Security of information systems is an increasingly critical issue. Access control is a crucial technique ensuring security. It should be based on an effective model. Even if some approaches have already been proposed, a comprehensive model, flexible enough to cope with real organizations, is still missing. This paper proposes a new access control model, FORBAC, which deals with the following issues: The first one is the adaptability to various kinds of organization. The second one concerns increasing flexibility and reducing errors and management cost, this is done by introducing a set of components which allow fine-grained and multi-level permission assignment. The paper introduces a framework for evaluating the proposed approach with respect to other related research through views, facets and criteria.
In this paper a software architecture design process based on a supportable meta-architecture (SMA) and roundtrip engineering is proposed for large software projects. Our process is applied after the requirements elicitation and analysis phases of a software project. The process begins with designing a SMA aimed at minimizing and managing software complexity. The meta-architecture should be highly supportable, i.e. understandable, maintainable, scalable, and portable and based on software engineering principles particularly object oriented design techniques, design patterns and frameworks. Roundtrip engineering embraces various supportability metrics to ensure that the implementation conforms to the meta-architecture and that the resulting system at the end of each development iteration period is supportable. Two project case studies using this design process are also presented in the paper.
Contextual ontologies are ontologies that characterize a concept by a set of properties that vary according to context. Contextual ontologies are now crucial for users who intend to exchange information in a domain. Existing ontology languages are not capable of defining such type of ontologies. The objective of this paper is to formally define a contextual ontology language to support the development of contextual ontologies. In this paper, we use description logics as an ontology language and then we extend it by introducing a new contextual constructor.
In this paper we discuss how knowledge integration throughout system analysis, modelling and development courses can be stimulated by giving an overview of our MIRO-project at K.U.Leuven. This includes offering an online knowledge base of all-embracing case studies, structured according to the Zachman framework. Supported by collaborative groupware, students not only get the opportunity to consult and compare solutions for the case studies, but also actively discuss and contribute to alternative solutions. In this Problem Based Learning (PBL)-context, students are able to influence and understand the development of a certain process through interactive computerized animations and demos.
In Constraint Programming, enumeration strategies are crucial for resolution performances. The effect of strategies is generally unpredictable. In a previous work, we proposed to dynamically change strategies showing bad performances, and to use metabacktrack to restore better states when bad decisions were made. In this paper, we design and evaluate strategies to improve resolution performances of a set of problems. Experimental results show the effectiveness of our approach.
The aim of this paper is to investigate the feasibility of predicting the gender of a text document's author using linguistic evidence. For this purpose, term- and style-based classification techniques are evaluated over a large collection of chat messages. Prediction accuracies up to 84.2% are achieved, illustrating the applicability of these techniques to gender prediction. Moreover, the reverse problem is exploited, and the effect of gender on the writing style is discussed.
According to increase of spatial data, many decision support systems require the fast spatio-temporal analysis. This paper proposes the improved index for efficient OLAP in a spatial data warehouse. The main idea is to use the hybrid index of the extended aggregation R-tree and the sorted hash table. The extended R-tree supports the spatial hierarchy with the level of R-tree. Also, it provides pre-aggregation for fast retrieval of the aggregated value. The sorted hash table is the transformed hash table for supporting the temporal hierarchy. So, it provides pre-aggregation of each temporal unit, year, month and etc. By the proposed hybrid index, an efficient spatio-temporal analysis can be supported since it provides the spatio-temporal hierarchy and the pre-aggregated value.
Locating the “right” piece of information among a wide range of available alternatives is not an easy task, as everyone has experienced at least once during his/her lifetime. In this paper we look at some recent issues arising when a database query is extended so as to include user preferences, which ultimately determine whether one alternative is reputed by the user better than another one. In particular, we focus on the case of qualitative preference queries, that strictly include well-known skyline queries, and describe how one can take advantage of the sorting machinery of standard database engines to speed-up evaluation both in centralized and distributed scenarios.
