The usability of semantic search tools:a review

The goal of semantic search is to improve on traditional search methods by exploiting the semantic metadata. In this paper, we argue that supporting iterative and exploratory search modes is important to the usability of all search systems. We also identify the types of semantic queries the users need to make, the issues concerning the search environment and the problems that are intrinsic to semantic search in particular. We then review the four modes of user interaction in existing semantic search systems, namely keyword-based, form-based, view-based and natural language-based systems. Future development should focus on multimodal search systems, which exploit the advantages of more than one mode of interaction, and on developing the search systems that can search heterogeneous semantic metadata on the open semantic Web.

Semantic annotation for knowledge management:requirements and a survey of the state of the art

While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.

Agile Case Study Evaluation In Middle Size Project

In the last few years Agile methodologies appeared as a reaction to traditional ways of developing software and acknowledge the need for an alternative to documentation driven, heavyweight software development processes. This paper shortly presents a combination between Rational Uni ed Process and an agile approach for software development of e-business applications. The resulting approach is described stressing on the strong aspects of both combined methodologies. The article provides a case study of the proposed methodology which was developed and executed in a successful e-project in the area of the embedded systems.

Application of Network Technologies for Development of Medical Data-advisory Clinic “Med-Health”

In this article the medical data-advisory web-resource developed by authors is considered. This resource allows carrying out information interchange between consumers of medical services and the medical establishments which give these services, and firms-manufacturers of medical equipment and medicaments. Main sections of this web-site, their purposes and capabilities are considered in this article.

Web-Based Information Systems in the Stock Market Financial Information Domain

The information domain is a recognised sphere for the influence, ownership, and control of information and it's specifications, format, exploitation and explanation (Thompson, 1967). The article presents a description of the financial information domain issues related to the organisation and operation of a stock market. We review the strategic, institutional and standards dimensions of the stock market information domain in relation to the current semantic web knowledge and how and whether this could be used in modern web based stock market information systems to provide the quality of information that their stakeholders want. The analysis is based on the FINE model (Blanas, 2003). The analysis leads to a number of research questions for future research.

A Sensitive Metric of Class Cohesion

Metrics estimate the quality of different aspects of software. In particular, cohesion indicates how well the parts of a system hold together. A metric to evaluate class cohesion is important in object-oriented programming because it gives an indication of a good design of classes. There are several proposals of metrics for class cohesion but they have several problems (for instance, low discrimination). In this paper, a new metric to evaluate class cohesion is proposed, called SCOM, which has several relevant features. It has an intuitive and analytical formulation, what is necessary to apply it to large-size software systems. It is normalized to produce values in the range [0..1], thus yielding meaningful values. It is also more sensitive than those previously reported in the literature. The attributes and methods used to evaluate SCOM are unambiguously stated. SCOM has an analytical threshold, which is a very useful but rare feature in software metrics. We assess the metric with several sample cases, showing that it gives more sensitive values than other well know cohesion metrics.

Adjusting WSMO API Reference Implementation to Support More Reliable Entity Persistence

* The research has been partially supported by INFRAWEBS - IST FP62003/IST/2.3.2.3 Research Project No. 511723 and “Technologies of the Information Society for Knowledge Processing and Management” - IIT-BAS Research Project No. 010061.

Enhancing visibility in EPCIS governing agri-food supply chains via linked pedigrees

Data integration for the purposes of tracking, tracing and transparency are important challenges in the agri-food supply chain. The Electronic Product Code Information Services (EPCIS) is an event-oriented GS1 standard that aims to enable tracking and tracing of products through the sharing of event-based datasets that encapsulate the Electronic Product Code (EPC). In this paper, the authors propose a framework that utilises events and EPCs in the generation of "linked pedigrees" - linked datasets that enable the sharing of traceability information about products as they move along the supply chain. The authors exploit two ontology based information models, EEM and CBVVocab within a distributed and decentralised framework that consumes real time EPCIS events as linked data to generate the linked pedigrees. The authors exemplify the usage of linked pedigrees within the fresh fruit and vegetables supply chain in the agri-food sector.

A knowledge driven approach towards the validation of externally acquired traceability datasets in supply chain business processes

The sharing of near real-time traceability knowledge in supply chains plays a central role in coordinating business operations and is a key driver for their success. However before traceability datasets received from external partners can be integrated with datasets generated internally within an organisation, they need to be validated against information recorded for the physical goods received as well as against bespoke rules defined to ensure uniformity, consistency and completeness within the supply chain. In this paper, we present a knowledge driven framework for the runtime validation of critical constraints on incoming traceability datasets encapuslated as EPCIS event-based linked pedigrees. Our constraints are defined using SPARQL queries and SPIN rules. We present a novel validation architecture based on the integration of Apache Storm framework for real time, distributed computation with popular Semantic Web/Linked data libraries and exemplify our methodology on an abstraction of the pharmaceutical supply chain.

Semantic patterns for sentiment analysis of Twitter

Most existing approaches to Twitter sentiment analysis assume that sentiment is explicitly expressed through affective words. Nevertheless, sentiment is often implicitly expressed via latent semantic relations, patterns and dependencies among words in tweets. In this paper, we propose a novel approach that automatically captures patterns of words of similar contextual semantics and sentiment in tweets. Unlike previous work on sentiment pattern extraction, our proposed approach does not rely on external and fixed sets of syntactical templates/patterns, nor requires deep analyses of the syntactic structure of sentences in tweets. We evaluate our approach with tweet- and entity-level sentiment analysis tasks by using the extracted semantic patterns as classification features in both tasks. We use 9 Twitter datasets in our evaluation and compare the performance of our patterns against 6 state-of-the-art baselines. Results show that our patterns consistently outperform all other baselines on all datasets by 2.19% at the tweet-level and 7.5% at the entity-level in average F-measure.

