Multi-Paradigm Reasoning for Access to Heterogeneous GIS

Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn the web into a geospatial web services enabled place. Mediation architectures like VirGIS overcome syntactical and semantical heterogeneity between several distributed sources. On mobile devices, however, this kind of solution is not suitable, due to limitations, mostly regarding bandwidth, computation power, and available storage space. The aim of this paper is to present a solution for providing powerful reasoning mechanisms accessible from mobile applications and involving data from several heterogeneous sources. By adapting contents to time and location, mobile web information systems can not only increase the value and suitability of the service itself, but can substantially reduce the amount of data delivered to users. Because many problems pertain to infrastructures and transportation in general and to way finding in particular, one cornerstone of the architecture is higher level reasoning on graph networks with the Multi-Paradigm Location Language MPLL. A mediation architecture is used as a “graph provider” in order to transfer the load of computation to the best suited component – graph construction and transformation for example being heavy on resources. Reasoning in general can be conducted either near the “source” or near the end user, depending on the specific use case. The concepts underlying the proposal described in this paper are illustrated by a typical and concrete scenario for web applications

A Framework for Semantic Interoperability for Distributed Geospatial Repositories

Interoperable access of geospatial information across disparate geospatial applications has become essential. Geospatial data are highly heterogeneous -- the heterogeneity arises both at the syntactic and semantic levels. Finding and accessing appropriate data in such a distributed environment is an important research issue. The paper proposes a methodology for interoperable access of geospatial information based on Open Geospatial Consortium (OGC) specified standards. An architecture for integrating diverse geospatial data repositories has been proposed using service-based methodology. The semantic issues for discovery and retrieval of geospatial data over distributed geospatial services have also been proposed in the paper. The proposed architecture utilizes the ontological concepts for service description and subsequent discovery of services. An approach for semantic similarity assessment of geospatial services has been discussed

An Approach for Service Oriented Discovery and Retrieval of Spatial Data

ABSTRACT Successful information integration and sharing data across disparate systems and designs are required for fast access to and interpretation of many types of geospatial information. Spatial data are highly heterogeneous -not only they differ from data representation and storage methods, but they also differ in the way of querying the data. Finding and accessing spatial data in an environment like this is a crucial task. Enterprise geographic information system (E-GIS) is an organization-wide approach to GIS implementation, operation, and management. The main focus of the paper is to integrate diverse spatial data repositories for geographic applications using service-based methodology. We have adopted service-oriented architecture (SOA) for the discovery and retrieval of geospatial data. The architecture uses a central ontology as metadata information, which acts as service broker. Ontology-based discovery and retrieval of geographic data solves the problem of semantic heterogeneity, the major bottleneck for spatial interoperability. The implementation is in compliant with the Web Map Service (WMS) and Web Feature Service (WFS), the web service standards proposed by OGC. The need for loosely coupled service-based access of data in the spatial domain has been exploited. A query processing mechanism in distributed environment of spatial data sources has been discussed at the end. The proposed system has been implemented and fully tested

Supporting Distributed Geo-Processing: A Framework for Managing Multi-Accuracy Spatial Data

