledge, rules are focused on answering queries about facts in the knowledge base. So far, research on DLs has been largely isolated from the research on rules. With the advent of the Semantic Web, however, it became apparent that neither formalism alone can cover all the practical use cases. The integration between DLs and rules, however, is technically challenging due to significant differences in the underlying semantic assumptions. In particular, DLs are based on standard first-order semantics and open-world assumption, whereas rules typically employ closed-world semantics based on a variant of circumscription. In my talk, I shall present an overview of the benefits of integrating DLs and rules in a coherent semantic framework, and shall discuss the main challenges in achieving a tight integration. I shall present an overview of the approaches currently discussed in literature. Finally, I shall present in more detail the approach that is based on the nonmonotonic logic MKNF by Lifschitz. This approach is tight in the sense that DLs and rules are given a common model-theoretic semantics. Furthermore, it is faithful in the sense that it is compatible with the original semantics of both DLs and rules. Finally, it is expressive and can naturally capture many of the existing proposals. I shall discuss the definitions of the semantics of the hybrid formalism, present a decision procedure for a particular decidable fragment, and discuss the complexity bounds of reasoning.

Semantic Web technologies play an increasingly important role in the integration of heterogeneous biomedical information as well as the generation of meaningful links between biological and clinical information resources, which are at the basis of both, translational and personalized, medicine. A critical component of the emergence of these technologies is the need to represent domain knowledge, e.g. biological and medical knowledge, in the systems that we build in order to facilitate not just the low level integration of resources, but to enable knowledge-driven analysis and reasoning across them. As is true for many other scientific disciplines, in spite of the potential benefits to be gained, we are still far from seeing a widespread adoption of the Semantic Web for the Life Sciences. Part of the problem is of course the large investment of effort needed to develop sufficiently formal representations of enough Life Science knowledge in the form of ontologies and other knowledge bases, but there are also issues with the maturity of the tools and applications that are currently available to those who want to develop and use Semantic Web applications and tools in the Life Sciences. The purpose of the SWAT4LS workshops http://www.swat4ls.org is to create a space for discussions involving experts from the Computing as well as the Life Sciences, filling the gap between the possibilities and the practicalities of the Semantic Web in the Life Sciences domain. The first of these took place in Edinburgh on 28 November 2008 and at its heart was the question as to what is hindering a more rapid adoption of Semantic Web technologies in this domain. To reflect this, the panel discussion at the Edinburgh workshop was held under the heading of If the Semantic Web is so good, why is everybody using OBO for ontologies and PERL for data integration?. The original call for the SWAT4LS 2008 workshop resulted in the total of 40 submissions which were peer reviewed: 8 were accepted as full papers, 4 as poster papers and one as a demo paper. In addition, a number of posters were accepted. The workshop took place at the e-Science Institute in Edinburgh and was attended by about 80 participants. Following the actual workshop, all contributors to SWAT4LS'08 (papers as well as posters) were invited to submit extended versions of their contributions, resulting in the submission of 21 papers, which underwent another complete peer review cycle. Of these, 13 papers were selected and are included in this BMC Bioinformatics supplement. We are delighted with the collection of high quality papers that are the result of this endeavor and are confident that the readers will find them helpful in their own work on Semantic Web technologies for the Life Sciences. We would like to thank all who have contributed to the SWAT4LS 2008 workshop and this BMC Bioinformatics supplement. Specifically, we thank all the authors for their contributions, all the reviewers who served on the program committee for the original workshop call and then again for the submissions for this supplement, the invited speakers (Prof. Michael Krauthammer, Dr. M. Scott Marshall and Prof. Mark D. Wilkinson) and all the participants who made the workshop a memorable event. The support from the e-Science Institute in Edinburgh, which has hosted the workshop and covered some of the costs for our invited speakers, is also gratefully acknowledged. We also thank our sponsors: OMII-UK, LabAge SA, Leaf Bioscience and Textensor Limited for their support., Finally, we thank the staff at BMC Bioinformatics, specifically Ms. Isobel Peters, for their help with editing and processing this supplement. Albert Burger, Paolo Romano, Adrian Paschke and Andrea Splendiani (SWAT4LS Supplement Editors and Co-chairs of SWAT4LS 2008)

