OWL

This paper presents the results of the STASIS (www.stasis-project.net) project and applies it to the area of semantic interoperability within technologyenhanced learning platforms. Within the paper an innovative approach for creating a comprehensive application suite is introduced which allows partners to simplify the mapping process between data schemas of different e-Learning platforms. This mapping allows users to easily transfer content from one e-Learning platform to another and hence making it much easier to reuse e-Learning objects and to update to new e-Learning environments without spending serious resources on manual migration of content and user models.

The paper provides an OWL ontology for legal cases with an instantiation of the legal case Popov v. Hayashi. The ontology makes explicit the conceptual knowledge of the legal case domain, supports reasoning about the domain, and can be used to annotate the text of cases, which in turn can be used to populate the ontology. A populated ontology is a case base which can be used for information retrieval, information extraction, and case based reasoning. The ontology contains not only elements of indexing the case (e.g. the parties, jurisdiction, and date), but as well elements used to reason to a decision such as argument schemes and the components input to the schemes. We use the Protégé ontology editor and knowledge acquisition system, current guidelines for ontology development, and tools for visual and linguistic presentation of the ontology. 1

From networks to Description Logics 8 1.3 Knowledge representation in Description Logics 16 1.4 From theory to practice: Description Logics systems 20 1.5 Applications developed with Description Logics systems 24 1.6 Extensions of Description Logics 34 1.7 Relationship to other fields of Computer Science 40 1.8 Conclusion 43 Part one: Theory 45 2 Basic Description Logics F. Baader, W. Nutt 47 2.1 Introduction 47 2.2 Definition of the basic formalism 50 2.3 Reasoning algorithms 78 2.4 Language extensions 95 3 Complexity of Reasoning F. M. Donini 101 3.1

The need for smart e-learning environments is resulting in new challenges for researchers and practitioners to develop intelligent systems that can be used to automate the Higher Education (HE) activities in an intelligent way. Some common examples of such activities are “analyzing, finding, and ranking the right resource to teach a course,” “analyzing and finding the people with common research interests to start joint research projects,” and “using data analytics and machine reasoning techniques for conducting the exams with different levels of complexities.” Ontological reasoning and smart data analytics can play an important role in analyzing and automating these HE activities and processes. In this paper, we present a framework named as Higher Education Activities and Processes Automation Framework (HEAPAF). The HEAPAF framework can be used to identify, extract, process, and produce the semantically enriched data in machine understandable format from different educational resources. We also present the Higher Education Ontology (HEO) that we designed and developed to accommodate the HE data and then to perform analysis and reasoning on it. As a proof of concept, we present a case study on the topic, “analyzing, finding, and ranking the right resources to teach a course,” which can dramatically improve the learning patterns of students in the growing smart educational environment. Finally, we provide the evaluation of our framework as evidence of its competency and consistency in improving academic analytics for educational activities and processes by using machine reasoning.

Semantic analysis is an essential feature of the NLP approach. It indicates, in the appropriate format, the context of a sentence or paragraph. Semantics is about language significance study. The vocabulary used conveys the importance of the subject because of the interrelationship between linguistic classes. In this article, semantic interpretation is carried out in the area of Natural Language Processing. The findings suggest that the best-achieved accuracy of checked papers and those who relied on the Sentiment Analysis approach and the prediction error is minimal.

Improving efficiency in the plant construction process and providing valid resulting plant models requires a technology that validates planning and data exchange formats for plant engineering, such as CAEX (Computer Aided Engineering Exchange). Semantic Web technologies support validation mechanisms for querying and reasoning over domain models expressed in form of ontologies. In this paper, we present an approach to the automated validation of CAEX plant models by their transformation to ontologies and subsequent application of Semantic Web reasoning for validation purposes.

This text provides a brief overview of selected structures aimed at knowledge representation in the form of ontologies based on description logic and aims at comparing them with their counterparts based on the rule-based approach. Due to the limitations on the length of the article, only elements associated with the representation of concepts could be shown, without including roles. The formalisms of the OWL language were used to record ontologies, while the rules were expressed in Prolog.