A hitherto unquestioned assumption made by all methods for integrity checking has been that the database satisfies its constraints before each update. This consistency assumption has been exploited for improving the efficiency of determining whether integrity is satisfied or violated after the update. Based on a notion of violation tolerance, we present and discuss an abstract property which, for any given approach to integrity checking, is an easy, sufficient condition to check whether the consistency assumption can be abandoned without sacrificing usability and efficiency of the approach. We demonstrate the usefulness of our definitions by showing that the theorem-proving approach to database integrity by Sadri and Kowalski, as well as several other well-known methods, can indeed afford to abandon the consistency assumption without losing their efficiency, while their applicability is vastly increased.
L3S research focuses on three key enablers for the European Information Society, namely Knowledge, Information and Learning. The first part of the talk will review this project background context and highlight some of these projects in more detail. The second part focuses on ”Personal Information Management” as guiding theme for several of these projects. Personal information management infrastructures provide advanced functionalities for accessing information from institutional repositories / digital libraries as well as personal collections, and facilitate knowledge sharing and exchange in work and learning contexts. Federated and peer-to-peer infrastructures, integrated search on metadata and full-text collections, and advanced personalization and ranking algorithms play an important role in this context.
Schema matching is a critical step in data integration from multiple heterogeneous data sources. This paper presents a new approach to schema matching, based on two observations. First, it is easier to find attribute correspondences between those schemas that are contextually similar. Second, the attribute correspondences found between these schemas can be used to help find new attribute correspondences between other schemas. Motivated by these observations, we propose a novel clustering-based approach to schema matching. First, we cluster schemas on the basis of their contextual similarity. Second, we cluster attributes of the schemas that are in the same schema cluster to find attribute correspondences between these schemas. Third, we cluster attributes across different schema clusters using statistical information gleaned from the existing attribute clusters to find attribute correspondences between more schemas. We leverage a fast clustering algorithm, the K-Means algorithm, to the above three clustering tasks. We have evaluated our approach in the context of integrating information from multiple web interfaces and the results show the effectiveness of our approach.
We propose a new architecture for object database access and management. It is based on updateable views which provide universal mappings of stored objects onto virtual ones. The mechanism preserves full transparency of virtual objects either for retrieval and any kind of updating. It provides foundation for three-level database architecture and correspondingly three database development roles: (1) a database programmer defines stored objects, i.e. their state and behavior; (2) a database administrator (DBA) creates views and interfaces which encapsulate stored objects and possibly limit access rights on them; (3) an application programmer or a user receives access and updating grants from DBA in the form of interfaces to views. We present a concrete solution that we are developing as a platform for grid and Web applications. The solution is supported by an intuitive methodology of schema development, determining the perspectives and responsibilities of each participant role.
Efficient resource allocation for submitted task is one of the main challenges in grid computing. Much work in this aspect has focused on resource discovery and usage. Resource allocation, which is an interface between resource discovery and usage, is always unvalued in the past while some resource owners may provide resources with poor quality. A personalized fair reputation scheme is proposed in this paper to overcome these limitations and to encourage collaboration in grid community. We present minimum and maximum threshold for reputation from other entities to decrease malicious competition. A rewarding mechanism is also proposed in our reputation scheme to encourage collaboration. Then we present how to integrate our reputation scheme into grid resource allocation approach. Experimental results show that our approach can work in the environment with high ratio of malicious nodes in grid.
The business rule approach is used in information systems to represent domain knowledge and to maintain rules systems efficiently in volatile business environment. A number of methods were proposed to develop rule models, but only few deal with reuse of knowledge acquired in the analysis of some particular domain and automatic implementation of rules. In this paper, a method for representing knowledge by ontology transformation into the rule model is described. The method is based on ontology transformation of axioms presented in a formal way into (semi-) formal information processing rules in the form of executable rules, like active DBMS triggers. The method is implemented into the developed prototype, which is described in the case study section.
