Challenging Issues of Spatio-Temporal Data Mining

The spatio-temporal database (STDB) has received considerable attention during the past few years, due to the emergence of numerous applications (e.g., flight control systems, weather forecast, mobile computing, etc.) that demand efficient management of moving objects. These applications record objects' geographical locations (sometimes also shapes) at various timestamps and support queries that explore their historical and future (predictive) behaviors. The STDB significantly extends the traditional spatial database, which deals with only stationary data and hence is inapplicable to moving objects, whose dynamic behavior requires re-investigation of numerous topics including data modeling, indexes, and the related query algorithms. In many application areas, huge amounts of data are generated, explicitly or implicitly containing spatial or spatiotemporal information. However, the ability to analyze these data remains inadequate, and the need for adapted data mining tools becomes a major challenge. In this paper, we have presented the challenging issues of spatio-temporal data mining. Keywords: database, data mining, spatial, temporal, spatio-tempora

Querying Spatio-Temporal Data of Moving Objects

Diplomová práce je věnována studiu možností, jakými lze reprezentovat data pohybujících se objektů a jak je možné se nad těmito časoprostorovými daty dotazovat. Dále jsou zde shrnuty výsledky diplomové práce pana Ing. Jaroslava Vališe, ze kterých se při řešení této diplomové práce mělo vycházet. Na základě získaného teoretického základu, prezentovaného na začátku práce, však byla navržena a implementována zcela nová podpora pro uložení časoprostorových dat a pro obecné dotazování se nad těmito daty. Její konkrétní využití je pak dále demonstrováno v ukázkové aplikaci, která mimo jiné toto řešení využívá k implementaci svých složitějších doménově specifických databázových operací. Na závěr jsou uvedeny hlavní směry dalšího vývoje navrženého databázového rozšíření a zasazení výsledků této práce do kontextu pokračujícího projektu, disertační práce na téma "Databáze pohybujících se objektů".This master's thesis is devoted to the studies of possibilities, which can be used for representation of moving objects data and for querying such spatio-temporal data. It also shows results of the master's thesis created by Ing. Jaroslav Vališ, that should be used for the solution of this master's thesis. But based on the theoretical grounds defined at the beginning of this work was designed and implemented new database extension for saving and querying spatio-temporal data. Special usage of this extension is demonstrated in an example application. This application uses the database extension for the implementation of its own database functions that are domain specific. At the conclusion, there are presented ways of the farther development of this database extension and the results of this master's thesis are there set into the context of the following project, doctoral thesis "Moving objects database".

Computer-Driven Instructional Design with INTUITEL

INTUITEL is a research project that was co-financed by the European Commission with the aim to advance state-of-the-art e-learning systems via addition of guidance and feedback for learners. Through a combination of pedagogical knowledge, measured learning progress and a broad range of environmental and background data, INTUITEL systems will provide guidance towards an optimal learning pathway. This allows INTUITEL-enabled learning management systems to offer learners automated, personalised learning support so far only provided by human tutors INTUITEL is - in the first place - a design pattern for the creation of adaptive e-learning systems. It focuses on the reusability of existing learning material and especially the annotation with semantic meta data. INTUITEL introduces a novel approach that describes learning material as well as didactic and pedagogical meta knowledge by the use of ontologies. Learning recommendations are inferred from these ontologies during runtime. This way INTUITEL solves a common problem in the field of adaptive systems: it is not restricted to a certain field. Any content from any domain can be annotated. The INTUITEL research team also developed a prototype system. Both the theoretical foundations and how to implement your own INTUITEL system are discussed in this book

