Use Of Semantic Web Technologies Research Articles

CyanoBase:a large-scale update on its 20th anniversary.

The first ever cyanobacterial genome sequence was determined two decades ago and CyanoBase (http://genome.microbedb.jp/cyanobase), the first database for cyanobacteria was simultaneously developed to allow this genomic information to be used more efficiently. Since then, CyanoBase has constantly been extended and has received several updates. Here, we describe a new large-scale update of the database, which coincides with its 20th anniversary. We have expanded the number of cyanobacterial genomic sequences from 39 to 376 species, which consists of 86 complete and 290 draft genomes. We have also optimized the user interface for large genomic data to include the use of semantic web technologies and JBrowse and have extended community-based reannotation resources through the re-annotation of Synechocystis sp. PCC 6803 by the cyanobacterial research community. These updates have markedly improved CyanoBase, providing cyanobacterial genome annotations as references for cyanobacterial research.

Software component and the semantic Web: An in-depth content analysis and integration history

A detailed study on the use of Semantic Web technologies in CBSE.Advancement is being made from using ontological concepts to Linked Data in CBSE.Semantic web techniques help in addressing the various challenges that CBSE faces.Simple and freely accessible CBSE applications that employ Semantic Web are limited.Some open issues relevant to the topic in concern have been examined. With the advent of Component-based software engineering (CBSE), large software systems are being built by integrating pre-built software components. The Semantic Web in association with CBSE has shown to offer powerful representation facilities and reasoning techniques to enhance and support querying, reasoning, discovery, etc. of software components. The goal of this paper is to research the applicability of Semantic Web technologies in performing the various tasks of CBSE and review the experimental results of the same in an easy and effective manner. To the best of our knowledge, this is the first study which provides an extensive review of the application of Semantic Web in CBSE from different perspectives. A systematic literature review of the Semantic Web approaches, employed for use in CBSE, reported from 2001 until 2015, is conducted in this research article. Empirical results have been drawn through the question-answer based analysis of the research, which clearly tells the year wise trend of the research articles, with the possible justification of the usage of Semantic Web technology and tools for a particular phase of CBSE. To conclude, gaps in the current research and potential future prospects have been discussed.

Word Sense Disambiguation Using Semantic Web for Tamil to English Statistical Machine Translation

<div><p><em> Machine Translation has been an area of linguistic research for almost more than two decades now. But it still remains a very challenging task for devising an automated system which will deliver accurate translations of the natural languages. However, great strides have been made in this field with more success owing to the development of technologies of the web and off late there is a renewed interest in this area of research. </em></p><p><em> Technological advancements in the preceding two decades have influenced Machine Translation in a considerable way. Several MT approaches including Statistical Machine Translation greatly benefitted from these advancements, basically making use of the availability of extensive corpora. Web technology web3.0 uses the semantic web technology which represents any object or resource in the web both syntactically and semantically. This type of representation is very much useful for the computing systems to search any content on the internet similar to lexical search and improve the internet based translations making it more effective and efficient.</em></p><p><em> In this paper we propose a technique to improve existing statistical Machine Translation methods by making use of semantic web technology. Our focus will be on Tamil and Tamil to English MT. The proposed method could successfully integrate a semantic web technique in the process of WSD which forms part of the MT system. The integration is accomplished by using the capabilities of RDFS and OWL into the WSD component of the MT model. The contribution of this work lies in showing that integrating a Semantic web technique in the WSD system significantly improves the performance of a statistical MT system for a translation from Tamil to English.</em></p></div><em> In this paper we assume the availability of large corpora in Tamil language and specific domain based ontologies with Tamil semantic web technology using web3.0. We are positive on the expansion and development of Tamil semantic web and subsequently infer that Tamil to English MT will greatly improve the disambiguation concept apart from other related benefits. This method could enable the enhancement of translation quality by improving on word sense disambiguation process while text is translated from Tamil to English language. This method can also be extended to other languages such as Hindi and Indian Languages.</em>

Cognitive friendship and goal management for the social IoT

The concept of an Internet of Things is already mature, enough to start evolving towards an Internet of Everything, over which humans, objects and virtual items can be interconnected. For this to be feasible though, there is the need for a framework which not only supports the interconnection between the entities of this Internet, but also allows the meaningful interaction between them. In this paper, we present an idea on how this can be materialized, based on the use of semantic web technologies and smart software agents. These middleware technologies, combined with machine learning techniques, can lead to cognitive friendship and goal management. The paper includes a presentation of the theoretical framework, a use case scenario, and results over the use of a simulation tool.