In a large modern enterprise, it is almost inevitable that different parts of an organization use different systems to produce, store, and search their critical data. In addition, the maintenance of heterogeneous database systems is becoming an overhead and a big problem for companies. Meanwhile, it is only achieved by combining the information from these various systems so that the enterprise can use the combined value of the data they contain. One way to solve this problem is to replace the legacy applications with a single information system. Introducing the new software is not enough; it is also necessary to migrate the data from the old system to the new one. As data has been collected over many years and contains a lot of information and knowledge, this most important value of a company must be preserved. Here, we present a specific solution based on a metadata repository model that we applied which addresses an organization’s operational need to integrate the custom databases of some specific hardware dependent legacy systems.
Spatial information processing is an active research field in database technology. Spatial databases store information about the position of individual objects in space [6]. Our current research is focused on providing an efficient caching structure for a telemetric data warehouse. We perform spatial objects clustering when creating levels of the structure. For this purpose we employ a density-based clustering algorithm. The algorithm requires an user-defined parameter Eps. As we cannot get the Eps from user for every level of the structure we propose a heuristic approach for calculating the Eps parameter. Automatic Eps Calculation (AEC) algorithm analyzes pairs of points defining two quantities: distance between the points and density of the stripe between the points. In this paper we describe in detail the algorithm operation and interpretation of the results. The AEC algorithm was implemented in one centralized and two distributed versions. Included test results present the algorithm correctness and efficiency against various datasets.
Connectivity based clustering has wide application in many networks like ad hoc networks, sensor networks and so on. But traditional research on this aspect is mainly based on graph theory, which needs global knowledge of the whole network. In this paper, we propose a intelligent approach called spreading activation models for connectivity based clustering (SAMCC) scheme that only local information is needed for clustering. The main feature of SAMCC scheme is applying the idea of spreading activation, which is an organization method for human long-term memory, to clustering and the whole network can be clustered in a decentralized automatic and parallel manner. The SAMCC scheme can be scaled to different networks and different level clustering. Experiment evaluations show the efficiency of our SAMCC scheme in clustering accuracy.
One of the most exciting accomplishments of computer science in the lifetime of this generation is the World Wide Web. The Web is a global electronic publishing medium. Its size has been growing with an enormous speed for over a decade. Most of its content is objectionable, but it also contains a huge amount of valuable information. The Web adds a new dimension to the concept of information explosion and tries to solve the very same problem by information retrieval systems known as Web search engines. We briefly review the information explosion problem and information retrieval systems, convey the past and state of the art in Turkish information retrieval research, illustrate some recent developments, and propose some future actions in this research area in Turkey.
The widespread use of XML brings out the need of ensuring the validity of XML data. The use of languages such as XML Schema makes easier the process of verification of XML documents, but the problem is that there are many constraints that can not be expressed by means of XML Schema. Besides, several works in the literature defend the consideration of a conceptual level in order to save XML designers from dealing with low level implementation issues. The approach of this paper is based on the inclusion of such a conceptual level, using UML as a conceptual modeling language. Starting from a UML class diagram annotated with conceptual constraints, our framework automatically generates an XML Schema together with a set of XSLT stylesheets to check those integrity constraints that can not be expressed in XML Schema.
MIGP (Medical Image Grid Platform) realizes information retrieval and integration in extensive distributed medical information systems, which adapts to the essential requirement for the development of healthcare information infrastructure. But the existing MIGPs, which are constructed mostly based on database middleware, are very difficult to guarantee local hospital data security and remote accessing legality. In this paper, a MIGP based on the WSRF-compliant HL7 (Health Level 7) grid middleware is proposed, which aims to combine the existing HL7 protocol and grid technology to realize medical data and image retrieval through the communications and interoperations with different hospital information systems. We also design the architecture and bring forward a metadata-based scheduling mechanism for our grid platforms. At last, experimental MIGPs are constructed to evaluate the performance of our method.