Esta tesis presenta el desarrollo de la plataforma denominada Selector de Tesis de la Universidad de Colima. Dicha plataforma es una herramienta web responsiva que ayuda a los alumnos de educación superior a elegir un tema de tesis de grado conforme algunos de sus intereses académicos (tema central, programa educativo, plantel educativo, nivel académico, asesor, grupo y línea de investigación, palabras clave, etc.), haciendo uso de filtros que permiten realizar búsquedas dinámicas, basadas en ontologías mediante una interfaz amigable. A los asesores de tesis, les ayuda a gestionar y administrar los proyectos de investigación de una manera independiente y autónoma, así como a llevar el control de las solicitudes de tesis por parte de los alumnos. La plataforma Selector de Tesis realiza el proceso de selección de tema de tesis, el proceso de aceptación del alumno y la generación de la carta compromiso; asimismo cataloga y muestra la información más relevante de las tesis, e informa si las tesis están o no están disponibles para ser solicitadas a los asesores.

La plataforma Selector de Tesis se realizó en dos fases fundamentales, empleando diversas técnicas de la ingeniería de software (edición de ontologías, transformación de modelos, aplicaciones web, búsquedas dinámicas, manejadores de base de datos). En la primera fase se desarrolló la plataforma Thesis-Selecter utilizada por la Facultad de Telemática de la Universidad de Colima, la cual utilizó la herramienta OWL to SQL Transformer (un transformador de modelos creado ad hoc para esta tesis). Con base en la experiencia de desarrollo y los buenos resultados de las pruebas sobre usabilidad y aceptación tecnológica, realizadas a asesores y alumnos de la Facultad de Telemática, se desarrolló la plataforma Selector de Tesis de la Universidad de Colima, como la segunda fase.

In this paper, we present a Knowledge Based System for describing
and storing dances that takes advantage of the expressivity of Description Logics.
We propose exploiting the tools of the Semantic Web Technologies in
representing and archiving dance choreographies by developing a Dance Ontology
in OWL-2. Description Logics allow us to express complex relations and
inference rules for the domain of dance movement, while Reasoning capabilities
make it easy to extract new knowledge from existing knowledge. Furthermore,
we can search within the ontology based on the steps and movements of
dances by writing SPARQL queries. The constructing elements of the ontology
and their relationships to construct the dance model are based on the semantics
of the Labanotation system, a widely applied language that uses symbols to denote
dance choreographies.

This paper is a survey of the research topics in the field of Semantic Web, Linked Data and Web of Data. This study looks at the contributions of this research community over its first twenty years of existence. Compiling several bibliographical sources and bibliometric indicators , we identify the main research trends and we reference some of their major publications to provide an overview of that initial period. We conclude with some perspectives for the future research challenges. RÉSUMÉ. Cet article est une étude des sujets de recherche dans le domaine du Web sémantique, des données liées et du Web des données. Cette étude se penche sur les contributions de cette communauté de recherche au cours de ses vingt premières années d'existence. En compilant plusieurs sources bibliographiques et indicateurs bibliométriques, nous identifions les princi-pales tendances de la recherche et nous référencons certaines de leurs publications majeures pour donner un aperçu de cette période initiale. Nous concluons avec une discussion sur les tendances et perspectives de recherche.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the specific activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information.
A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the first time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledge-based architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the first module's output, and executes ontological inference to provide users, activities and their influence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in different environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches.
As an added value, for the system to be sufficiently simple and
flexible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and configure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the final application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Mémoire pour le diplôme de master « Technologies numériques appliquées à l'histoire » 2015 Remerciements Je souhaite remercier en premier lieu Anne-Marie Turcan-Verkerk et Matthieu Bonicel pour m'avoir accordé ce stage et donné une vraie autonomie pour mener mes activités. Je remercie également tous les membres du Pool Biblissima, en particulier Pauline Charbonnier, Stefanie Gehrke, Elizabeth MacDonald et Régis Robineau, pour leur accueil enthousiaste, leurs conseils précieux, leur confiance, leur patience et leur gentillesse. Je remercie de nouveau Anne-Marie Turcan-Verkerk pour avoir partagé avec moi ses connaissances sur Florus, Mannon et leurs manuscrits, ainsi que Pierre Chambert-Protat pour m'avoir apporté son expertise en matière des manuscrits de Florus. Mes remerciements vont également à l'ensemble des enseignants de l'Ecole des chartes et à Jean-Baptiste Camps, responsable pédagogique du master « Technologies numériques appliquées à l'histoire ». Les compétences acquises dans le cadre du master m'ont permis d'appréhender ce stage avec sérénité et de mener à bout mon travail.

Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we describe the major prerequisites and challenges that should be addressed by the modern exploration and visualization systems. Considering these challenges, we present how state-of-the-art approaches from the Database and Information Visualization communities attempt to handle them. Finally , we survey the systems developed by Semantic Web community in the context of the Web of Linked Data, and discuss to which extent these satisfy the contemporary requirements.

Enterprise architecture facilitates the alignment between different domains, such as business, applications and information technology. These domains must be described with description languages that best address the concerns of its stakeholders. However, current model-based enterprise architecture techniques are unable to integrate multiple descriptions languages either due to the lack of suitable extension mechanisms or because they lack the means to maintain the coherence, consistency and traceability between the representations of the multiple domains of the enterprise. On the other hand, enterprise architecture models are often designed and used for communication and not for automated analysis of its contents. Model analysis is a valuable tool for assessing the qualities of a model, such as conformance and completeness, and also for supporting decision making. This paper addresses these two issues found in model-based enterprise architecture: (1) the integration of domain description languages, and (2) the automated analysis of models. This proposal uses ontology engineering techniques to specify and integrate the different domains and reasoning and querying as a means to analyse the models. The utility of the proposal is shown through an evaluation scenario that involve the analysis of an enterprise architecture model that spans multiple domains. Enterprise architecture is defined by Lankhorst as "a coherent whole of principles, methods, and models that are used in the design and realization of an enterprise's organizational structure, business processes, information systems, and infrastructure", with a "focus on alleviating the infamous business-information technology alignment problem" [1]. Such alignment is typically achieved through the creation of models describing an enterprise, including business and IT elements, so that it can realize management requirements and be maintained over the period of its useful life .

Spirit, Power and Axis of everything, in our mortal eyes there is Emptiness: for the truly complete in these empty ones is empty. The Moon, the Axis of everything in our world, is therefore empty for them, and SHOULD BE empty. // Дух, Сила и Ось всего, в смертных очах — Пустота: ибо истинно полное в них, пустых, пусто. Луна, Ось всего в нашем мире, для них посему и пуста, и ДОЛЖНА БЫТЬ пустой.

Recent research in semantic web technologies for the built environment has resulted in several proposals to further improve information exchange among stakeholders from the domain. Most notable is the production of several OWL ontologies that allow to capture building data in RDF graphs. For example, an ifcOWL ontology allows to capture IFC data in an RDF graph. As the building data is now available in a semantic graph with an explicit formal basis, it can be restructured and simplified so that it more easily matches the different requirements associated with practical use case scenarios. In this paper, we investigate several proposals and technological approaches to simplify ifcOWL building data, thus addressing the needs of specific industrial use cases.

During the poetry tour of UK and Europe, Bill and Daph hosted me in their delightful cottage in St Albans, following my Ver Poets recitation (April 27, 1998). I recall being transfixed by a tiny metal sculpture of an owl in the bedroom. It had a pair of large holes in place of eyes and I recall telling Bill that an Owl poem was bound to occur. And so it did a month later, one night in Graz, Austria. I must have then mailed it to Bill and 22 years later, emailed it to his daughter after learning that Bill had passed away.

The calligraphy was displayed in the Downloading Animals exhibition, Galerie Jean Cocteau. Bombay, April 6-10, 1999.
The poem was published in Alphabestiary, Holstein: Exile Editions, 2011. p.66

Cross Reference. See also
The note next to Daedalus (Calligraphy) in Poetry Section
Downloading Animals in Bat, Poetry Section
Alphabestiary in the Books section
VER Reading in Talks Section (forthcoming)

The management of resources is a great challenge for commanders in Search and Rescue operations and has a strong impact on all areas of operation control, as command-and-communication structure, geo-referenced information, and operational tasks are inter-connected with complex relations. During an operation these are subject to dynamic changes. For an efficient operation control commanders need access to up-to-date information in their mobile working environment. This paper presents a new approach to manage resources and their relations in an operation. It is based on ontologies to build a model of an operation and Description Logic reasoning to provide enhanced decision support.