Negli ultimi anni molti paesi hanno sviluppato un'infrastruttura tecnologica al fine di gestire i propri dati geografici (Spatial Data Infrastructure, SDI). Tali infrastrutture rechiedono nuove ed efficati metodologie per integrare continuamente dati che provengoono da sorgenti diverse e sono caratterizzati da diversi livelli di qualit\ue0. Questo bisogno \ue8 riconosciuto in letteratura ed \ue8 noto come problema di integrazione del dato (data integration) o fusione di informazioni (information fusion). Un aspetto peculiare dell'integrazione del dato geografico riguarda il matching e l'allineamento degli oggetti geometrici. I metodi esistenti solitamente eseguono l'integrazione semplicemente allineando il database meno accurato con quello pi\uf9 accurato, assumendo che il secondo contenga sempre una rappresentazione migliore delle geometrie rilevate. Seguendo questo approccio, gli oggetti geografici sono combinati assieme in una maniera non ottimale, causando distorsioni che potenzialmente riducono la qualit\ue0 complessiva del database finale. Questa tesi si occupa del problema dell'integrazione del dato spaziale all'interno di una SDI fortemente strutturata, in cui i membri hanno preventivamente aderito ad uno schema globale comune, pertanto si focalizza sul problema dell'integrazione geometrica, assumendo che precedenti operazioni di integrazione sullo schema siano gi\ue0 state eseguire. In particulare, la tesi inizia proponendo un modello per la rappresentazione dell'informazione spaziale caratterizzata da differenti livelli di qualit\ue0, quindi definisce un processo di integrazione che tiene conto dell'accuratezza delle posizioni contenute in entrambi i database coinvoilti. La tecnica di integrazione proposta rappresenta la base per un framework capace di supportare il processamento distributo di dati geografici (geo-processing) nel contesto di una SDI. Il problema di implementare tale computazione distribuita e di lunga durata \ue8 trattato anche da un punto di vista pratico attraverso la valutazione dell'applicabilit\ue0 delle tecnologie di workflow esistenti. Tale valutazione ha portato alla definizione di una soluzione software ideale, le cui caratteristiche sono discusse negli ultimi capitoli, considerando come caso di studio il design del processo di integrazione proposto.In the last years many countries have developed a Spatial Data Infrastructure (SDI) to manage their geographical information. Large SDIs require new effective techniques to continuously integrate spatial data coming from different sources and characterized by different quality levels. This need is recognized in the scientific literature and is known as data integration or information fusion problem. A specific aspect of spatial data integration concerns the matching and alignment of object geometries. Existing methods mainly perform the integration by simply aligning the less accurate database with the more accurate one, assuming that the latter always contains a better representation of the relevant geometries. Following this approach, spatial entities are merged together in a sub-optimal manner, causing distortions that potentially reduce the overall database quality. This thesis deals with the problem of spatial data integration in a highly-coupled SDI where members have already adhered to a common global schema, hence it focuses on the geometric integration problem assuming that some schema matching operations have already been performed. In particular, the thesis initially proposes a model for representing spatial data together with their quality characteristics, producing a multi-accuracy spatial database, then it defines a novel integration process that takes care of the different positional accuracies of the involved source databases. The main goal of such process is to preserve coherence and consistency of the integrated data and when possible enhancing its accuracy. The proposed multi-accuracy spatial data model and the related integration technique represent the basis for a framework able to support distributed geo-processing in a SDI context. The problem of implementing such long-running distributed computations is also treated from a practical perspective by evaluating the applicability of existing workflow technologies. This evaluation leads to the definition of an ideal software solution, whose characteristics are discussed in the last chapters by considering the design of the proposed integration process as a motivating example

Personalized City Tours - An Extension of the OGC OpenLocation Specification

A business trip to London last month , a day visit in Cologne next saturday and romantic weekend in Paris in autumn – this example exhibits one of the central characteristics of today’s tourism. People in the western hemisphere take much pleasure in frequent and repeated short term visits of cities. Every city visitor faces the general problems of where to go and what to see in the diverse microcosm of a metropolis. This thesis presents a framework for the generation of personalized city tours - as extension of the Open Location Specification of the Open Geospatial Consortium. It is founded on context-awareness and personalization while at the same time proposing a combined approach to allow for adaption to the user. This framework considers TimeGeography and its algorithmic implementations to be able to cope with spatio-temporal constraints of a city tour. Traveling salesmen problems - for which a heuristic approache is proposed – are subjacent to the tour generation. To meet the requirements of today’s distributed and heterogeneous computing environments, the tour framework comprises individual services that expose standard-compliant interfaces and allow for integration in service oriented architectures