https://www.cs.ox.ac.uk/people/bernardo.cuencagrau/publications/PelletDemo.pdf

Pellet: A practical OWL-DL reasoner

Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaikos book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, and artificial intelligence. The second edition of Ontology Matching has been thoroughly revised and updated to reflect the most recent advances in this quickly developing area, which resulted in more than 150 pages of new content. In particular, the book includes a new chapter dedicated to the methodology for performing ontology matching. It also covers emerging topics, such as data interlinking, ontology partitioning and pruning, context-based matching, matcher tuning, alignment debugging, and user involvement in matching, to mention a few. More than 100 state-of-the-art matching systems and frameworks were reviewed. With Ontology Matching, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can be equally applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a systematic and detailed account of matching techniques and matching systems from theoretical, practical and application perspectives.

Ontology Matching

Service-oriented architectures (SOA) is an emerging approach that addresses the requirements of loosely coupled, standards-based, and protocol- independent distributed computing. Typically business operations running in an SOA comprise a number of invocations of these different components, often in an event-driven or asynchronous fashion that reflects the underlying business process needs. To build an SOA a highly distributable communications and integration backbone is required. This functionality is provided by the Enterprise Service Bus (ESB) that is an integration platform that utilizes Web services standards to support a wide variety of communications patterns over multiple transport protocols and deliver value-added capabilities for SOA applications. This paper reviews technologies and approaches that unify the principles and concepts of SOA with those of event-based programing. The paper also focuses on the ESB and describes a range of functions that are designed to offer a manageable, standards-based SOA backbone that extends middleware functionality throughout by connecting heterogeneous components and systems and offers integration services. Finally, the paper proposes an approach to extend the conventional SOA to cater for essential ESB requirements that include capabilities such as service orchestration, "intelligent" routing, provisioning, integrity and security of message as well as service management. The layers in this extended SOA, in short xSOA, are used to classify research issues and current research activities.

/pdf/service-oriented-architectures-approaches-technologies-and-1m0bcwz0fm.pdf

Service oriented architectures: approaches, technologies and research issues

In today’s Web, Web services are created and updated on the fly. It’s already beyond the human ability to analysis them and generate the composition plan manually. A number of approaches have been proposed to tackle that problem. Most of them are inspired by the researches in cross-enterprise workflow and AI planning. This paper gives an overview of recent research efforts of automatic Web service composition both from the workflow and AI planning research community.

/pdf/a-survey-of-automated-web-service-composition-methods-54v17alhym.pdf

A survey of automated web service composition methods

This is a system description of the Description Logic reasoner FaCT++. The reasoner implements a tableaux decision procedure for the well known SHOIQ description logic, with additional support for datatypes, including strings and integers. The system employs a wide range of performance enhancing optimisations, including both standard techniques (such as absorption and model merging) and newly developed ones (such as ordering heuristics and taxonomic classification). FaCT++ can, via the standard DIG interface, be used to provide reasoning services for ontology engineering tools supporting the OWL DL ontology language.

FaCT++ description logic reasoner : System description

https://www.cs.umd.edu/~nau/papers/sirin2004htn.pdf

HTN planning for Web Service composition using SHOP2

Current industry standards for describing Web Services focus on ensuring interoperability across diverse platforms, but do not provide a good foundation for automating the use of Web Services. Representational techniques being developed for the Semantic Web can be used to augment these standards. The resulting Web Service specifications enable the development of software programs that can interpret descriptions of unfamiliar Web Services and then employ those services to satisfy user goals. OWL-S ("OWL for Services") is a set of notations for expressing such specifications, based on the Semantic Web ontology language OWL. It consists of three interrelated parts: a profile ontology, used to describe what the service does; a process ontology and corresponding presentation syntax, used to describe how the service is used; and a grounding ontology, used to describe how to interact with the service. OWL-S can be used to automate a variety of service-related activities involving service discovery, interoperation, and composition. A large body of research on OWL-S has led to the creation of many open-source tools for developing, reasoning about, and dynamically utilizing Web Services.

/pdf/bringing-semantics-to-web-services-with-owl-s-52kxa9d5zi.pdf

Bringing Semantics to Web Services with OWL-S

In order to gain experience with description logic reasoner, and to contribute to the OWL Candidate Recommendation process, a small team at MINDSWAP set out to implement a tableau reasoner for the Lite and DL dialects of OWL (corresponding roughly to the description logics SHIF(D) and SHION(D)). Our group found existing, available DL reasoners lacking for our purposes, because we needed an open-source tool that provides ABox reasoning, that does not make Unique Name assumption, supports entailment checks and works with XML Schema datatypes. Pellet has been developed to addresses these issues and has become both our test bed for experiments with DL and Semantic Web reasoning, as well as our standard reasoning component. While not (yet) in the performance range of Racer or Fact, it has many usability features that makes it a good choice for various lighter weight situations. Technically, Pellet is a sound and complete tableau reasoners for SHIN(D) and SHON(D) (with ABoxes), and a sound but incomplete tableau reasoner for SHION(D) (with ABoxes). Pellet has the usual suite of optimizations including lazy unfolding, absorption, dependency directed backjumping, and semantic branching. It incorporates datatype reasoning for the built-in primitive XML Schema datatypes. Pellet is implemented in pure Java and available as open source software.

/pdf/pellet-an-owl-dl-reasoner-ooqcb14vlv.pdf

Pellet: An OWL DL Reasoner

As web services become more prevalent, tools will be needed to help users find, filter and integrate these services. Composing existing services to obtain new functionality will prove to be essential for both business-to-business and business-to-consumer applications. We have developed a prototype that guides a user in the dynamic composition of web services. Our semi-automatic process includes presenting matching services to the user at each step of a composition, filtering the possibilities by using semantic descriptions of the services. The generated composition is then directly executable through the WSDL grounding of the services. We tested our system by generating semantic descriptions for some of the common services available on the web such as translator, dictionary and map services. We also applied our approach to a prototype sensor network environment where each sensor provides its data as

/pdf/semi-automatic-composition-ofweb-services-using-semantic-3ar72gsboy.pdf

Evren Sirin

Papers

Pellet: A practical OWL-DL reasoner

HTN planning for Web Service composition using SHOP2

Bringing Semantics to Web Services with OWL-S

Pellet: An OWL DL Reasoner

Semi-automatic Composition ofWeb Services using Semantic Descriptions