Building Standards-Based Geoprocessing Mobile Clients

Ponència presentada en AGILE’2012 International Conference on Geographic Information Science, "Multidisciplinary Research on Geographical Information in Europe and Beyond" celebrat a Avignon, els dies 24-27 d'abril de 2012The adoption of geoprocessing service clients in mobile devices seems to be still rare, even when the communication protocol provided by the Web Processing Service (WPS) seems to fit the philosophy of accessing computation-intensive processes from resourceconstrained devices such as mobile phones. One of the reasons to such a low use of WPS services is that input and output data used in geospatial processes are often encoded in some XML-based format, which demands large processing capabilities for mobile devices. In order to deal with this problem we present the WPS Mobile Framework. This framework provides light-weight libraries to communicate with WPS servers and it carries out automatic generation of XML data binding code for mobile devices tailored to specific application needs

Workflow technology for geo-processing: the missing link

Nowadays GIS users have at their disposal an unprecedented amount of spatial information, thanks to the growing acquisition capacity of the applied survey techniques and instruments, and to the development of Spatial Data Infrastructures and OGC Standards for sharing distributed spatial data. In this context there is the need for new GIS applications that cross the boundary of a single organization and are flexible enough to adapt to the environmental changes. This paper evaluates the applicability of the emerging workflow technology for developing new GIS distributed applications that combine automatic services and human interactions, and are able to deal with large amount of spatial data during long-running processing tasks. Moreover, the limits of this technology when applied to the geographical context are highlighted and some possible solutions to these limitations are proposed

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