Content Ontology Research Articles

Book Review. A New Insight into Theory of Conceptual Metaphor

Book Review. A New Insight into Theory of Conceptual Metaphor

Using UML class diagrams for content ontology design patterns engineering

The paper presents a method for Ontology Design Patterns (ODP) engineering based on the transformation of conceptual models serialized in the XML-like formats. In this paper, we use UML class diagrams as the source of conceptual models. The method includes the following activities: design and serialization of a source conceptual domain model; analysis and transformation of an XML structure of a source conceptual model to an ontological schema model; transformation of an ontological schema model to a content ODP code in the OWL 2 DL format; verification and modification of obtained content ODPs by domain experts. All transformations are implemented with the use of original domain-specific language, namely, Transformation Model Representation Language (TMRL). The proposed method is used for ODPs engineering in tasks of industrial safety inspection of technical systems. Obtained ODPs can be used for knowledge bases and intelligent systems engineering.

Prototyping of creation, implementation and visualization of correlation rules and microDocs

Semantic Correlation Rules (SCR) and microDocs are new concepts in the field of content delivery. SCR allow to define relationships between information units based on their metadata and, therefore, allow for the dynamic aggregation of microDocs. The creation of SCR heavily relies on the capabilities of modern content management systems (CMS) or ontology editors. The evaluation and visualization of the emerging microDocs, on the other hand, relies on the capabilities of content delivery portals (CDP). At this time, the support of both concepts in most software solutions currently being used, is only partly existent. This paper aims to demonstrate, how these currently existing limitations can be overcome, to reveal important factors to be considered and to showcase future possibilities of the aforementioned concepts. For this purpose, we developed a series of prototypes and conceptional visuals regarding creation of SCR, aggregation of microDocs and their visual appearance taking human perception into account.

Information Model of LibMeta Digital Library

When developing a digital library, heavy emphasis is laid onto the library information model. The content of digital libraries can be featured in different formats and presented in different ways. The library, as defined by the LibMeta system, is a storage of structured and diverse data with the possibility of integrating it with other data sources and specifying its content by analysing the subject area. The semantic content ontology of the library provides basis for further content formalization. The article introduces the basic concepts needed to describe the problem of data integration, as well as concepts required for the definition of an unspecified thesaurus. The ontology’s structure enables the possibility to determine the semantic library within any subject area.

COMBINING OF METHODS OF CONSTRAINT PROPAGATION AND STRUCTURAL DECOMPOSITION FOR THE A PRIORI ANALYSIS OF QUERIES TO THE ONTOLOGIES

Unlike relational DBMS that focused on maintaining of the referential integrity of rapidly changing transactional data, while using of RDF repositories which are storages for ontologies, there is no need to operate with such atomic structures as a tuple and you can use more suitable structures for grouping and summarizing of information. The article considers ontology as a set of relations (unary and binary), which are represented by specialized matrix-like structures – C-systems. That allows us to consider tasks of inference on ontologies as constraint satisfaction problems. The problem of a priori analysis and simplification of the SPARQL queries, considered in the article, is solved for ontologies that are developed using content ontology design patterns, which ensures the predictability of the structure of potential queries. In fact, each pattern is associated with a set of patterns of SPARQL queries. A method of a priori analysis and transformation of SPARQL queries patterns into a form, which speeds up the subsequent execution of concrete user queries has been developed. The method is based on the combining of the methods of structural decomposition and the author's methods for non-numeric constraints satisfaction. The structural decomposition methods make it possible to split the SPARQL query pattern into parts and parallelize its execution, which is especially important when accessing large volume RDF repositories. Due to the low frequency of modifications of the RDF repository, it is possible, based on the analysis of templates, to prepare data structures for the subsequent execution of concrete queries. This allows you to avoid unnecessary overhead incurred by repeated execution of the operation of joining the same relations when processing user requests described by a common pattern. For the join of relations, expressed as a set of C-systems, author's methods of non-numeric constraints satisfaction are applied, which are modifications of the known methods of maintaining node and arc consistency. As a result, the proposed approach to the ontology presentation and organization of inference procedures on ontologies allows to reduce the memory consumption and to ensure an acceptable speed of execution of SPARQL queries even for RDF repositories containing large amounts of data.

SmartOntoSensor: Ontology for Semantic Interpretation of Smartphone Sensors Data for Context-Aware Applications

The integration of cheap and powerful sensors in smartphones has enabled the emergence of several context-aware applications and frameworks. However, the available smartphone context-aware frameworks are static because of using relational data models having predefined usage of sensory data. Importantly, the frameworks lack the soft integration of new data types and relationships that appear with the emergence of new smartphone sensors. Furthermore, sensors generate huge data that intensifies the problem of too much data and not enough knowledge. Smarting of smartphone sensory data is essential for advanced analytical processing, integration, inferencing, and interpretation by context-aware applications. In order to achieve this goal, novel smartphone sensors ontology is required for semantic modeling of smartphones and sensory data, which is the main contribution of this paper. This paper presents SmartOntoSensor, a lightweight mid-level ontology that has been developed using NeOn methodology and Content Ontology Design pattern. The ontology describes smartphone and sensors from different aspects including platforms, deployments, measurement capabilities and properties, observations, data fusion, and context modeling. SmartOntoSensor has been developed using Protégé and evaluated using OntoQA, SPARQL, and experimental study. The ontology is also tested by integrating into ModeChanger application that leverages SmartOntoSensor for automatic changing of smartphone modes according to the varying contexts. We have obtained promising results that advocate for the improved ontological design and applications of SmartOntoSensor.

