Michail Vaitis

Probabilistic spatial queries on existentially uncertain data

We study the problem of answering spatial queries in databases where objects exist with some uncertainty and they are associated with an existential probability. The goal of a thresholding probabilistic spatial query is to retrieve the objects that qualify the spatial predicates with probability that exceeds a threshold. Accordingly, a ranking probabilistic spatial query selects the objects with the highest probabilities to qualify the spatial predicates. We propose adaptations of spatial access methods and search algorithms for probabilistic versions of range queries and nearest neighbors and conduct an extensive experimental study, which evaluates the effectiveness of proposed solutions.

Top-k Spatial Preference Queries

A spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, consider a real estate agency office that holds a database with available flats for lease. A customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other features (e.g., restaurants, cafes, hospital, market, etc.) within a distance range from them. In this paper, we formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Our methods are experimentally evaluated for a wide range of problem settings.

Efficient Evaluation of Probabilistic Advanced Spatial Queries on Existentially Uncertain Data

We study the problem of answering spatial queries in databases where objects exist with some uncertainty and they are associated with an existential probability. The goal of a thresholding probabilistic spatial query is to retrieve the objects that qualify the spatial predicates with probability that exceeds a threshold. Accordingly, a ranking probabilistic spatial query selects the objects with the highest probabilities to qualify the spatial predicates. We propose adaptations of spatial access methods and search algorithms for probabilistic versions of range queries, nearest neighbors, spatial skylines, and reverse nearest neighbors and conduct an extensive experimental study, which evaluates the effectiveness of proposed solutions.

Ranking Spatial Data by Quality Preferences

A spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, using a real estate agency database of flats for lease, a customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other features (e.g., restaurants, cafes, hospital, market, etc.) within their spatial neighborhood. Such a neighborhood concept can be specified by the user via different functions. It can be an explicit circular region within a given distance from the flat. Another intuitive definition is to assign higher weights to the features based on their proximity to the flat. In this paper, we formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Extensive evaluation of our methods on both real and synthetic data reveals that an optimized branch-and-bound solution is efficient and robust with respect to different parameters.

Towards a semantics-based approach in the development of geographic portals

As the demand for geospatial data increases, the lack of efficient ways to find suitable information becomes critical. In this paper, a new methodology for knowledge discovery in geographic portals is presented. Based on the Semantic Web, our approach exploits the Resource Description Framework (RDF) in order to describe the geoportals information with ontology-based metadata. When users traverse from page to page in the portal, they take advantage of the metadata infrastructure to navigate easily through data of interest. New metadata descriptions are published in the geoportal according to the RDF schemas.

Modeling and mapping temperature and precipitation climate data in Greece using topographical and geographical parameters

This study presents a methodology for modeling and mapping the seasonal and annual air temperature and precipitation climate normals over Greece using several topographical and geographical parameters. Data series of air temperature and precipitation from 84 weather stations distributed evenly over Greece are used along with a set of topographical and geographical parameters extracted with Geographic Information System methods from a digital elevation model (DEM). Normalized difference vegetation index (NDVI) obtained from MODIS Aqua satellite data is also used as a geographical parameter. First, the relation of the two climate elements to the topographical and geographical parameters was investigated based on the Pearson’s correlation coefficient to identify the parameters that mostly affect the spatial variability of air temperature and precipitation over Greece. Then a backward stepwise multiple regression was applied to add topographical and geographical parameters as independent variables into a regression equation and develop linear estimation models for both climate parameters. These models are subjected to residual correction using different local interpolation methods, in an attempt to refine the estimated values. The validity of these models is checked through cross-validation error statistics against an independent test subset of station data. The topographical and geographical parameters used as independent variables in the multiple regression models are mostly those found to be strongly correlated with both climatic variables. Models perform best for annual and spring temperatures and effectively for winter and autumn temperatures. Summer temperature spatial variability is rather poorly simulated by the multiple regression model. On the contrary, best performance is obtained for summer and autumn precipitation while the multiple regression model is not able to simulate effectively the spatial distribution of spring precipitation. Results revealed also a relatively weaker model performance for precipitation than that for air temperature probably due to the highly variable nature of precipitation compared to the relatively low spatial variability of air temperature field. The correction of the developed regression models using residuals improved though not significantly the interpolation accuracy.

Measuring the Economic, Social and Environmental Performance of European Island Regions: Emerging Issues for European and Regional Policy

Islands in the European Union (EU) are very diverse, with many small or very small islands and are recognized as territories facing particular development challenges. In this study, we seek to compare the state and the attractiveness of island administration units in their national and EU context and highlight their divergence in different dimensions, building on existing analysis of the European Commission and of ESPON, using more indicators than the GDP per capita. The assessment is performed with the use of five different indexes: one for the state of development, one for changes during 2000–2006 and three for the attractiveness of islands (direct effects of insularity to attractiveness, indirect effects and natural and cultural potential of islands). Findings for economy demonstrate that islands with better economic performance either specialize in a low added value activity (tourism), or have their GDP “boosted” by exogenous influences (duty free area, oil extraction or the public sector). For attractiveness, most of the islands perform very low and the situation of small islands and archipelagos is worse. Since insularity can be considered as a permanent, natural feature affecting negatively, directly and indirectly, most of the factors that make islands attractive, the need for a territorial policy emerges.

Supporting the design of behaviors in Callimachus

Behaviors play an important role to relationship semantics. In this paper, we present how behavioral aspects of structures are conceived in Callimachus, a structural computing environment. Callimachus supports the definition of behavioral designs called propagation templates that assist in addressing behavioral concerns of structures within structure servers. Propagation templates provide a higher level of abstraction and signify an attempt to move from an atom-based view of behaviors to a system and pattern-based view.

Towards the Development of Open Cartographic Hypermedia Systems

Despite the evolving technological developments that have influenced spatial information management and communication, digital cartography has to overcome a number of issues concerning cognition and usability. Hypermaps, integrating concepts from geographical information systems and hypermedia systems, have been proposed by many researchers as a promising solution. However, these systems are isolated, without making an attempt for information and services exchange. In this chapter, inspired by previous work on Open Hypermedia Systems, we propose a conceptual reference model for cartographic hypermedia services. As a prerequisite, a number of hypermap systems have been studied, resulting in a set of indispensable requirements.

Structural engineering: processes and tools for developing component-based open hypermedia systems

The emergence of Component-Based Open Hypermedia Systems aims at the releasing of Hypermedia and Web applications from the monocracy of link as the information structuring primitive. Instead, an open set of structure services, each one providing structure abstractions relevant to a specific domain, is offered to an open set of client applications. Nonetheless, the lack of an engineering framework guiding the development process of CB-OHS has a part in their limited exploitation. In this paper, we analyze the characteristics of CB-OHS from an engineering approach, and we propose a framework and a number of tools, supporting all phases of their development process.