Dimensional enrichment of statistical linked open data

On-Line Analytical Processing (OLAP) is a data analysis technique typically used for local and well-prepared data. However, initiatives like Open Data and Open Government bring new and publicly available data on the web that are to be analyzed in the same way. The use of semantic web technologies for this context is especially encouraged by the Linked Data initiative. There is already a considerable amount of statistical linked open data sets published using the RDF Data Cube Vocabulary (QB) which is designed for these purposes. However, QB lacks some essential schema constructs (e.g., dimension levels) to support OLAP. Thus, the QB4OLAP vocabulary has been proposed to extend QB with the necessary constructs and be fully compliant with OLAP. In this paper, we focus on the enrichment of an existing QB data set with QB4OLAP semantics. We first thoroughly compare the two vocabularies and outline the benefits of QB4OLAP. Then, we propose a series of steps to automate the enrichment of QB data sets with specific QB4OLAP semantics; being the most important, the definition of aggregate functions and the detection of new concepts in the dimension hierarchy construction. The proposed steps are defined to form a semi-automatic enrichment method, which is implemented in a tool that enables the enrichment in an interactive and iterative fashion. The user can enrich the QB data set with QB4OLAP concepts (e.g., full-fledged dimension hierarchies) by choosing among the candidate concepts automatically discovered with the steps proposed. Finally, we conduct experiments with 25 users and use three real-world QB data sets to evaluate our approach. The evaluation demonstrates the feasibility of our approach and shows that, in practice, our tool facilitates, speeds up, and guarantees the correct results of the enrichment process.

Semantic catalogs for life cycle assessment data

Life cycle assessment (LCA) is a highly interdisciplinary field that requires knowledge from different domains to be gathered and interpreted together. Although there are relatively few major data sources for LCA, the data themselves are presented with highly heterogeneous formats, interfaces, and distribution mechanisms. The lack of agreement among data providers for descriptions of processes and flows creates substantial barriers for information sharing and reuse of practitioners’ models.Nevertheless, the many data resources share a common logic. The use of Semantic Web technologies and text mining techniques can facilitate the interpretation of data from diverse sources. Numerous existing efforts have been made to articulate a knowledge model for LCA. In March of 2015 a joint workshop was held that brought together leading international domain experts with ontology engineers to develop a set of simple models called ontology design patterns (ODPs) for LCA information. In this paper we build on the outcomes of the workshop, as well as prior published works, to derive a minimal “consensus model” for LCA. We use the consensus model to derive a description of an LCA “catalog” that can be used to express the semantic content of a data resource. We generate catalogs of several prominent databases, and make those catalogs available to the public for independent use. Finally, we “link” those catalogs to existing knowledge models using JSON-LD, a linked data format that can expose the catalog contents to Semantic Web tools.We then show by example how the catalogs may be used to answer questions about the scope, coverage, and comparability of data, both within and across data sources, that are difficult to answer when the contents of the catalogs are provided independently and inconsistently. We discuss how the use of semantic catalogs can help address challenges that initiatives such as the “Global Network of Interoperable LCA Databases – Global LCA Data Access” are facing today.

La Web Semántica y los archivos de televisión: estado de la cuestión

Se analizan y describen las principales líneas de trabajo de la Web Semántica en el ámbito de los archivos de televisión. Para ello, se analiza y contextualiza la web semántica desde una perspectiva general para posteriormente analizar las principales iniciativas que trabajan con lo audiovisual: Proyecto MuNCH, Proyecto S5T, Semantic Television y VideoActive.