Description logics provide powerful languages for representing and reasoning about knowledge of static application domains. The main strength of description logics is that they offer considerable expressive power going far beyond propositional logic, while reasoning is still decidable. There is a demand to bring the power and character of description logics into the description and reasoning of dynamic application domains which are characterized by actions. In this paper, based on a combination of the propositional dynamic logic PDL, a family of description logics and an action formalism constructed over description logics, we propose a family of dynamic description logics DDL(X @) for representing and reasoning about actions, where X represents well-studied description logics ranging from the to the , and X @ denotes the extension of X with the @ constructor. The representation power of DDL(X @) is reflected in four aspects. Firstly, the static knowledge of application domains is represented as RBoxes and acyclic TBoxes of the description logic X. Secondly, the states of the world and the pre-conditions of atomic actions are described by ABox assertions of the description logic X @, and the post-conditions of atomic actions are described by primitive literals of X @. Thirdly, starting with atomic actions and ABox assertions of X @, complex actions are constructed with regular program constructors of PDL, so that various control structures on actions such as the "Sequence", "Choice", "Any-Order", "Iterate", "If-Then-Else", "Repeat-While" and "Repeat-Until" can be represented. Finally, both atomic actions and complex actions are used as modal operators for the construction of formulas, so that many properties on actions can be explicitly stated by formulas. A tableau-algorithm is provided for deciding the satisfiability of DDL(X @)-formulas; based on this algorithm, reasoning tasks such as the realizability, executability and projection of actions can be effectively carried out. As a result, DDL(X @) not only offers considerable expressive power going beyond many action formalisms which are propositional, but also provides decidable reasoning services for actions described by it.

The vision of the Semantic Web aims to make use of semantic representations on the largest possible scale - the Web. Large knowledge bases such as DBpedia, OpenCyc, and GovTrack are emerging and freely available as Linked Data and SPARQL endpoints. Exploring and analysing such knowledge bases is a significant hurdle for Semantic Web research and practice. As one possible direction for tackling this problem, the authors present an approach for obtaining complex class expressions from objects in knowledge bases by using Machine Learning techniques. The chapter describes in detail how to leverage existing techniques to achieve scalability on large knowledge bases available as SPARQL endpoints or Linked Data. The algorithms are made available in the open source DL-Learner project and this chapter presents several real-life scenarios in which they can be used by Semantic Web applications.

Data warehouses have established themselves as necessary components of an effective Information Technology (IT) strategy for large businesses. In addition to utilizing operational databases data warehouses must also integrate increasing amounts of external data to assist in decision support. An important source of such external data is the Web. In an effort to ensure the availability and quality of Web data for the data warehouse we propose an intermediate data-staging layer called the Meta-Data Engine (M-DE). A major challenge, however, is the conversion of data originating in the Web, and brought in by robust search engines, to data in the data warehouse. The authors therefore also propose a framework, the Semantic Web Application (SEMWAP) framework, which facilitates semi-automatic matching of instance data from opaque web databases using ontology terms. Their framework combines Information Retrieval (IR), Information Extraction (IE), Natural Language Processing (NLP), and ontology techniques to produce a matching and thus provide a viable building block for Semantic Web (SW) Applications.

Description logics (DLs) are modern knowledge representation formalisms which are used today in many applications for reasoning with structured knowledge. Moreover, they are used in the semantic web (an extension of the current web) through the ontology language OWL. On the other hand fuzzy description logics (fuzzy-DLs) have been proposed as expressive logical formalisms capable of capturing and reasoning with

An article tries to see a group of semantic web representation and communication means like description logics, semantic networks, RDF model and language, OWL language, RDF CFL etc. taking a part at the development of formal ontologies from a slightly higher (meta) level. A focus has been oriented towards properties that semantic web language ought to have to fulfill according to a semantic web idea. Consequently the article tries to draw by the help of the means above the trip towards a proper semantic-web ontology language fulfilling the main demands of expressivity and also easy-to-use conditions. Even if the development of a semantic web language was until now much more complicated with a taking part of a lot of people or companies the authors of the article try to contribute to an analyzing of the actual state by drawing it as a cloud of demands, streams, events or condition’s fulfilling that at the end would have brought into the world an easy-to-usable semantic web ontology language having all the demands fulfilled. The article moreover shows that a language RDF CFL belongs nowadays to the semantic web family as a unique well usable tool of reasoning within semantic web knowledge bases.

For designing Entity-relationship(ER) schemas, an interesting topic is how to transform ER schemas into knowledge bases (KBs) in description logics (DLs). It is significance in translations that one can use automated DL reasoning services to support the development and maintenance of correct ER schemas. This paper proposed a faithful translation, which translates ER schemas into KBs in the description logic ALDL and allows us to reduce reasoning on ER schemas to finite models reasoning on ALDL KBs.

Automatic service discovery in heterogeneous environment is becoming one of the challenging problems for applications in semantic web, wireless sensor networks, etc. It is mainly due to the lack of accurate semantic similarity assessment between profile attributes of user request and web services. Generally, lexical semantic resources consist of corpus and domain knowledge. To improve similarity measures in terms of accuracy, various hybrid methods have been proposed to either integrate different semantic resources or combine various similarity methods based on a single resource. In this work, we propose a novel approach which combines vector similarity metrics in a continuous vector space to evaluate semantic similarity between concepts. This approach takes advantage of both corpus and knowledge base by constructing diverse vector space models. Specifically, we use differential evolutionary (DE) algorithm which is an powerful population-based stochastic search strategy for obtaining optimal value of the combination. Our approach has been validated against a variety of vector-based similarity approaches on multiple benchmark datasets. The empirical results demonstrate that our approach outperforms the state-of-the-art approaches. The results also indicate the continuous vectors are efficient for evaluating semantic similarity, since they have outstanding expressiveness to latent semantic features of words. Moreover, the robustness of our approach is presented by the steady measure results under different hyper-parameters of neural network. Keywords-differential evolutionary; semantic similarity; continuous vector space; vector similarity metrics

