Valentina Janev

Semantic Web Technologies: Ready for Adoption?

A review of semantic Web use in the EU shows that its related technologies are finding their way into real-world applications. Rather than being a fashionable research issue, the semantic Web is slowly but surely becoming a reality.

Applicability assessment of Semantic Web technologies

The Semantic Web is one of the fastest developing fields within the Information and Communication Technology sector and, as such, under constant examination by scientists and IT professionals. This article aims to provide a better understanding of the applicability of Semantic Web tools and technologies in practice. This aim will be achieved by surveying the recommended and emerging W3C standards, presenting an overview of the state-of-the-art in the Semantic Web research in the European Union, analysing the W3C collection of Case studies and Use Cases, and discussing the extent of adoption of Semantic Web technologies. The overall technology maturity level assessment has shown that Semantic Web technologies are finding their ways into real-world applications, and that, rather than being merely a fashionable research issue, the Semantic Web, slowly but surely, becomes our reality.

Lifting Open Data Portals to the Data Web

Recently, a large number of open data repositories, catalogs and portals have been emerging in the scientific and government realms. In this chapter, we characterise this newly emerging class of information systems. We describe the key functionality of open data portals, present a conceptual model and showcase the pan-European data portal PublicData.eu as a prominent example. Using examples from Serbia and Poland, we present an approach for lifting the often semantically shallow datasets registered at such data portals to Linked Data in order to make data portals the backbone of a distributed global data warehouse for our information society on the Web.

Modeling, Fusion and Exploration of Regional Statistics and Indicators with Linked Data Tools

This paper contributes to the understanding of challenges related to publishing and consuming public sector information using Linked Data tools. Linked Data paradigm has opened new possibilities and perspectives for the process of collecting and monitoring socio-economic indicators. Due to multidimensionality of the statistical data, in order to ensure efficient exploration and analysis, hierarchical data structures are needed for modeling the space and time dimensions. This paper presents several illustrative examples of modeling, analyzing and visualization of Linked Data from Serbian government bodies. The approach utilizes tools from the Linked Data stack, as well as the first prototype of the Exploratory Spatio-Temporal Analysis component that has been developed in the GeoKnow project framework.

Supporting the Linked Data Life Cycle Using an Integrated Tool Stack

The core of a Linked Data application is the processing of the knowledge expressed as Linked Data. Therefore the creation, management, curation and publication of Linked Data are critical aspects for an application’s success. For all of these aspects the LOD2 project provides components. These components have been collected and placed under one distribution umbrella: the LOD2 stack. In this chapter we will introduce this component stack. We will show how to get access; which component covers which aspect of the Linked Data life cycle and how using the stack eases the access to Linked Data management tools. Furthermore we will elaborate how the stack can be used to support a knowledge domain. The illustrated domain is statistical data.

Semantic Web Based Integration of Knowledge Resources for Expertise Finding

This article discusses the challenges of expertise data integration and expert finding in modern organizations using an illustrative case study of a concrete research-intensive establishment, the Mihajlo Pupin Institute (MPI). It presents how the latest semantic technologies (Ontologies, Web services, Semantic Wiki) could be used on the top of the commercial ERP (Enterprise Resource Planning) software (SAP®) and the open-source ECM (Enterprise Content Management) software (Alfresco) to ensure meaningful search and retrieval of expertise for in-house users, as well as the integration into the Semantic Web community space. This article points out the necessary adjustments in enterprise knowledge management infrastructure in the light of uprising initiatives for standardization of the Semantic Web data.

Comparative Analysis of Commercial Knowledge Management Solutions and their Role in Enterprises

Knowledge technologies are a subject of permanent interest for software engineers at research organisations, as well as for market analysts in commercial organisations. In this paper, which aims to clarify the role of knowledge management solutions in an enterprise business, we survey the market of commercial knowledge management solutions and analyse their functionalities in domains such as document management, information retrieval, collaboration, decision support, e-learning, business automation and enterprise integration. The survey is based on a thorough study of web resources of knowledge management solution providers. Regarding the role of knowledge solutions in the business process, the present study will show that on an operational level they serve for better utilisation of the enterprise knowledge resources and, on a strategic level, they synthesise new knowledge needed for better management of customers, suppliers and partners. This paper gives an insight into the knowledge management market that can help strategic planners to easily begin a knowledge management initiative.

Exploratory spatio-temporal analysis of linked statistical data

Abstract Publishing and sharing open government data in Linked Data format provides many opportunities in terms of data aggregation/integration and creation of information mashups. Statistical data, that contains various performance indicators and their evolution through time, is an example of data that can be used as the foundation for policy prediction, planning and adjustments, and can be re-used in different applications. However, due to Linked Data being relatively a new field, currently there is a lack of tools that enable efficient exploration and analysis of linked geospatial statistical datasets. Therefore, ESTA-LD (Exploratory Spatio-Temporal Analysis) tool was developed to address some of the Linked statistical Data management issues, such as crossing the statistical and the geographical dimensions, producing statistical maps, visualizing different measures, and comparing statistical indicators of different regions through time. This paper discusses the modeling approach that was adopted so that the published data conform to the established standards for representing statistical, spatial and temporal data in Linked Data format. The main contribution is related to the delivery of state-of-the-art open-source tools for retrieving, quality assessment, exploration and analysis of statistical Linked Data that is made available through a SPARQL endpoint.

Ontology enabled decision support system for emergency management at airports

This paper presents the first prototype of the EMILI-SITE system that will provide an advanced simulation and training capabilities for emergency management in critical infrastructures like airports, railway/metro systems, and power grids. In addition, the EMILI-SITE system will support decision-making activities in safety-critical situations in timely manner. The prototype provides a proof-of-concept in the early phase of the EMILI project and demonstrates the applicability of advanced technologies such as complex event processing, semantic technologies and web services in mission-critical applications.

Application of Complex Event Processing Paradigm in Situation Awareness and Management

This paper describes a novel approach to situation awareness and management in critical infrastructures using an emerging Complex Event Processing paradigm in combination with ECA (Event Condition Action) rules. Every modern infrastructural facility, especially critical ones, would want to catch or predict exceptions and threats at the earliest possible moment. The crucial prerequisite for this is a holistic and accurate situation assessment. To be able to assess the situation, evaluate the risk and provide decision support to the emergency managers, we need to define event chains that identify what is normal, compliant and expected, and what is exceptional and/or dangerous. These problems introduce a novel genre of applications - event-driven applications that make automated decisions based on a complex event or pattern of events, their detection, correlation and aggregation. In cases where an automated reaction is not possible, a recommendation is given to a human operator who remains in the control loop.