The increasing availability of web services necessitates efficient discovery and execution framework. The use of xml at various levels of web services standards poses challenges to the above process. OWLS is a service ontology and language, whose semantics are based on OWL. The semantics provided by OWL support greater automation of service selection, invocation, translation of message content between heterogeneous services, and service composition. The development and consumption of an OWLS based web service is time consuming and error prone. OWLS IDE assists developers in the semantic web service development, deployment and consumption processes. In order to achieve this the OWLS IDE uses and extends existing web service tools. In this paper we will look in detail at the support for discovery for semantic web services. We also present the matching schemes, the implementation and the results of performance evaluation. .

Numerous images embedded in the painted decorations in early modern Central and Eastern European synagogues conveyed allegorical messages to the congregation. The symbolism was derived from biblical verses, stories, legends, and prayers, and sometimes different allegories were combined to develop coherent stories. In the present case study, which concerns a bird, seemingly a nocturnal raptor, depicted on the ceiling of the Unterlimpurg Synagogue, I explore the symbolism of this image in the contexts of liturgy, eschatology, and folklore. I undertake a comparative analysis of paintings in medieval and early modern illuminated manuscripts-both Christian and Jewish-and in synagogues in both Eastern and Central Europe. I argue that in some Hebrew illuminated manuscripts and synagogue paintings, nocturnal birds of prey may have been positive representations of the Jewish people, rather than simply a response to their negative image in Christian literature and art, but also a symbol of redemption. In the Unterlimpurg Synagogue, the night bird of prey, combined with other symbolic elements, represented a complex allegoric picture of redemption, possibly implying the image of King David and the kabbalistic nighttime prayer Tikkun H. az. ot. This case study demonstrates the way in which early modern synagogue painters created allegoric paintings that captured contemporary religious and mystical ideas and liturgical developments.

Enemy or Threat Courses of Action are produced during Intelligence Preparation of the Battlefield, during the Military Decision Making Process, and as part of the process of Situation Development. Due to the overwhelming amount of information involved in these processes and the limited time available to intelligence analysts, significant efforts are underway to develop computer based tools to assist in these processes. For these to be successful there needs to be a way for formally representing Enemy/Threat Courses of Action. This paper investigates the requirements for and potential solutions to this problem using OWL, elements of JC3IEDM and the OWL Time ontology.

This paper presents a task-based and Semantic Web approach to find geospatial data. The purpose of the project is to improve data discovery and facilitate automatic retrieval of data sources. The work presented here helps create the beginnings of a Geospatial Semantic Web. The intent is to create a system that provides appropriate results to application users who search for data when facing tasks such as emergency response or planning activities. In our task-based system, we formalize the relationships between types of tasks, including emergency response, and types of data sources needed for those tasks. Domain knowledge, including criteria describing data sources, is recorded in an ontology language. With the ontology, reasoning can be done to infer various types of information including which data sources meet specific criteria for use in particular tasks. The vision presented here is that in an emergency, for example, a user accesses a Web-based application and selects the type of emergency and the geographic area. The application then returns the types and locations (URLs) of the specific geospatial data needed. We explore the abilities and limitations of the OWL Web Ontology Language along with other Semantic Web technologies for this purpose.

The semantic web remains in the early stages of development. It has not yet achieved the goals envisioned by its founders as a pervasive web of distributed knowledge and intelligence. Success will be attained when a dynamic synergism can be created between people and a sufficient number of infrastructure systems and tools for the semantic web in analogy with those for the original web. The domain name system (DNS), web browsers, and the benefits of publishing web pages motivated many people to register domain names and publish web sites on the original web. An analogous resource label system, semantic search applications, and the benefits of collaborative semantic networks will motivate people to register resource labels and publish resource descriptions on the semantic web. The Domain Ontology Oriented Resource System (DOORS) and Problem Oriented Registry of Tags and Labels (PORTAL) are proposed as infrastructure systems for resource metadata within a paradigm that can serve as a bridge between the original web and the semantic web. Registers domain names while DNS publishes domain addresses with mapping of names to addresses for the original web. Analogously, POR-TAL registers resource labels and tags while DOORS publishes resource locations and descriptions with mapping of labels to locations for the semantic web. BioPORT is proposed as a prototype PORTAL registry specific for the problem domain of biomedical computing.

