Process Modelling, Web Services and Geoprocessing

Process modelling has always been an important part of research in generalisation. In the early days this would take the form of a static sequence of generalisation actions, but currently the focus is on modelling much more complex processes, capable of generalising geographic data into various maps according to specific user requirements. To channel the growing complexity of the processes required, better process models had to be developed. This chapter discusses several aspects of the problem of building such systems. As the system gets more complex, it becomes important to be able to reuse components which already exist. Web services have been used to encapsulate generalisation processes in a way that maximises their interoperability and therefore reusability. However, for a system to discover and trigger such a service, it needs to be formalised and described in a machine understandable way, and the system needs to have the knowledge about where and when to use such tools. This chapter therefore explores the requirements and potential approaches to the design and building of such systems

GENERALISATION AND DATA QUALITY

The quality of spatial data has a massive impact on its usability. It is therefore critical to both the producer of the data and its users. In this paper we discuss the close links between data quality and the generalisation process. The quality of the source data has an effect on how it can be generalised, and the generalisation process has an effect on the quality of the output data. Data quality therefore needs to be kept under control. We explain how this can be done before, during and after the generalisation process, using three of 1Spatial’s software products: 1Validate for assessing the conformance of a dataset against a set of rules, 1Integrate for automatically fixing the data when non-conformances have been detected and 1Generalise for controlling the quality during the generalisation process. These tools are very effective at managing data that need to conform to a set of quality rules, the main remaining challenge is to be able to define a set of quality rules that reflects the fitness of a dataset for a particular purpose

Towards an interoperable web generalisation services framework – current work in progress

Web Generalisation Services are now receiving considerable attention from the research community. In this context, interoperability has been identified as a crucial beneficiary of the Web Service concept. This has inspired the formation of a working group to establish consensus for Web Generalisation Services and to specify further technical requirements. The intent of this working group is to enable a higher degree of interoperability and thereby increase the possibilities for exchanging and sharing generalisation functionality over the Web. OGC’s WPS interface specification has been taken as a basis, since it provides a standardized means within the geo-spatial domain to establish processes such as generalisation. This paper reports the current status of the working group and the forthcoming work items

Methodologies for the evaluation of generalised data derived with commercial available generalisation systems

The paper investigates methodical questions on the analyses and evaluation of automated generalised maps. The maps are produced with commercially available out-of-the-box generalisation systems, in a way that every system was tested by several persons on four test cases. The requirements on the generalised maps were described by cartographic constraints in a formal way. In addition, manually generalised maps were provided to give further reference information for the tester. The analyses of the generalised maps are to be based on empirical and automated evaluation methods. The paper will present these evaluation methods in detail with objectives, related research, how the methods are realised and expected outcomes. Possible interchanges and synergies between the evaluation methods will also be described. The work published within this paper contributes to research on formal descriptions of cartographic requirements on generalised maps. It supports the development of methods for the situation and context dependent application of generalisation functionality and serves on the evaluation of existing generalisation products, to derive future research and development potentia

A study on the state-of-the-art in automated map generalisation implemented in commercial out-of-the-box software

This paper describes the set up and the progress of the EuroSDR project that studies the state-of-the-art in automated map generalisation implemented in commercial out-of-thebox software. The project started in October 2006 with a project team consisting of National Mapping Agencies (NMAs) and research institutes. From October 2006 till May 2007 four test cases of four different NMAs were selected, consisting of a large scale source data set, requirements for the smaller scale output map as well as symbolisation information. Much effort has been put in specifying and harmonising requirements for the output maps. These requirements have been defined as a set of constraints to be respected in the output maps. From June 2007 the project team tested the four test cases with four commercial out-of-the-box software systems: ArcGIS, Genesys, Change/Push/Typify and Clarity. The vendors of these systems performed parallel tests on the four test cases in which they were allowed to customise their systems. An evaluation methodology has been designed and partly implemented. Results are expected by the end of 2008

Molecular diversity of the adenylyl cyclase-coupled signaling in pancreatic islet cells

info:eu-repo/semantics/publishe

Web service approaches for providing enriched data structures to generalisation operators

Web service technologies can be used to establish an interoperable framework between different generalisation systems. In a previous article three categories of generalisation web services were identified, including support services, operator services and processing services. This paper focuses on the category of support services. In a service-based generalisation system, the purpose of support services is to assist the generalisation process by providing auxiliary measures, procedures and data structures that allow the representation of structural cartographic knowledge. The structural knowledge of the spatial and semantic context and the modelling of structural and spatial relationships is critical for the understanding of the role of cartographic features and thus for automated generalisation. Support services should extract and model this knowledge from the raw data and make it available to other generalisation operators. On the one hand the structural knowledge can be expressed by enriching map features with additional geometries or attributes. On the other hand, there exist various hierarchical and nonhierarchical relationships between map features, many of which can be represented by graph data structures. After a brief introduction to the interoperable web service framework, this paper proposes a taxonomy of generalisation support services and discusses its elements. It is then shown how the complex output of such services can be represented for use with web services and stored in a reusable fashion. Finally, the utilisation of support services is illustrated on four implementation examples of support services that also highlight the interactions with the generalisation operators that use these auxiliary services

Methodology for evaluating automated map generalization in commercial software

This paper presents a methodology developed for a study to evaluate the state of the art of automated map generalization in commercial software without applying any customization. The objectives of this study are to learn more about generic and specific requirements for automated map generalization, to show possibilities and limitations of commercial generalization software, and to identify areas for further research. The methodology had to consider all types of heterogeneity to guarantee independent testing and evaluation of available generalization solutions. The paper presents the two main steps of the methodology. The first step is the analysis of map requirements for automated generalization, which consisted of sourcing representative test cases, defining map specifications in generalization constraints, harmonizing constraints across the test cases, and analyzing the types of constraints that were defined. The second step of the methodology is the evaluation of generalized outputs. In this step, three evaluation methods were integrated to balance between human and machine evaluation and to expose possible inconsistencies. In the discussion the applied methodology is evaluated and areas for further research are identified