Dimensional Enrichment of Statistical Linked Open Data

On-Line Analytical Processing (OLAP) is a data analysis technique typically used for local and well-prepared data. However, initiatives like Open Data and Open Government bring new and publicly available data on the web that are to be analyzed in the same way. The use of semantic web technologies for this context is especially encouraged by the Linked Data initiative. There is already a considerable amount of statistical linked open data sets published using the RDF Data Cube Vocabulary (QB) which is designed for these purposes. However, QB lacks some essential schema constructs (e.g., dimension levels) to support OLAP. Thus, the QB4OLAP vocabulary has been proposed to extend QB with the necessary constructs and be fully compliant with OLAP. In this paper, we focus on the enrichment of an existing QB data set with QB4OLAP semantics. We first thoroughly compare the two vocabularies and outline the benefits of QB4OLAP. Then, we propose a series of steps to automate the enrichment of QB data sets with specific QB4OLAP semantics; being the most important, the definition of aggregate functions and the detection of new concepts in the dimension hierarchy construction. The proposed steps are defined to form a semi-automatic enrichment method, which is implemented in a tool that enables the enrichment in an interactive and iterative fashion. The user can enrich the QB data set with QB4OLAP concepts (e.g., full-fledged dimension hierarchies) by choosing among the candidate concepts automatically discovered with the steps proposed. Finally, we conduct experiments with 25 users and use three real-world QB data sets to evaluate our approach. The evaluation demonstrates the feasibility of our approach and shows that, in practice, our tool facilitates, speeds up, and guarantees the correct results of the enrichment process.

Nutrition for Elder Care: a nutritional semantic recommender system for the elderly

AbstractThe awareness and familiarity of elderly people with the use of new technologies have increased considerably in the last few years, which consequently cause a higher willingness to the use of these technologies in their daily lives. This allows the elderly to benefit from technology through active and conscious participation in activities related to health, leisure and promotion of social relationships, fostering active ageing. Three large dimensions cover almost a major part of health care within the framework of early and intermediate stages of active ageing: physical exercise, healthy nutrition and cognitive stimulation. In this paper, we present a nutritional recommender system, Nutrition for Elder Care, intended to help elderly users to draw up their own healthy diet plans following the nutritional experts guidelines. The system has been developed with the intensive use of Semantic Web technologies pursuing knowledge sharing and reuse between different applications and agents and the discovering of implicit new knowledge.

Linked data practice at different levels of semantic precision: The perspective of libraries, archives and museums

EDITOR'S SUMMARYLibraries, archives and museums rely on structured schemas and vocabularies to indicate classes in which a resource may belong. In the context of linked data, key organizational components are the RDF data model, element schemas and value vocabularies, with simple ontologies having minimally defined classes and properties in order to facilitate reuse and interoperability. Simplicity over formal semantics is a tenet of the open‐world assumption underlying ontology languages central to the Semantic Web, but the result is a lack of constraints, data quality checks and validation capacity. Inconsistent use of vocabularies and ontologies that do not follow formal semantics rules and logical concept hierarchies further complicate the use of Semantic Web technologies. The Simple Knowledge Organization System (SKOS) helps make existing value vocabularies available in the linked data environment, but it exchanges precision for simplicity. Incompatibilities between simple organized vocabularies, Resource Description Framework Schemas and OWL ontologies and even basic notions of subjects and concepts prevent smooth translations and challenge the conversion of cultural institutions' unique legacy vocabularies for linked data. Adopting the linked data vision requires accepting loose semantic interpretations. To avoid semantic inconsistencies and illogical results, cultural organizations following the linked data path must be careful to choose the level of semantics that best suits their domain and needs.

Using Semantic Web Technologies for Exploratory OLAP: A Survey

This paper describes the convergence of some of the most influential technologies in the last few years, namely data warehousing (DW), on-line analytical processing (OLAP), and the Semantic Web (SW). OLAP is used by enterprises to derive important business-critical knowledge from data inside the company. However, the most interesting OLAP queries can no longer be answered on internal data alone, external data must also be discovered (most often on the web), acquired, integrated, and (analytically) queried, resulting in a new type of OLAP, exploratory OLAP . When using external data, an important issue is knowing the precise semantics of the data. Here, SW technologies come to the rescue, as they allow semantics (ranging from very simple to very complex) to be specified for web-available resources. SW technologies do not only support capturing the “passive” semantics, but also support active inference and reasoning on the data. The paper first presents a characterization of DW/OLAP environments, followed by an introduction to the relevant SW foundation concepts. Then, it describes the relationship of multidimensional (MD) models and SW technologies, including the relationship between MD models and SW formalisms. Next, the paper goes on to survey the use of SW technologies for data modeling and data provisioning, including semantic data annotation and semantic-aware extract, transform, and load (ETL) processes. Finally, all the findings are discussed and a number of directions for future research are outlined, including SW support for intelligent MD querying, using SW technologies for providing context to data warehouses, and scalability issues.