In collaborative environments where resources must be shared across multiple sites, the access control policies of the participants must be combined in order to define a coherent policy. The relevant challenge in composing access policies is to deal with inconsistencies or modality conflicts. This difficulty exacerbates when the policies to compose are specified independently by different entities with no global power to decide in case of conflicts which entity must take precedence. In this paper, we present a semi-automated framework called Policy Composition and Conflict Resolution framework (P2CR) to address this issue. We focus on access control policies expressed as XACML statements. We propose a three-level conflicts resolution strategy: i.) by using metadata added to the policies, ii.) by using a defeasible logic theory, and iii.) by providing recommendations to the entities owners of the resources. The novelty of this work is threefold. First, we provide a mechanism to add metadata to XACML. Such mechanism allows the entities to express adjustments they are willing to bring in their access policies in a way to prevent potential conflicts during the composition. Second, we combine the access policies without prioritizing any of the entities involved in the composition. Given the context of our work, we consider this approach to be more suitable than the current approaches that are mainly negotiationoriented or assign priorities to the policies. Finally, the resulting composite policy appears flexible and easily adjustable to runtime conflicts.

Business ontology can enhance the successful development of complex enterprise system; this is being achieved through knowledge sharing and the ease of communication between every entity in the domain. Through human semantic interaction with the web resources, machines to interpret the data published in a machine interpretable form under web. However, the theoretical practice of business ontology in eCommerce domain is quite a few especially in the section of electronic transaction, and the various techniques used to obtain efficient communication across spheres are error prone and are not always guaranteed to be efficient in obtaining desired result due to poor semantic integration between entities. To overcome the poor semantic integration this research focuses on proposed ontology called LB2CO, which combines the framework of IDEF5 & SNAP as an analysis tool, for automated recommendation of product and services and create effective ontological framework for B2C transaction & communication across different business domains that facilitates the interoperability & integration of B2C transactions over the web.

There is a critical need to design and develop tools that abstract away the fundamental complexity of XML-based Web services specifications and toolkits, and provide an elegant, intuitive, simple, and powerful query-based invocation system to end users. Web services based tools and standards have been designed to facilitate seamless integration and development for application developers. As a result, current implementations require the end user to have intimate knowledge of Web services and related toolkits, and users often play an informed role in the overall Web services execution process. We employ a self-learning mechanism and a set of algorithms and optimizations to match user queries with corresponding operations in Web services. Our system uses Semantic Web concepts and Ontologies in the process of automating Web services matchmaking. We present performance analysis of our system and quantify the exact gains in precision and recall due to the knowledge acquisition algorithms.

Requirements specification is a major component of the system development cycle. Mistakes and omissions in requirements documents lead to ambiguous or wrong interpretation by engineers and, in turn, cause errors that trickle down in design and implementation with consequences on the overall development cost. In this paper we describe a methodology for requirements specification that aims to alleviate the above issues and that produces models for functional requirements that can be automatically validated for completeness and consistency. This methodology is part of the Requirements Driven Design Automation framework (RDDA) that we develop for component-based system development. The RDDA framework uses an ontology-based language for semantic description of functional product requirements, UM-L/SysML structure diagrams, component constraints, and Quality of Service. The front end method for requirements specification is the SysML editor in Rhapsody. A requirements model in OWL is converted from SysML XMI representation. The specification is validated for completeness and consistency with a ruled-based system implemented in Prolog. With our methodology, omissions and several types of consistency errors present in the requirements specification are detected early on, before the design stage.

The Software & Systems Process Engineering meta-model (SPEM) allows the modelling of software processes using OMG (Object Management Group) standards such as the MOF (Meta-Object Facility) and UML (Unified Modelling Language) making possible to represent software processes using tools compliant with UML. Process definition encompasses both the static and dynamic structure of roles, tasks and work products together with imposed constraints on those elements. However, the latter requires support for constraint enforcement that is not always directly available in SPEM. Such constraint-checking behaviour could be used to detect possible mismatches between process definitions and the actual processes being carried out in the course of a project. This paper approaches the modelling of such constraints using the SWRL (Semantic Web Rule Language), which is a W3C recommendation. To do so, we need first represent generic processes modelled with SPEM using an underlying ontology based on the OWL (Ontology Web Language) representation together with data derived from actual projects.

Current mobile middleware is designed according to a 'one-size-fits-all' paradigm, which lacks the flexibility for customization and adaptation to different situations, and does not support user-centered application scenarios well. In this paper we describe an ongoing intelligent mobile middleware research project called PLIMM that focuses on user-centered application scenarios. PLIMM is designed based on software product line ideas which make it possible for specialized customization and optimization for different purposes and hardware/software platforms. To enable intelligence, the middleware needs access to a range of context models. We model these contexts with OWL, focusing on usercentered concepts. The basic building block of PLIMM is the enhanced BDI agent where OWL context ontology logic reasoning will add indirect beliefs to the belief sets. Our approach also addresses the handling of ontology evolutions resulting from the timely adaptation of ontology to changes and the consistent propagation of these changes to all related artifacts, using Frame based product line configuration techniques.

In this paper we describe O-DEVICE, a memory-based knowledge base system for reasoning and querying OWL ontologies by implementing RDF/OWL entailments in the form of production rules in order to apply the formal semantics of the language. Our approach is based on a transformation procedure of OWL ontologies into an Object-Oriented schema and the application of inference production rules over the generated objects in order to implement the various semantics of OWL. In order to enhance the performance of the system, we introduce a dynamic approach of generating production rules for ABOX reasoning and an incremental approach of loading ontologies. O-DEVICE is built over the CLIPS production rule system, using the object-oriented language COOL to model and handle ontology concepts and RDF resources. One of the contributions of our work is that we enable a well-known and efficient production rule system to handle OWL ontologies. We argue that although native OWL rule reasoners may process ontology information faster, they lack some of the key features that rule systems offer, such as the efficient manipulation of the information through complex rule programs. We present a comparison of our system with other OWL reasoners, showing that O-DEVICE can constitute a practical rule environment for ontology manipulation.

Whether predators can limit their prey has been a topic of scientific debate for decades. Traditionally it was believed that predators take only wounded, sick, old or otherwise low-quality individuals, and thus have little impact on prey populations. However, there is increasing evidence that, at least under certain circumstances, vertebrate predators may indeed limit prey numbers. This potential role of predators as limiting factors of prey populations has created conflicts between predators and human hunters, because the hunters may see predators as competitors for the same resources. A particularly acute conflict has emerged over the past few decades between gamebird hunters and birds of prey in Europe. As a part of a European-wide research project, we reviewed literature on the relationships between birds of prey and gamebirds. We start by analysing available data on the diets of 52 European raptor and owl species. There are some 32 species, mostly specialist predators feeding on small mammals, small passerine birds or insects, which never or very rarely include game animals (e.g. hares, rabbits, gamebirds) in their diet. A second group (20 species) consists of medium-sized and large raptors which prey on game, but for which the proportion in the diet varies temporally and spatially. Only three raptor species can have rather large proportions of gamebirds in their diet, and another seven species may utilise gamebirds locally to a great extent. We point out that the percentage of a given prey species in the diet of an avian predator does not necessarily reflect the impact of that predator on densities of prey populations. Next, we summarise available data on the numerical responses of avian predators to changing gamebird numbers. In half of these studies, no numerical response was found, while in the remainder a response was detected such that either raptor density or breeding success increased with density of gamebirds. Data on the functional responses of raptors were scarce. Most studies of the interaction between raptors and gamebird populations give some estimate of the predation rate (per cent of prey population taken by predator), but less often do they evaluate the subsequent reduction in the pre-harvest population or the potential limiting effect on breeding numbers. The few existing studies indicate that, under certain conditions, raptor predation may limit gamebird populations and reduce gamebird harvests. However, the number and extent of such studies are too modest to draw firm conclusions. Furthermore, their geographical bias to northern Europe, where predator-prey communities are typically simpler than in the south, precludes extrapolation to more diverse southern European ecosystems. There is an urgent need to develop further studies, particularly in southern Europe, to determine the functional and numerical responses of raptors to gamebird populations in species and environments other than those already evaluated in existing studies. Furthermore, additional field experiments are needed in which raptor and possibly also mammalian predator numbers are manipulated on a sufficiently large spatial and temporal scale. Other aspects that have been little studied are the role of predation by the non-breeding part of the raptor population, or floaters, on the breeding success and survival of gamebirds, as well as the effect of intra-guild predation. Finally there is a need for further research on practical methods to reduce raptor predation on gamebirds and thus reduce conflict between raptor conservation and gamebird management.

