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Nowadays many museums are being transformed to some “smart” variants: a cultural space in a digitally-equipped environment is formed where cultural heritage knowledge can be easily and collaboratively usable and creatable by interested visitors as well as by professionals. By using such innovative technologies as Internet of Things (IoT) and Smart Spaces it is possible to shorten the distance between museum exhibits and collected historical information on one side and consumers and providers of this information on the other side. In this paper, we study the smart museum concept for development of software that realizes connection between the involved actors and shared cultural heritage knowledge. Our research and development are focused on designing a semantic layer in the form of a software infrastructure. This infrastructure is a middleware on top of which such advanced museum information services can be constructed as personal visit planning, virtual exhibition preparation, and collaborative enrichment the museum collection. We introduce a suit of smart space-based solutions to create this type of software infrastructures. The generic solutions are theoretically analyzed based on the case study of the History Museum of Petrozavodsk State University (PetrSU).

In this paper we show that an ontology-based approach can be beneficial for enhancing the access to cultural resources, and in particular historical documents. The paper starts with an overview of our approach, aimed at providing online archival systems with a semantic layer based on Semantic Web standards (OWL 2 and RDF). Two projects are introduced, namely Harlock900 and PRiSMHA, carried out in collaboration with local cultural institutions owning rich historical archives. In particular, the paper describes the computational ontologies supporting the approach, and then focuses on two case studies showing that our framework provides better results if compared with standard access systems. The case studies show the enhancement provided by a semantically rich representation of time intervals and a detailed formal description of events and their participants.

У статті висвітлено питання підтексту в музиці. Автор вивчає засоби та прийоми, які передають імпліцитну інформацію, досліджує функціонування підтексту на матеріалі «Добре темперованого клавіру» Й. С. Баха, де в прелюдіях і фугах композитор закодував релігійні мотиви, що наповнили музику новими смислами. Розглядаються інтерпретації В. Ландовської, С. Ріхтера та відтворення прихованого релігійного змістового пласту виконавцями. Ключові слова: Й. С. Бах, В. Ландовська, С. Ріхтер, «Добре темперований клавір», музика, підтекст, релігійний мотив, прелюдія, фуга. В статье раскрывается вопрос подтекста в музыке. Автор изучает средства и приёмы, которые передают имплицитную информацию, исследует функционирование подтекста на материале «Хорошо темперированного клавира» Й. С. Баха, где в прелюдиях и фугах композитор закодировал религиозные мотивы, которые в свою очередь наполнили музыку новыми смыслами. Рассматриваются интерпретации В. Ландовской, С. Рихтера и воспроизведение скрытого религиозного смыслового пласта исполнителями. Ключевые слова: Й. С. Бах, В. Ландовска, С. Рихтер, «Хорошо темперированный клавир», музыка, подтекст, религиозный мотив, прелюдия, фуга. The problem of subtext in music is under investigation in the paper. The author studies methods and ways for creating implied information and examines the function of subtext on the basis of J. S. Bach’s «The Well-Tempered Clavier», where the composer encoded religious motives in his preludes and fugues, and in turn it gave music new senses. W. Landowska’s and S. Richter’s interpretations and the performing musicians’ presentation of implicit religious semantic layer are considered. Key words: J. S. Bach, W. Landowska, S. Richter, «The Well-Tempered Clavier», music, subtext, religious motive, prelude, fugue.

The challenges facing learning of reasoning require a general refounding of knowledge modeling expressed by the development and integration of intelligence and reasoning techniques in the processing of this knowledge. In this paper, we present a part of the research work of PERO2 project. This intelligent system is a machine teaching dedicated to the learning of reasoning and problem-solving of exercises in physical science. Our research is focused on representing the knowledge base of PERO2 by integrating a semantic layer based upon a domain ontology, capable of adding some intelligence and enriching the reasoning in our system. In order to build this ontology, we propose a hybrid method based on two main phases: (*) design phase of our domain ontology called “OntoPhyScEx”. (**) Semantic validation phase of this ontology.

In this work, we describe a methodology to interpret large persons’ networks extracted from text by classifying cliques using the DBpedia ontology. The approach relies on a combination of NLP, Semantic web technologies, and network analysis. The classification methodology that first starts from single nodes and then generalizes to cliques is effective in terms of performance and is able to deal also with nodes that are not linked to Wikipedia. The gold standard manually developed for evaluation shows that groups of co-occurring entities share in most of the cases a category that can be automatically assigned. This holds for both languages considered in this study. The outcome of this work may be of interest to enhance the readability of large networks and to provide an additional semantic layer on top of cliques. This would greatly help humanities scholars when dealing with large amounts of textual data that need to be interpreted or categorized. Furthermore, it represents an unsupervised approach to automatically extend DBpedia starting from a corpus.