SentiCircles for contextual and conceptual semantic sentiment analysis of Twitter

Lexicon-based approaches to Twitter sentiment analysis are gaining much popularity due to their simplicity, domain independence, and relatively good performance. These approaches rely on sentiment lexicons, where a collection of words are marked with fixed sentiment polarities. However, words' sentiment orientation (positive, neural, negative) and/or sentiment strengths could change depending on context and targeted entities. In this paper we present SentiCircle; a novel lexicon-based approach that takes into account the contextual and conceptual semantics of words when calculating their sentiment orientation and strength in Twitter. We evaluate our approach on three Twitter datasets using three different sentiment lexicons. Results show that our approach significantly outperforms two lexicon baselines. Results are competitive but inconclusive when comparing to state-of-art SentiStrength, and vary from one dataset to another. SentiCircle outperforms SentiStrength in accuracy on average, but falls marginally behind in F-measure. © 2014 Springer International Publishing.

Article Disassembly - New Ways to Handle Information in Publications

ACM Computing Classification System (1998): I.7.4.

Europeana Creative. EDM Endpoint. Custom Views

The paper discusses the Europeana Creative project which aims to facilitate re-use of cultural heritage metadata and content by the creative industries. The paper focuses on the contribution of Ontotext to the project activities. The Europeana Data Model (EDM) is further discussed as a new proposal for structuring the data that Europeana will ingest, manage and publish. The advantages of using EDM instead of the current ESE metadata set are highlighted. Finally, Ontotext’s EDM Endpoint is presented, based on OWLIM semantic repository and SPARQL query language. A user-friendly RDF view is presented in order to illustrate the possibilities of Forest - an extensible modular user interface framework for creating linked data and semantic web applications.

Персональная цифровая библиотека Libmeta как среда интеграции связанных открытых данных

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

Preface

The Semantic Web has come a long way since its inception in 2001, especially in terms of technical development and research progress. However, adoption by non- technical practitioners is still an ongoing process, and in some areas this process is just now starting. Emergency response is an area where reliability and timeliness of information and technologies is of essence. Therefore it is quite natural that more widespread adoption in this area has not been seen until now, when Semantic Web technologies are mature enough to support the high requirements of the application area. Nevertheless, to leverage the full potential of Semantic Web research results for this application area, there is need for an arena where practitioners and researchers can meet and exchange ideas and results. Our intention is for this workshop, and hopefully coming workshops in the same series, to be such an arena for discussion. The Extended Semantic Web Conference (ESWC - formerly the European Semantic Web conference) is one of the major research conferences in the Semantic Web field, whereas this is a suitable location for this workshop in order to discuss the application of Semantic Web technology to our specific area of applications. Hence, we chose to arrange our first SMILE workshop at ESWC 2013. However, this workshop does not focus solely on semantic technologies for emergency response, but rather Semantic Web technologies in combination with technologies and principles for what is sometimes called the "social web". Social media has already been used successfully in many cases, as a tool for supporting emergency response. The aim of this workshop is therefore to take this to the next level and answer questions like: "how can we make sense of, and furthermore make use of, all the data that is produced by different kinds of social media platforms in an emergency situation?" For the first edition of this workshop the chairs collected the following main topics of interest: • Semantic Annotation for understanding the content and context of social media streams. • Integration of Social Media with Linked Data. • Interactive Interfaces and visual analytics methodologies for managing multiple large-scale, dynamic, evolving datasets. • Stream reasoning and event detection. • Social Data Mining. • Collaborative tools and services for Citizens, Organisations, Communities. • Privacy, ethics, trustworthiness and legal issues in the Social Semantic Web. • Use case analysis, with specific interest for use cases that involve the application of Social Media and Linked Data methodologies in real-life scenarios. All of these, applied in the context of: • Crisis and Disaster Management • Emergency Response • Security and Citizen Journalism The workshop received 6 high-quality paper submissions and based on a thorough review process, thanks to our program committee, the decision was made to accept four of these papers for the workshop (67% acceptance rate). These four papers can be found later in this proceedings volume. Three out of four of these papers particularly discuss the integration and analysis of social media data, using Semantic Web technologies, e.g. for detecting complex events in social media streams, for visualizing and analysing sentiments with respect to certain topics in social media, or for detecting small-scale incidents entirely through the use of social media information. Finally, the fourth paper presents an architecture for using Semantic Web technologies in resource management during a disaster. Additionally, the workshop featured an invited keynote speech by Dr. Tomi Kauppinen from Aalto university. Dr. Kauppinen shared experiences from his work on applying Semantic Web technologies to application fields such as geoinformatics and scientific research, i.e. so-called Linked Science, but also recent ideas and applications in the emergency response field. His input was also highly valuable for the roadmapping discussion, which was held at the end of the workshop. A separate summary of the roadmapping session can be found at the end of these proceedings. Finally, we would like to thank our invited speaker Dr. Tomi Kauppinen, all our program committee members, as well as the workshop chair of ESWC2013, Johanna Völker (University of Mannheim), for helping us to make this first SMILE workshop a highly interesting and successful event!