TECHNOLOGY OF APPLICATION OF ONTOLOGY DESIGN PATTERNS FOR ACCELERATION OF QUERIES EXECUTION IN ONTOLOGY BASED DATA ACCESS SYSTEMS

One of the known approaches to the construction of knowledge-based systems is the Ontology-based data access (OBDA) approach, which involves combining an ontology that represents a domain conceptual system and a relational database used to store data that corresponds to the concepts defined in the ontology. In this case, the ontology is used as the basis for the formation of user queries, and the database for obtaining the results of their execution. The article proposes a technology for improving the performance of queries to such systems by preliminarily database preparation, taking into account that the used ontology have been developed with using content ontology design patterns (CDP). These patterns are small ontology fragments that describes generalized situations of the domain (for example, participation in an event, the execution of some role, the parts of an object, etc.). The novelty of this technology determines the possibility of its application for a whole class of ontologies based on ontological patterns. The general principle of ontology-based data access system is considered. The description of the proposed technology, as well as its implementation for a specific ontology, and an experimental evaluation of the obtained results are described.

OntoPedigree: Modelling pedigrees for traceability in supply chains

The sharing of product and process information plays a central role in coordinating supply chains operations and is a key driver for their success. Linked - linked datasets, that encapsulate event based traceability information of artifacts as they move along the supply chain, provide a scalable mechanism to record and facilitate the sharing of track and trace knowledge among supply chain partners. In this paper we present a content ontology design pattern for the representation of linked pedigrees, that can be specialised and extended to define domain specific traceability ontologies. Events captured within the pedigrees are specified using EPCIS - a GS1 standard for the specification of traceability information within and across enterprises, while certification information is described using PROV - a vocabulary for modelling provenance of resources. We exemplify the utility of OntoPedigree in linked pedigrees generated for supply chains within the perishable goods and pharmaceuticals sectors.

Rancang Bangun Pembangkit Ontologi dan RDF pada Sistem E-Learning PrimagamaPlus

PrimagamaPlus adalah situs e-Learning Primagama yang berisi resource edukatif diantaranya ebook, video, berita dan artikel edukasi, serta TryOut secara Online. Situs ini sangat bermanfaat bagi siswa dalam belajar. PrimagamaPlus ingin konten yang dimiliki juga dapat dikonsumsi oleh aplikasi atau sistem lain. Oleh Karena itu Penelitian ini bertujuan untuk menerapkan penggunaan teknologi web semantik agar konten pembelajaran PrimagamaPlus dapat dimanfaatkan oleh aplikasi-aplikasi lain melalui Internet. Pengembangan program menggunakan web semantik jenis RDF/XML karena skemanya dapat dibuat sendiri menggunakan RDFs dan Ontologi OWL. Library untuk pengembangan web semantik adalah DotNetRDF. Program yang dibuat berupa pembangkit ontologi dan pembangkit RDF untuk setiap konten e-Learning PrimagamaPlus. Ontologi dibuat dengan cara mendefinisikan kelas, datatype properties dan object properties yang akan digunakan untuk pembuatan RDF. Data RDF yang dibangkitkan menggunakan data ontologi sesuai dengan profil masing-masing konten e-Learning. Pembangkit RDF diset aktif saat ada penambahan, perubahan, atau penghapusan konten, agar tidak menambah aktivitas Administrator. Penelitian ini menunjukkan bahwa aplikasi di luar PrimagamaPlus dapat lebih mudah menambang konten-konten e-Learning PrimagamaPlus. Setiap halaman PrimagamaPlus yang diakses, maka berkas RDF yang telah dibangkitkan tidak diikutkan di halaman tersebut. Yang ditambahkan hanyalah tag links yang mengacu ke lokasi berkas RDF. Hal ini memudahkan pengguna dan mesin penambang data mengakses konten karena transfer data yang relatif kecil. PrimagamaPlus, the Primagama e-Learning website has education resources consist of ebook, video, education news, article, and online tryout. This website is very useful for students when studying. PrimagamaPlus wants its learning contents can be consumed well machines or applications. So, this research purpose is to implement the use of semantic web technology so that the PrimagamaPlus learning contents can be consumed easily by those applications or machines. The software development use RDF/XML semantic web type because its schema can be costumed in RDFs and OWL ontology. The library for its development is DotNetRDF. The software feature that is built are ontology generator and RDF generator for every PrimagamaPlus e-Learning contents. The ontology is written by defining the classes, datatype properties and object properties that will be used for RDF creation. The RDF data that are created use ontology data apropriated with each e-Learning contents profiles. The RDF generator will run when there are addition, update, or deletion of the contents, so the administrator has no activity addition for this. This research shows that custom mining applications more easily to mine every PrimagamaPlus e-Learning contents. Every accessed PrimagamaPlus page, the RDF data is not added in it. The addition for the page is a links tag that has RDF data url. This condition make the users and mining applications have no transfer data difficulties when downloading the contents.