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries. The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007–2013) under Grant Agreement no.305444—the RD-Connect project. Pedro Sernadela is funded by Fundac¸ao para a Ci ˜ encia e Tecnologia (FCT) under the ˆGrant Agreement SFRH/BD/52484/2014. Lorena Gonzalez- ´Castro is funded by the Xunta de Galicia, including funding from the operative program FSE Galicia 2007–2013, under the Grant Agreement IN809A 19/2015.

This paper presents a proposal of CERIF data model extension for evaluation of scientific research results. The data model extension is based on the CERIF semantic layer which enables classification of entities and relations between entities according to some classification scheme. The proposed data model was created using PowerDesigner CASE tool. The model is represented using a physical data model in the conceptual notation that is adopted in literature for representing the CERIF data model. This model is verified using the rule book for evaluation and quantitative expression of scientific research results of researchers employed at University of Novi Sad. © 2010 Akadémiai Kiadó, Budapest, Hungary.

In several areas of research such as knowledge management and natural language processing, domain-specific corpora are required for tasks such as terminology extraction and ontology learning. The presented investigations herein are based on the assumption that Wikipedia can be used for the purpose of corpus extraction. It presents the advantage of possessing a semantic layer, which should ease the extraction of domain- specific corpora. Yet, as the Wikipedia category graph is scale- free, it can not be used as it is for these purposes. In this paper, we propose a novel approach to graph clustering called BorderFlow, which we use and evaluate on the Wikipedia category graph. Additional possible applications of these results in the area of information retrieval are presented.

Vocabulary is the most basic unit of language, and vocabulary cognitive is the most basic form of human linguistic cognitive. In this paper, we have a vocabulary recognition study of Chinese-English - Mongolian on visual information with the brain electrical technology. By comparing the ERP signal of English - Mongolian and English - Chinese vocabulary consistent or inconsistent respectively, found that there are priming effect between English Mongolian and English - Chinese, and indicate they have common semantic layer and different concept layer. This conclusion has inspired Mongolia college students to learn the third language effectively in the master of relationship of pronunciation and shape between the three languages.

In this paper we propose a series of novel lines of research emerging from the encounter of computer vision and formal ontologies. The main underlying idea is that a genuine visual knowledge can only emerge by the integration of the algorithmic and the semantic layer, which are typical of the two disciplines. We also present some early attempts at applying the proposed hybrid approach to tackle some important and still unsolved issues.

SOA allows a rapid and low-cost application development through service composition. Existing used methodologies designed to support service oriented development cannot be reused for semantic SOA without any adaptation. As a consequence, new methodologies are required to ensure effective semantic SOA application development. This paper aims to present an implementation strategy for the semantic layer of the Semantic SOA.

The e-mails used for personal or business proposals are becoming more and more difficult to manage. The abundant/overhead of e-mails and the lack of assistance from e-mail clients will certainly lead to losing tracks of information contained in e-mails. The multilingual nature of e-mails makes this situation even worse. In this research, we have explained the necessity for utilizing multilingual ontology learning processes to solve this problem. We have proposed the multilingual ontology learning algorithm for semantic email. The proposed algorithm is designed to handle the unstructured emails. This will lead to intelligent applications and information extraction for email users while keeping the semantic layer opaque to the end user.

In the field of multi-application personalization, several techniques have been proposed to support user modeling for user data management across different applications. Many of them are based on data reconciliation techniques often implying the concepts of static ontologies and generic user data models. None of them have sufficiently investigated two main issues related to user modeling: (1) profile definition in order to allow every application to build their own view of users while promoting the sharing of these profiles and (2) profile evolution over time in order to avoid data inconsistency and the subsequent loss of income for web-site users and companies. In this paper, we conduct work and propose separated solutions for every issue. We propose a flexible user modeling system, not imposing any fixed user model whom different applications should conform to, but based on the concept of mapping among applications (and mapping functions among their user attributes). We focus in particular on the management of user profile data propagation, as a way to reduce the amount of inconsistent user profile information over several applications. A second goal of this paper is to illustrate, in this context, the benefit obtained by the integration of a Semantic Layer that can help application designers to automatically identify potential user attribute mappings between applications. This paper so illustrates a work-in-progress work where two complementary approaches are integrated to improve a main goal: managing multi-application user profiles in a semi-automatic manner. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

We present the prototype of an augmented game that uses an enhanced Frisbee-Disc as an interaction device to explore the capability of flying tangible user interfaces for increasing the attractiveness of physical games. While playing with the disc, a dynamic audio stream is generated, which serves as an additional semantic layer that can be leveraged to develop novel game concepts for simple catch-and-throw games. Initial observations of users interacting with our prototype indicate that minor auditory augmentations to seemingly old-fashioned physical exertion games can have a potential to enhance the playing experience and support a more persistent engagement in physical activity.