Learning Management Systems should focus on how to satisfy the e-learners needs and it may advise a learner with most suitable resources and learning objects. But Because of many limitations using web 2.0 for creating E-learning management system, now-a-days we use Web 3.0 which is known as Semantic web. It is a platform to represent E-learning management system that recovers the limitations of Web 2.0.In this paper we present "improve information retrieval and e-learning using mobile agent based on semantic web technology". This paper focuses on design and implementation of knowledge-based industrial reusable, interactive, web-based training activities at the sea ports and logistics sector and use e-learning system and semantic web to deliver the learning objects to learners in an interactive, adaptive and flexible manner. We use semantic web and mobile agent to improve Library and courses Search. The architecture presented in this paper is considered an adaptation model that converts from syntactic search to semantic search. We apply the training at Damietta port in Egypt as a real-world case study. we present one of possible applications of mobile agent technology based on semantic web to management of Web Services, this model improve the information retrieval and E-learning system.

The Web of Data is an open environment consisting of a great number of large inter-linked RDF datasets from various do-mains. In this environment, organizations and companies adopt the Linked Data practices utilizing Semantic Web (SW) tech-nologies, in order to publish their data and offer SPARQL endpoints (i.e., SPARQL-based search services). On the other hand, the dominant standard for information exchange in the Web today is XML. Additionally, many international standards (e.g., Dublin Core, MPEG-7, METS, TEI, IEEE LOM) in several domains (e.g., Digital Libraries, GIS, Multimedia, e-Learning) have been expressed in XML Schema. The aforementioned have led to an increasing emphasis on XML data, accessed using the XQuery query language. The SW and XML worlds and their developed infrastructures are based on different data models, semantics and query languages. Thus, it is crucial to develop interoperability mechanisms that allow the Web of Data users to access XML datasets, using SPARQL, from their own working environments. It is unrealistic to expect that all the existing legacy data (e.g., Relational, XML, etc.) will be transformed into SW data. Therefore, publishing legacy data as Linked Data and providing SPARQL endpoints over them has become a major research challenge. In this direction, we introduce the SPARQL2XQuery Framework which creates an interoperable environment, where SPARQL queries are automatically translated to XQuery queries, in order to access XML data across the Web. The SPARQL2XQuery Framework provides a mapping model for the expression of OWL–RDF/S to XML Schema mappings as well as a method for SPARQL to XQuery translation. To this end, our Framework supports both manual and automatic mapping specification between ontologies and XML Schemas. In the automatic mapping specification scenario, the SPARQL2XQuery exploits the XS2OWL component which transforms XML Sche-mas into OWL ontologies. Finally, extensive experiments have been conducted in order to evaluate the schema transfor-mation, mapping generation, query translation and query evaluation efficiency, using both real and synthetic datasets.

Effective use of electronic healthcare records (EHRs) has the potential to positively influence both the quality and the cost of health care. Consequently, sharing patient's EHRs is becoming a global priority in the healthcare information technology domain. This paper addresses the interoperability of EHR structure and content. It describes how two different EHR standards derived from the same reference information model (RIM) can be mapped to each other by using archetypes, refined message information model (R-MIM) derivations, and semantic tools. It is also demonstrated that well-defined R-MIM derivation rules help tracing the class properties back to their origins when the R-MIMs of two EHR standards are derived from the same RIM. Using well-defined rules also enable finding equivalences in the properties of the source and target EHRs. Yet an R-MIM still defines the concepts at the generic level. Archetypes (or templates), on the other hand, constrain an R-MIM to domain-specific concepts, and hence, provide finer granularity semantics. Therefore, while mapping clinical statements between EHRs, we also make use of the archetype semantics. Derivation statements are inferred from the Web Ontology Language definitions of the RIM, the R-MIMs, and the archetypes. Finally, we show how to transform Health Level Seven clinical statement instances to EHRcom clinical statement instances and vice versa by using the generated mapping definitions.

The diet of the Barn Owl Tyto alba and the Spotted Owlet Athene brama were studied in an urban habitat of Yavatmal city, Maharashtra, India, during June to October 2013. Regurgitated pellets of these two owl species were analysed to understand their dietary composition. The diet of the Barn Owl mainly comprised small mammals such as Suncus murinus (61.53%) and Mus Booduga grey (23.07%), while the diet of the Spotted Owlet comprised mostly insects like Coleoptera (87.47%) and Mus booduga (35%). Food niche overlap between the Barn Owl and the Spotted Owlet in overall diet as indicated by Piankas index was found to be 0.131.