Peter Bednár

Data mining and integration for predicting significant meteorological phenomena

Abstract This paper describes the planned contribution of the project Data Mining Meteo (DMM) to the research of parametrized models and methods for detection and prediction of significant meteorological phenomena, especially fog and low cloud cover. The project is expected to cover methods for integration of distributed meteorological data necessary for running the prediction models, training models and then mining the data in order to be able to efficiently and quickly predict even randomly occurring phenomena. We present the methods and technologies we will use for integration of the input data, distributed on different vendors’ servers. The meteorological detection and prediction methods are based on statistical and climatological methods combined with knowledge discovery — data mining of meteorological data (SYNOP, METAR messages, weather radar imagery, “raw” meteorological data from stations, satellite imagery and results of common meteorological prediction models).

Semantic Integration of eGovernment Services in Schleswig-Holstein

The paper presents an example of e-government service integration on a semantic basis, as it was designed within the Access-eGov research project and applied in the Schleswig-Holstein state government. The case study follows up the application of a requirements-driven approach for designing e-government service interfaces with respect to the informational needs of citizens and business users. Using this approach, a conceptual model for e-government services was developed, formalised in the WSML ontology language, and used for semantic annotation of the services as a basis for integration. A subsequent field test was focused on the evaluation of produced semantic description on the client-side system components as Annotation tool and the Personal Assistant Client. The results of the field test have been evaluated and are presented in as lessons learned.

Integration of government services using semantic technologies

The paper describes an approach to semantic interoperability of eGovernment services applied within the 027020 FP6 IST Access-eGov project. The goal of the project was to improve accessibility and connectivity of governmental services for citizens and businesses by means of creating integrated scenarios and providing guidance to users while following this scenario. The scenario helps the user to identify and fulfil any needed electronic or real governmental services in a selected life situation. The Access-eGov project has developed software tools enabling service integration using semantic technologies. In addition to that, a methodology providing guidance to the user-driven process of creating ontologies was developed. Sample ontologies were prepared for trial applications. The developed tools support browsing, discovery, and execution of government services according to a selected life event or goal. The project successfully developed and tested the proposed solutions. The software developed within the project is available as open source software.

Meteorological phenomena forecast using data mining prediction methods

The occurrence of various meteorological phenomena, such as fog or low cloud cover, has significant impact on many human activities as air or ship transport operations. The management of air traffic at the airports was the main reason to design effective mechanisms for timely prediction of these phenomena. In both these cases meteorologists already use some physical models based on differential equations as simulations. Our goal was to design, implement and evaluate a different approach based on suitable techniques and methods from data mining domain. The selected algorithms were applied on obtained historical data from meteorological observations at several airports in United Arab Emirates and Slovakia. In the first case, the fog occurrence was predicted based on data from METAR messages with algorithms based on neural networks and decision trees. The low cloud cover was forecasted at the national Slovak airport in Bratislava with decision trees. The whole data mining process was managed by CRISP-DM methodology, one of the most accepted in this domain.

Analytical Framework for Mirroring and Reflection of User Activities in E-Learning Environment

This chapter deals with evaluation of user activities and their participation in collaborative processes realized within the supporting virtual environment. The main goal behind proposed solution is to provide standalone package with all necessary functionalities to obtain data from examined virtual collaborative system in form of logs. For this purpose the following has been designed and implemented: a repository with predefined log format representing source historical data for analyzes; supporting middleware services for proposed analytical approaches; end-user tool for time-line based mirroring and analyses of user activities. These basic functionalities are extended with possibility to extract various summative statistics [10] about performed user activities and possibility to export data in predefined format (e.g. MS Excel) for analyses in third party tools as e.g. IBM SPSS Modeler. Described analytical framework has been designed, implemented and tested mainly within KP-Lab System that represents new interesting application in the domain of virtual environments or e-Learning systems. Proposed architecture was designed as generic platform with possibility to be integrated with other systems such as Moodle or Claroline in order to reflect different user practices.

RDF vs. NoSQL databases for the semantic web applications

The main objective of presented paper is to compare and analyze the performance of semantic and NoSQL storage on the selected datasets. Paper focuses on a theoretical analysis of the problem and details the performance testing of selected semantic repositories and NoSQL databases. The practical part is focused on the testing of selected systems and our main aim was to simulate multiple querying with regard to diversity of the queries with different criteria. Results of the performed experiments are reported and analyzed.

Orchestration of public administration services with a use of semantic technologies

Currently, public administration services are being transformed into electronic. In such state, service consumers can solve their life event situations by going thru sequence of services where combination of traditional and electronic services is might occur. Service choreography is known as observable behaviour of one service from clients point of view. But there is a need to describe also how the overall functionality of the service is achieved in terms of cooperation with the other services (a full execution mechanism) is known as orchestration. Execution mechanism that is able to interpret (chosen) WSMO choreography and orchestration description is based on abstract state machines for WSMO specification. In principle, this implementation is not suitable in case there is a need to navigate user during the process execution. To overcome this problem, an alternative solution based on Cashew workflow language was proposed.

Distributed task-based execution engine for support of text-mining processes

This paper describes design and implementation aspects for extension of our original software system developed in Java for support of information retrieval and text mining with specialized execution engine for different type of tasks. Some of our experiences and specific requirements of the real applications lead us to idea give the system possibility to run the tasks in distributive way. The result of the idea is task-based execution engine, which represents middleware-like transparent layer (mostly for programmers who want to re-use functionality of our package) for running of different tasks in multi-thread environment. The original system is being developed as open source with the intention to provide an easy extensible, modular framework for pre-processing, indexing and further exploration of large text collections. This specialized execution engine has been implemented within APVV project called PoZnaŤ (Support for knowledge creation processes) in order to extend proposed text-mining platform for educational and experimental purposes. Conceptual architecture of the system is provided as well as details regarding our extension of library like usage of content repository paradigm, representation and encapsulation of tasks, implementation of the engine itself and its role within PoZnaŤ platform.

Use of Semantic Principles in a Collaborative System in Order to Support Effective Information Retrieval

This paper focuses on information retrieval aspects of a new application in domain of collaborative systems based on utilization of semantic principles for representation of different types of knowledge, collaborative objects and relations between them. Proposed collaborative system (within European IST project called KP-Lab) uses ontologies as common communication framework and exchange format for different types of end-user tools. Theoretical background is provided by innovative theoretical approach called Trialogical learning. Information retrieval in KP-Lab System is supported by designed and implemented text-mining and search services. These two sets of functionalities provide features for management of shared objects, described with content in textual format, as well as with semantic metadata.

Analytical Platform Based on Jbowl Library Providing Text-Mining Services in Distributed Environment

The paper presents the Jbowl, Java software library for data and text analysis, and various research activities performed and implemented on top of the library. The paper describes the various analytical services for text and data mining implemented in Jbowl as well as numerous extensions aimed to address the evolving trends in data and text analysis and its usage in various tasks reflecting the areas such as big data analysis, distributed computing and parallelization. We also present the complex analytical platform built on top of the library, integrating the distributed computing analytical methods with the graphical user interface, visualization methods and resource management capabilities.