Congratulations! You’ve reached the second part of the book. The first half focused on the importance of building a solid, structural foundation in HTML, creating a semantic layer upon which to build. We’ve introduced you to HTML5, the next generation of markup for the Web, and we’ve highlighted the benefits HTML5 has to offer, including some of the great new APIs and a large number of new, semantic elements that will ensure your web pages are just that extra bit future-friendly.

This chapter aims to collocate Akoma Ntoso into the historical scenario of the legal XML schemas and to define the pillars of the Akoma Ntoso architecture. Second goal is to present the basic elements of Akoma Ntoso XML standard and how it can be used for marking up a legal document respecting a clear subdivision between the semantic layer of the knowledge embedded into the document.

Book Subtitle: 5th International Conference, MTSR 2011, Izmir, Turkey, October 12-14, 2011. Proceedings Since biomedical information is scattered among a number of semantically or syntactically incompatible independent systems, a contemporary pragmatic approach is proposed in this study to make use of a semantic middle layer and common standards for information exchange between these systems. Biological and medical terminologies and ontologies take vital part in the background of life sciences information systems and the Unified Medical Language System (UMLS) is an inclusive source for biomedical vocabulary. Taking this fact into account, the need of new tools, which transform whole or part of UMLS content to a semantically sharable and reusable format, is also revealed to support knowledge-intensive biomedical actions.

A fundamental challenge in Peer-To-Peer (P2P) systems is how to locate objects of interest, namely, the look-up service problem. In the distributed hash table (DHT), including Chord, CAN, Pastry and Tapestry, among others, both object id and network node are randomly hashed to a same id space, so that “locality-awareness” is not inbuilt in the basic DHT design. Therefore, objects are referred to in a location-independent manner. In this paper, we propose an semantic approach to build a P2P system called SemanticChord which aims to integrate and organize the data/information resources based on the domain of interest to route requests to the most likely physical location of data. We apply the Topic maps approach as a semantic layer in aggregating and organizing ressources based on the domain of interest on top of the Chord Protocol. Experimental results show that SemanticChord improves the traditional DHT-based Chord in terms of average number of messages per lookup (11%), the average success rate for content location ( 6%) and response time.

In environmental databases there is a plethora of data, described in different terminologies, stored in different data structures and referring to distinct time periods and locations. Thus it is difficult for non-experts to find the data they are looking for. Adding an ontology-layer, which provides semantic enhancement, provides the underlying data structure for an open and intuitive search interface for non-experts. In this paper, we present the design of a bilingual eco-ontology using fuzzy mappings and loosely bridged ontologies which introduce a semantic layer in an existing environmental database storing data in German and French.

The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data-driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "subsymbolic semantic layer" automatically added to the Cyc ontology. Users queries can also be mapped in the same conceptual space, and evoke similar ontology concepts. As a result the agent can exploit this feature, attempting to retrieve ontological concepts that are not easily reachable by means of the traditional ontology reasoning engine.

Most of the efforts concerning graphical representations of humans (Virtual Humans) have been focused on synthesizing geometry for static or animated shapes. The next step is to consider a human body not only as a 3D shape, but as an active semantic entity with features, functionalities, interaction skills, etc. The ontology for Virtual Humans we are defining will provide the ”semantic layer” required to reconstruct, stock, retrieve and reuse content and knowledge related to Virtual Humans. The connection between the semantic and graphical data is achieved thanks to an intermediate layer based on anatomical features extracted form morphological shape analysis. The resulting shape descriptors can be used to derive higher-level descriptors from the raw geometric data. High-level descriptors can be used to control human models.

This paper presents a technology for information portals that supports multimedia retrieval while focusing at the same time on different ecologies of information provider and content owner environments. This means it addresses cross-media information provision and cross-owner content building. The technology was developed under the FP5 project IRAIA1 and was applied to two different areas: economic information and cultural information related to puppetry2. The first area puts more emphasis on multimedia retrieval while the latter one has special requirements in respect to cross-owner content building and content delivery. IRAIA enriches the implementation of multimedia, cross-media, and cross content owner retrieval with a design flexibility that enables an information provider to adapt the delivery channel as well as the content building process to requirements specific to its service. Leading through IRAIA applications in the areas mentioned above we present IRAIA’s system design and architecture, its human-computer interaction modes, and its powerful semantic layer that links the different facets of cross-media delivery and of cross-content building.

Previous approaches to robustness in natural language processing usually treat deviant input by relaxing grammatical constraints whenever a successful analysis cannot be provided by “normal” means. This schema implies, that error detection always comes prior to error handling, a behaviour which hardly can compete with its human model, where many erroneous situations are treated without even noticing them. The paper analyses the necessary preconditions for achieving a higher degree of robustness in natural language processing and suggests a quite different approach based on a procedure for structural disambiguation. It not only offers the possibility to cope with robustness issues in a more natural way but eventually might be suited to accommodate quite different aspects of robust behaviour within a single framework.