Computer-Driven Instructional Design with INTUITEL

INTUITEL is a research project that was co-financed by the European Commission with the aim to advance state-of-the-art e-learning systems via addition of guidance and feedback for learners. Through a combination of pedagogical knowledge, measured learning progress and a broad range of environmental and background data, INTUITEL systems will provide guidance towards an optimal learning pathway. This allows INTUITEL-enabled learning management systems to offer learners automated, personalised learning support so far only provided by human tutors INTUITEL is - in the first place - a design pattern for the creation of adaptive e-learning systems. It focuses on the reusability of existing learning material and especially the annotation with semantic meta data. INTUITEL introduces a novel approach that describes learning material as well as didactic and pedagogical meta knowledge by the use of ontologies. Learning recommendations are inferred from these ontologies during runtime. This way INTUITEL solves a common problem in the field of adaptive systems: it is not restricted to a certain field. Any content from any domain can be annotated. The INTUITEL research team also developed a prototype system. Both the theoretical foundations and how to implement your own INTUITEL system are discussed in this book

An object-relational prototype of a GIS-based disaster database

Natural disasters cause billions of dollars of property and infrastructure damage, unexpected disruption to socio-economic activities and tragic loss of human lives each year. The importance of collecting and maintaining detailed and accurate records on disastrous events for an effective risk assessment and disaster mitigation has been widely recognised. Considerable efforts have been directed towards the establishment of databases on historic disasters but many disaster databases built are primarily a set of lists of historical disaster events. Disaster phenomena vary dramatically with both space and time. It is therefore important to integrate spatial-temporal dimensions of disaster events in a disaster database to support efficient and interactive querying and reporting operations. It is also important to make such a database readily accessible by a variety of users from government agencies, non-government organisations, research institutes and local communities, to enable effective and efficient emergency response, impact and risk assessment, and mitigation planning. This thesis presents a study that investigates effective and efficient geographical information system (GIS) based approaches to the representation, organisation and access of disaster information - including logical data models for representing disastrous events, the object-relational approach to database implementation, and internet-based user-interfaces for database queries and report generation. Key aspects of a disaster event, including the spatial-temporal dimensions of the hazard and its impacts, are considered in the development of data models and database implementation in order to support user-friendly querying and reporting operations. The technological strengths of GIS, database management systems, and Internet-related toolboxes are leveraged for developing a prototype of a GIS-based, object-relational disaster database with an Internet-based user interface that supports multi-mode (including map-based) database queries and flexible facilities for report generation

Automated web-based analysis and visualization of spatiotemporal data

Most data are associated with a place, and many are also associated with a moment in time, a time interval, or another linked temporal component. Spatiotemporal data (i.e., data with elements of both space and time) can be used to assess movement or change over time in a particular location, an approach that is useful across many disciplines. However, spatiotemporal data structures can be quite complex, and the datasets very large. Although GIS software programs are capable of processing and analyzing spatial information, most contain no (or minimal) features for handling temporal information and have limited capability to deal with large, complex multidimensional spatiotemporal data. A related problem is how to best represent spatiotemporal data to support efficient processing, analysis, and visualization. In the era of "big data," efficient methods for analyzing and visualizing large quantities of spatiotemporal data have become increasingly necessary. Automated processing approaches, when made scalable and generalizable, can result in much greater efficiency in spatiotemporal data analysis. The growing popularity of web services and server-side processing methods can be leveraged to create systems for processing spatiotemporal data on the server, with delivery of output products to the client. In many cases, the client can be a standard web browser, providing a common platform from which users can interact with complex server-side processing systems to produce specific output data and visualizations. The rise of complex JavaScript libraries for creating interactive client-side tools has enabled the development of rich internet applications (RIA) that provide interactive data exploration capabilities and an enhanced user experience within the web browser. Three projects involving time-series tsunami simulation data, potential human response in a tsunami evacuation scenario, and large sets of modeled time-series climate grids were conducted to explore automated web-based analysis, processing, and visualization of spatiotemporal data. Methods were developed for efficient handling of spatiotemporal data on the server side, as well as for interactive animation and visualization tools on the client side. The common web browser, particularly when combined with specialized server side code and client side RIA libraries, was found to be an effective platform for analysis and visualization tools that quickly interact with complex spatiotemporal data. Although specialized methods were developed to for each project, in most cases those methods can be generalized to other disciplines or computational domains where similar problem sets exist