DTD and its instance have been considered the standard for data representation and information exchange format on the current web. However, when coming to the next generation of web, the Semantic Web, the drawbacks of XML and its schema are appeared. They mainly focus on the structure level and lack support for data representation. Meanwhile, some Semantic Web applications such as intelligent information services and semantic search engines require not only the syntactic format of the data, but also the semantic content. These requirements are supported by the Web Ontology Language (OWL), which is one of the recent W3C recommendation. But nowadays the amount of data presented in OWL is small in compare with XML data. Therefore, finding a way to utilize the available XML documents for the Semantic Web is a current challenge research. In this work we present an effective solution for transforming XML document into OWL domain knowledge. While keeping the original structure, our work also adds more semantics for the XML document. Moreover, whole of the transformation processes are done automatically without any outside intervention. Further, unlike previous approaches which focus on the schema level, we also extend our methodology for the data level by transforming specific XML instances into OWL individuals. The results in existing OWL syntaxes help them to be loaded immediately by the Semantic Web applications.

Semantic Web research relies on a number of key methodologies such as knowledge representation languages or reasoning algorithms. As a research community, however, we could not progress based on these methodologies exclusively, but require tools and systems that realize our research results as key technologies for the Semantic Web. There would be no Linked Data without repositories to store them, no Semantic Web applications without application programming interfaces to load and edit ontologies, and no semanticsbased user interfaces without reasoners. Consequently, some of these technologies are research enablers in their own rights. Unfortunately, the developers of such software— often researchers themselves—rarely get appropriate credit for their work. Attempts to publish papers describing their software systems frequently provoke reviews and decision letters questioning their ’conceptual contribution’. This criticism may be correct, be it because the conceptual underpinnings have been published previously, or because there may in fact be little conceptual underpinnings apart from excellent software engineering. As a result, developers of key research enabling software often have considerable difficulties publishing their work in high-quality journals. In turn, paradoxically, researchers using these systems within their own work lack a primary citation source for the used software, and may have to settle for a URL, a short demo paper, or for a workshop contribution as citation. These outlets, however, can not provide the rigid quality criteria and visibility compared to journal publications. There is a need for publishing Tools and Systems papers in primary journals. The criteria applied to evaluate such papers have to differ from those applied to classical research articles. Unfortunately, these alternative evaluation criteria are often not spelled out in detail and therefore not consistently taken into account by reviewers and editors. As a consequence, the Semantic Web journal has adopted the Tools and Systems article as one of its regular paper types and provides crisp criteria for their evaluation: Reports on tools and systems—short papers describing mature Semantic Web related tools and systems. These reports should be brief and pointed, indicating clearly the capabilities of the described tool or system. It is strongly encouraged, that the described tools or systems are free, open, and accessible on the Web. If this is not possible, then they have to be made available to the reviewers. For commercial tools and systems, exceptions can be arranged through the editors. These submissions will be reviewed along the following dimensions: (1) Quality, importance, and impact of the described tool or system (convincing evidence must be provided). (2) Clarity, illustration, and readability of the describing paper, which shall convey to the reader both the capabilities and the limitations of the tool. The impact of the described tool or system is indeed decisive. Authors are asked to provide evidence for a substantial number of researchers using their software for research and applications. In exceptional cases, authors may also argue about the potential future impact of their software given that they can provide clear evidence for this. Clearly, software prototypes which were only implemented as proof-of-concepts, or software which is closely tied to a particular (externally funded) project, are out of scope. Originality or novelty—which are decisive dimensions for high-quality research articles—are not mentioned among the evalu-

Reasoning with inconsistencies is an important issue for Semantic Web as imperfect information is unavoidable in real applications. For this, different paraconsistent approaches, due to their capacity to draw as nontrivial conclusions by tolerating inconsistencies, have been proposed to reason with inconsistent description logic knowledge bases. However, existing paraconsistent approaches are often criticized for being too skeptical. To this end, this paper presents a non-monotonic paraconsistent version of description logic reasoning, called minimally inconsistent reasoning, where inconsistencies tolerated in the reasoning are minimized so that more reasonable conclusions can be inferred. Some desirable properties are studied, which shows that the new semantics inherits advantages of both non-monotonic reasoning and paraconsistent reasoning. A complete and sound tableau-based algorithm, called multi-valued tableaux, is developed to capture the minimally inconsistent reasoning. In fact, the tableaux algorithm is designed, as a framework for multi-valued DL, to allow for different underlying paraconsistent semantics, with the mere difference in the clash conditions. Finally, the complexity of minimally inconsistent description logic reasoning is shown on the same level as the (classical) description logic reasoning.