M-Learning through Semantically Annotated Learning Objects and Ontologies

Number of mobile subscriptions has increased tremendously due to rapid development of mobile technologies. The performance and accessibility of the e-learning process can be enhanced through mobile devices which is called m-learning. M-learning makes learning resources available anywhere and anytime, provide strong search capabilities, and offers easy interaction features to the learners. M-learning also points the opportunity for interoperability than existing e-learning system. The integration of semantic web in m-learning can improve the efficiency of searching for learning objects and reduce the time and cost of learning process. Semantic web can be integrated with the help of ontologies and learning objects in semantic web. They offer rich medium to assist m-learning via semantic annotated learning objects and shared repositories. Two types of ontologies, such as learning object content ontology and learning object structure ontology are used in this system. These ontologies facilitate the reuse, sharing and retrieval of relevant learning objects which are the backbone of m-learning.

Semantic Service Registration and Retrieval for Smart Home

In order to solve the syntax problem of service retrieval based on keywords, we present an Ontology-based solution for service registration and retrieval in this paper. Firstly we analyze the semantics of home service from different facets, and extract relative concepts of service to construct three domain ontologies including function ontology, content ontology and device ontology. Then, a model based on these domain ontologies has been presented. Finally the process from registration to retrieval is given in detail.

Reconstruction of phylogenetic relationships from metabolic pathways based on the enzyme hierarchy and the gene ontology.

There has been much interest in the structural comparison and alignment of metabolic pathways. Several techniques have been conceived to assess the similarity of metabolic pathways of different organisms. In this paper, we show that the combination of a new heuristic algorithm for the comparison of metabolic pathways together with any of three enzyme similarity measures (hierarchical, information content, and gene ontology) can be used to derive a metabolic pathway similarity measure that is suitable for reconstructing phylogenetic relationships from metabolic pathways. Experimental results on the Glycolysis pathway of 73 organisms representing the three domains of life show that our method outperforms previous techniques.

A Context-Aware Reasoning Framework with OWL for Mobile Web Information Acquisition

As the mobile Internet era advances, using mobile devices to access web content has become more and more popular. However, users often find that mobile web content acquisition is not convenient as expected and is problematic. In this study, we devise a context-aware reasoning framework to tackle this problem. We implement a prototype system using Protege with Jess Tab, which is a plug-in Jess module. In the proposed framework, the user profile, network and environment parameters, device information, etc. are characterized as the user context and is described in OWL format so that it can be shared, reused and applied to the reasoning engine. With Protege, we build a user context template, which is an OWL document, and design a context updater to automatically update the context information. The web content ontology is constructed also with Protege and is exported into OWL format so that logic inference for web page navigation can be performed automatically. Moreover, reasoning rules are defined so as to automatically infer appropriate web information for users. A pragmatic example with our prototype system shows that, with the proposed context-aware reasoning framework, a mobile user can be automatically and easily navigated to access the web page that he or she wants to browse and, therefore, can acquire the appropriate web information quickly and efficiently.

A linguistic ontology

This paper defends the choice of a linguistically-based content ontology for natural language processing and demonstrates that a single common-sense ontology produces plausible interpretations at all levels from parsing through reasoning. The paper explores some of the problems and tradeoffs for a method which has just one content ontology. A linguistically-based content ontology represents the "world view" encoded in natural language. The content ontology (as opposed to the formal semantic ontology which distinguishes events from propositions, and so on) is best grounded in the culture, rather than in the world itself, or in the mind. By "world view" we mean naive assumptions about "what there is" in the world, and how it should be classified. These assumptions are time-worn and reflected in language at several levels: morphology, syntax and lexical semantics. The content ontology presented in the paper is part of a Naive Semantic lexicon, Naive Semantics is a lexical theory in which associated with each word sense is a naive theory (or set of beliefs) about the objects or events of reference. While naive semantic representations are not combinations of a closed set of primitives, they are also limited by a shallowness assumption. Included is just the information required to form a semantic interpretation incrementally, not all of the information known about objects. The Naive Semantic ontology is based upon a particular language, its syntax and its word senses. To the extent that other languages codify similar world views, we predict that their ontologies are similar. Applied in a computational natural language understanding system, this linguistically-motivated ontology (along with other native semantic information) is sufficient to disambiguate words, disambiguate syntactic structure, disambiguate formal semantic representations, resolve anaphoric expressions and perform reasoning tasks with text.