The use of ontologies for effective knowledge modelling and information retrieval

© 2017 The dramatic increase in the use of knowledge discovery applications requires end users to write complex database search requests to retrieve information. Such users are not only expected to grasp the structural complexity of complex databases but also the semantic relationships between data stored in databases. In order to overcome such difficulties, researchers have been focusing on knowledge representation and interactive query generation through ontologies, with particular emphasis on improving the interface between data and search requests in order to bring the result sets closer to users research requirements. This paper discusses ontology-based information retrieval approaches and techniques by taking into consideration the aspects of ontology modelling, processing and the translation of ontological knowledge into database search requests. It also extensively compares the existing ontology-to-database transformation and mapping approaches in terms of loss of data and semantics, structural mapping and domain knowledge applicability. The research outcomes, recommendations and future challenges presented in this paper can bridge the gap between ontology and relational models to generate precise search requests using ontologies. Moreover, the comparison presented between various ontology-based information retrieval, database-to-ontology transformations and ontology-to-database mappings approaches provides a reference for enhancing the searching capabilities of massively loaded information management systems

E-MDAV: A Framework for Developing Data-Intensive Web Applications

The ever-increasing adoption of innovative technologies, such as big data and cloud computing, provides significant opportunities for organizations operating in the IT domain, but also introduces considerable challenges. Such innovations call for development processes that better align with stakeholders needs and expectations. In this respect, this paper introduces a development framework based on the OMG's Model Driven Architecture (MDA) that aims to support the development lifecycle of data-intensive web applications. The proposed framework, named E-MDAV (Extended MDA-VIEW), defines a methodology that exploits a chain of model transformations to effectively cope with both forward- and reverse-engineering aspects. In addition, E-MDAV includes the specification of a reference architecture for driving the implementation of a tool that supports the various professional roles involved in the development and maintenance of data-intensive web applications. In order to evaluate the effectiveness of the proposed E-MDAV framework, a tool prototype has been developed. E-MDAV has then been applied to two different application scenarios and the obtained results have been compared with historical data related to the implementation of similar development projects, in order to measure and discuss the benefits of the proposed approach

Web Data Extraction, Applications and Techniques: A Survey

Web Data Extraction is an important problem that has been studied by means of different scientific tools and in a broad range of applications. Many approaches to extracting data from the Web have been designed to solve specific problems and operate in ad-hoc domains. Other approaches, instead, heavily reuse techniques and algorithms developed in the field of Information Extraction. This survey aims at providing a structured and comprehensive overview of the literature in the field of Web Data Extraction. We provided a simple classification framework in which existing Web Data Extraction applications are grouped into two main classes, namely applications at the Enterprise level and at the Social Web level. At the Enterprise level, Web Data Extraction techniques emerge as a key tool to perform data analysis in Business and Competitive Intelligence systems as well as for business process re-engineering. At the Social Web level, Web Data Extraction techniques allow to gather a large amount of structured data continuously generated and disseminated by Web 2.0, Social Media and Online Social Network users and this offers unprecedented opportunities to analyze human behavior at a very large scale. We discuss also the potential of cross-fertilization, i.e., on the possibility of re-using Web Data Extraction techniques originally designed to work in a given domain, in other domains.Comment: Knowledge-based System

A New Design for Open and Scalable Collaboration of Independent Databases in Digitally Connected Enterprises

“Digitally connected enterprises” refers to e-business, global supply chains, and other new business designs of the Knowledge Economy; all of which require open and scalable information supply chains across independent enterprises. Connecting proprietarily designed and controlled enterprise databases in these information supply chains is a critical success factor for them. Previous connection designs tend to rely on “hard-coded” regimes, which do not respond well to disruptions (including changes and failures), and do not afford these enterprises sufficient flexibility to join simultaneously in multiple supply chain regimes and share information for the benefit of all. The paper develops a new design: It combines matchmaking with global database query, and thereby supports the interoperation of independent databases to form on-demand information supply chains. The design provides flexible (re-)configuration to decrease the impact of disruption, and proactive control to increase collaboration and information sharing. More broadly, the papers results contribute to a new Information System design method for massively extended enterprises, and facilitate new business designs using digital connections at the level of databases

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

Needs of Service Identification for Service-Oriented Business Process Management

Since the trend of adopting SOA into enterprise applications, the needs for definition and identification of services have been recognized. There is a growing body of research carried out on the identification of different types of services. Identifying right granularity services is important: if the service is of large size, it goes against the reusability principle of SOA, whereas if the service is of small size, then it causes unnecessary computing power for implementing any business functions. Without a formal (semi)- automatic approach to identify services, it is difficult in migrating existing systems into service-oriented systems. This paper explores the need for service identification for service-oriented business process management systems. The current approaches, techniques and methods of service identification are reviewed, and limitations of the each approach is analysed. New requirements and techniques are demonstrated in creating improved dynamic services with consideration for interoperability, modularity, reusability within information environment

Web and Semantic Web Query Languages

A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion

Dagstuhl News January - December 2001

"Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic