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Spatio-temporal database is a new type of database that manages spatio-temporal objects and supports corresponding query languages. Term moving objects databases is today used as a synonym for spatiotemporal databases managing spatial objects with continuously changing location and/or extend. DSMS (Data Stream Management System) is an extension of a DBMS (Database Management System) that efficiently manages potentially unbound data streams as well as standard relations and supports continuous queries in addition to standard one-time queries. By combining these two systems, we get a system that manages moving objects whose position is determined by one or more data streams. In this paper we present a data model consisting of data types and operations needed to support spatio-temporal data in data streams. Defined data model is illustrated through an SQL-like query language.

This paper gives an overview of web personalization approaches and techniques and explains possible ways of introducing the semantics into the web personalization process. Theoretical models of personalization are presented as base models for different semantic approaches to personalization and evaluated from aspect of usability. Existing semantic personalization models and systems are described and the level of improvement they achieve is discussed, with emphasis on personalization accuracy. The initial idea for including personalization into the existing semantic web portal "Sweb" is presented. Proposed approach combines social networking data with semantic reasoning based personalization technique to increase the accuracy of recommendations.

At the moment, the field of Semantic Web is lacking methodologies for development of Semantic Web solutions. We argue that existing methodologies are no longer relevant because of the constant technological changes in the field of Semantic Web as well as in the Web development. We also argue that providing unique development methodology for all Semantic Web applications is not satisfactorily and that specialization of methodologies is needed. To establish foundation for such methodologies we conducted an analysis of Semantic Web solutions resulting in a categorization of Semantic Web applications. In this paper we present our categorization scheme and provide precise definitions for each of the identified categories.

A multidatabase system (MDBS) is a software package that allows user transactions to invoke retrieval and update instructions against data located in autonomous heterogeneous hardware and software environments. Here, the Tanagra Project is presented, a large part of which is a simple MDBS API. This API is introduced, and the Data Model it uses is described. The layers of the API and the tasks and capabilities of each layer are defined. Ways of handling standard data operations are shown. Possible extensions of the API are discussed, as well as its limitations and shortcomings.

Credit card fraud is a serious and ever-growing problem with billions of dollars lost every year due to fraudulent transactions. Fraud has always been present and will always be. It is also ever changing, as the technology and usage patterns change over time, which makes CCFD (credit card fraud detection) a particularly hard problem. Traditionally, fraud detection relied solely on domain experts’ detection rules, but in the past decade or two, such solutions are being augmented with data mining models for fraud detection. The progress in this area is impeded both by the sensitive nature of the data and great commercial potential – the industrial solutions are understandably kept secret and authentic datasets are rare and few. In this paper we study the CCFD problem with its typical problems and state of the art solution. We survey the recent literature and bring a structured overview of relevant fraud detection features and data mining approaches to this problem.

Currently, the World Wide Web is mostly composed of isolated and loosely connected "data islands". Connecting them together and retrieving only the information that is of interest to the user is the common Web usage process. Creating infrastructure that would support automation of that process by aggregating and integrating Web data in accordance to user's personal preferences would greatly improve today's Web usage. A significant part of Web data is available only through the login and password protected applications. As that data is very important for the usefulness of described process, proposed infrastructure needs to support authorized access to user's personal data. In this paper we propose a semantically enhanced Web portal that presents unique personalized user's entry to the domain-specific Web information. We also propose an identity management system that supports authorized access to the protected Web data. To verify the proposed solution, we have built Sweb - a semantically enhanced Web portal that uses proposed identity management system.

For a peer-to-peer(P2P) content sharing network holding large amount of data, an efficient semantic based search mechanism is a key requisite. Semantic based search should generate as little traffic (messages) possible while achieving precision and recall rates comparable to those of correspondent centralized system. In this paper protocols for self-organizing P2P networks that arranges links between peers according to peer's content are developed and tested. Peers organize themselves into "semantic communities" without losing links to other semantic communities. Proposed network requires no prior knowledge of the semantics of documents that are to be shared in the system. Through simulations, it is shown that proposed network is resilient to membership changes and achieves high recall rates.

With increasing student mobility and boom of the international student exchange programmes, a need arises for unifying and presenting information about academic study programmes on the Web. Publishing study programmes using semantic web technologies enables students to easily search and select study topic of their interest. In this paper, we discuss the way to transform data from production-grade information system’s relational database to semantic data. The process of transforming starts with building ontology for describing study programmes. Data from relational database is mapped to the semantic model. Finally, we present the study programmes from semantic model which are used by the web application. Project presented in this paper took first step in introducing ISVU to semantic web and demonstrated possibility to integrate data about academic programmes.

HEIS (Higher Education Information System) is a project funded by the Croatian Ministry of Science, Education and Sports started in the year 2001. HEIS is a comprehensive information system that provides support for education related processes taking place within a higher education institution. As a part of the project, a data warehouse was developed to provide reporting and analytical features. This paper presents the HEIS data warehouse architecture, comments on the data model and addresses issues (and our solutions) that arose during the seven-year development and maintenance period. Foremost, we address improvements in the ETL process and maintenance process.

We are proposing a multi-meta model that serves as afoundation for schema reuse in conceptual database design. Multimetamodel is based on entity-relationship model. According to theproposed model corresponding database, called multi-meta databaseis built. Multi-meta database contains descriptions of the existingdatabase models and serves as a basis for design of new models. Toavoid ambiguity regarding the model descriptions the redundancy hasbeen maximally reduced without loss of any existing knowledge. Theprocess of the design of a new database model can cause therestructuring of existing knowledge contained in the multi-metadatabase. In the proposed non-redundant model the restructuring issimplified, while the consistencies are preserved. The necessaryconditions that have to be satisfied by each database model aredefined. In case that these conditions are not met, the describedprocedures for the model restructuring have to be applied.

Data warehouse is a copy of transaction data specifically structured for query and analysis [1]. Within data warehouse, data is usually stored in a dimensional model. On-Line Analytical Processing (OLAP) is an approach to analysis and reporting that enables a user to easily and selectively extract and view data from different points of view based on a multidimensional data structure called a cube [2]. There are numerous data warehousing platforms available on the market. Exhaustive data warehousing platform comprises of data warehouse server, OLAP server and some data mining functionality. There are no present standards to support interoperability between different OLAP systems. In this article, two major initiatives towards standardization are examined: XMLA and JOLAP. Web service is a piece of business logic, located somewhere on the Internet, that is accessible through standard-based Internet protocols such as HTTP or SMTP [3]. Web services are neither language nor platformspecific. Using Java programming language, general purpose client tool prototype for standardized OLAP data access is developed. Client communicates with OLAP data source through web service and is based on XMLA 1.1. specification. It is concluded that the client encompasses satisfactory set of functionalities.

Spatio-temporal database is a new type of database that manages spatio-temporal objects and supports corresponding query languages. If position and/or extent of an objects changes continuously, we talk about moving object database. A moving objects database supports a number of data types that could be termed moving. Standard and spatial operations on non-moving data types can be applied to moving data types through a process called temporal lifting. In this paper, an implementation of spatio-temporal data types based on Java extended with parametric polymorphism is explored. A framework for implementing moving data types is presented, with emphasis on the concept of temporal lifting and implementation of lifted operations using Java genericity capabilities.

In the late 1970s and the early 1980s, the term and the idea of the information society emerged. Since then, it has been witnessed the substantial changes in society as a whole, the changes that stemmed from the development of the new information and communication technologies. The Internet has been changing the world we live in and its popularity has been shaping up the need for education. Elearning, a segment of the information society, is today transforming from the basic utilization of ICT as means of learning into new forms of education and training that emphasize creativity and team work as the new requirements imposed by the society of knowledge. This fact in turn requires a substantial shift of stress from technology, network links and the Internet to an enhanced study of the context of learning and the need for cooperation and communication.