A Context-aware Approach for Personalized Mobile Self-Assessment

With the increasing development of mobile technologies, the learning environment is currently undergoing a major shift. Access to contextual information in a mobile learning environment aims to meet the needs of learning and assessment personalization according to various learners' profiles and a range of learning contexts. Semantic Web technologies have been applied in recent years with different purposes in education. But, their applications for generating useful personalized mobile assessment resources have not been researched enough so far. In this paper, an approach making use of semantic Web technologies to support personalized self-assessment in mobile environments is described. Assessment techniques are formalized with First Order Logic rules which allow to personalize assessment activities. We also propose an algorithm for semantic assessment resources retrieval. Finally, a Mobile Semantic Web Assessment Personalization system is presented. The qualitative and quantitative evaluation of the proposed system is also provided.

Optimize Energy Efficiency in the Supply Chain of FMCGs with the Use of Semantic Web Technologies

Supply Chain Management is a critical domain for Fast Moving Consumer Goods (FMCGs). This domain is known for its complexity. New standards and regulations regarding Energy Efficiency and Environmental Aspects in general, as well as customer demand, make the analysis, modeling and design of the Supply Chain more and more complicated. Partners involved in these processes are numerous and of diverse background. To help solving this problem, common understanding of the domain and exchange of information among partners involved in the Supply Chain is of high importance. An ontology capturing the knowledge of the domain was created. To achieve maximum efficiency of the domain operations in terms of cost, quality of service and environmental impact, concept definitions from multiple sources were gathered. An advanced software solution that leverages semantic web technologies, enables users to link data from multiple Excel spreadsheets and relational databases together in real-time for data collection, collaboration, and reporting. In this framework, a new way for collaboration throughout the supply chain with the use of an underlying ontology, semantic technologies and visualization technics is introduced. The proposed approach is applied in the context of the FP7 European project e-SAVE.

A Context-Aware Framework to Provide Personalized Mobile Assessment

In mobile learning environment, context-aware systems refer to applications that employs contextual information to provide appropriate services to the leaners or other applications to perform a specific task. An important challenge in such applications is context modeling, using ontologies to model context information and to reason about context at a semantic level has attracted a lot of interest in the research community. Semantic Web technologies have been applied in recent years with different purposes in education. But, their applications for generating useful personalized mobile assessment resources have not been researched enough so far.In this paper, we introduce a context-aware approach that makes use of Semantic Web technologies to support personalized assessment in mobile environments. We propose a Service-based framework for bringing assessment techniques to mobile environment. We provide a formal description for our mobile assessment framework and detail the functionalities of its various layers. We have carried out also an experiment with computer science university students to evaluate our mobile assessment framework.

Lessons learnt from the deployment of a semantic virtual research environment

The ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a platform to support multi-disciplinary research groups. This paper introduces the main semantic components of the system: a framework to capture the provenance of the research process, a collection of services to create and visualise metadata and a policy reasoning service. We also describe different approaches to authoring and accessing metadata within the VRE. Using evidence gathered from data provided by the users of the system we discuss the lessons learnt from deployment with three case study groups.

Health information professionals and the Semantic Web: a symbiotic relationship?

Objective - To identify opportunities for health information professionals to participate in the ongoing devel- opment of the Semantic Web and to investigate the benefits promised by emerging semantic technologies. Methods -A search of two biomedical databases (MEDLINE, CINAHL), three information science databases (LISTA, LISA, and Li- brary Literature), and Web-published literature retrieved articles on core Semantic Web concepts that relate to the prac- tice of information professionals and the use of Semantic Web technologies in a health care context. Articles that focused solely on Semantic Web architecture and similar technology-focused literature were not selected for inclusion. A basic thematic analysis was performed to identify trends in the selected literature. Results - Five key areas of profes- sional focus emerged as themes: ontology development, knowledge translation, information retrieval, scientific publish- ing, and resource classification and indexing. Discussion - Health information professionals have a role to play in the development of a powerful and nuanced biomedical Semantic Web. Rather than making traditional medical library posi- tions obsolete, the Semantic Web could present new opportunities for information professionals within the five identi- fied areas of professional focus. In turn, semantic technologies developed with the input of experienced health information professionals have the potential to transform the practice of these professionals, particularly within the five aforementioned areas.

Towards a Holistic Framework for the Evaluation of Emergency Plans in Indoor Environments

One of the most promising fields for ambient intelligence is the implementation of intelligent emergency plans. Because the use of drills and living labs cannot reproduce social behaviors, such as panic attacks, that strongly affect these plans, the use of agent-based social simulation provides an approach to evaluate these plans more thoroughly. (1) The hypothesis presented in this paper is that there has been little interest in describing the key modules that these simulators must include, such as formally represented knowledge and a realistic simulated sensor model, and especially in providing researchers with tools to reuse, extend and interconnect modules from different works. This lack of interest hinders researchers from achieving a holistic framework for evaluating emergency plans and forces them to reconsider and to implement the same components from scratch over and over. In addition to supporting this hypothesis by considering over 150 simulators, this paper: (2) defines the main modules identified and proposes the use of semantic web technologies as a cornerstone for the aforementioned holistic framework; (3) provides a basic methodology to achieve the framework; (4) identifies the main challenges; and (5) presents an open and free software tool to hint at the potential of such a holistic view of emergency plan evaluation in indoor environments.

Archival description and linked data: a preliminary study of opportunities and implementation challenges

This paper presents the results of a study to investigate how archives can connect their collections to related data sources through the use of Semantic Web technologies, specifically Linked Data. Questions explored included (a) What types of data currently available in archival surrogates such as Encoded Archival Description (EAD) finding aids and Machine-Readable Cataloging (MARC) records may be useful if converted to Linked Data? (b) For those potentially useful data points identified in archival surrogates, how might one align data structures found in those surrogates to the data structures of other relevant internal or external information sources? (c) What features of current standards and data structures present impediments or challenges that must be overcome in order to achieve interoperability among disparate data sources? To answer these questions, the researcher identified metadata elements of potential use as Linked Data in archival surrogates, as well as metadata element sets and vocabularies of data sets that could serve as pathways to relevant external data sources. Data sets chosen for the study included DBpedia and schema.org; metadata element sets examined included Friend of a Friend (FOAF), GeoNames, and Linking Open Description of Events (LODE). The researcher then aligned tags found in the EAD encoding standard to related classes and properties found in these Linked Data sources and metadata element sets. To investigate the third question about impediments to incorporating Linked Data in archival descriptions, the researcher analyzed the locations and frequencies at which controlled and uncontrolled access points (personal and family name, corporate name, geographic name, and genre/form entities) appeared in a sample of MARC and EAD archival descriptive records by using a combination of hand counts and the natural language processing (NLP) tool, OpenCalais. The results of the location and frequency analysis, combined with the results of the alignment process, helped the researcher identify several critical challenges currently impeding interoperability among archival information systems and relevant Linked Data sources, including differences in granularity between archival and other data source vocabularies, and inadequacies of current encoding standards to support semantic tagging of potential access points embedded in free text areas of archival surrogates.

Lessons Learnt from the Deployment of a Semantic Virtual Research Environment

The ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a platform to support multi-disciplinary research groups. This paper introduces the main semantic components of the system: a framework to capture the provenance of the research process, a collection of services to create and visualise metadata and a policy reasoning service. We also describe different approaches to authoring and accessing metadata within the VRE. Using evidence gathered from data provided by the users of the system we discuss the lessons learnt from deployment with three case study groups.

World of Trivia: A Player versus Player Game in the Web of Data with User Generated Content

Digital games have become an integral part of the culture of the new generations. Edutainment and Games Based Learning (GBL) seem to have found their place within the overall educational process, as “traditional teaching” methods are increasingly considered inefficient in providing the required learning outcomes. This paper presents World of Trivia, an online multiplayer game developed within the Facebook environment through the use of the node.js platform, one of the most modern server-side techniques for online gaming. The game presented retrieves its content from DBpedia, the Wikipedia knowledge base, through the use of Semantic Web technologies. World of Trivia provides an excellent environment for Internet users to challenge themselves either in single player or multiplayer mode by answering questions on the various thematic domains that Wikipedia Open Content provides, combining in this way entertainment with education.