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International audience; Cartographic generalisation seeks to summarise geographical information to produce legible maps at smaller scales. Past research led to the development of many automated cartographic generalisation processes, each one being more or less specialised to a particular problem: a landscape like urban areas, a data theme like land use, a cartographic conflict like linear symbol overlap or most of the time of mix of the three. This paper deals with the development of a model allowing collaborative generalisation i.e. the collaboration between automatic processes like these in order to tackle the generalisation of a complete map. CollaGen, our proposed model, allows to partition data in geographic spaces and to find to best suited process to generalise each space. The applications of a process on a space are automatically orchestrated. Interoperability between processes is managed thanks to formal constraints and side effects are monitored after each process application. Results from CollaGen prototype are shown and discussed.

The need for high-quality spatial information offering to the potential users of spatial data a simpler and more efficient use of the information is growing at the global level. According to the Law on State Survey and Real Property Cadastre (Official Gazette 16/07) and the Rules and Regulations on Topographic Survey and State Maps Production (Official Gazette 108/08), the State Geodetic Administration (SGA) is responsible for planning and implementing the topographic survey programs, development and maintenance of the topographic and cartographic database and official State maps and supervision and control of their production in specific stages of operations. By completing the Base Topographic Database (BTD) as the main originator of all official topographic datasets, products and topographic map in the scale of 1:25, 000 (TK25), the SGA is faced with the task of establishing an efficient system of updating. The data contained in the BTD is the topologically processed original data of the photogrammetric restitution, and represents the most accurate and detailed data created during the production of the topographic map in the scale of 1:25, 000 (TK25). Therefore, the SGA initiated a project in 2009 that resulted in the production of the BTD Updating Specifications and the development of updated TK25 sheets. These Specifications define the guidelines for maintaining the BTD and producing the updated TK25 editions in a manner that can satisfy the user needs for up-to-date data. The base datasets updating cycle amounts to 4 years but also defines shorter deadlines for updating certain data categories. The term “data categories” denotes the packages and classes included in the BTD structure and objects contained in TK25. The updating criteria for each specific class of data have been defined in such a way as to list the data of specific importance for the users under the first criteria group. In the Specifications, this means that deadlines have been defined for each specific class and that the content must be updated within these deadlines if there are any changes in the reality for certain data categories. By using this methodology of the base SGA datasets updating process organization, we have been able to respond to the following three basic questions: what, when and where to update i.e. grounds have been laid for the important changes to the objects to be collected immediately after their creation while, at the same time, preserving the real cartographic value of the entire dataset.

There is a growing consensus within the map generalization research community that open research platforms will allow closer integration in terms of collaborative research, data abstractions, interoperability of functional components, and the augmentation of geo-spatial applications with generalization capabilities. This chapter describes the authors' experiences in developing systems to support collaborative research in map generalization. The increasing complexity of methods used in generalization research together with growing demands for generalization processing to support a myriad of new geospatial services and technologies has led researchers to investigate how open architectures might better support such changing needs. The chapter explains two such requirements: to share generalization techniques among researchers within the field and to present generalization functionality externally to geographic services. This chapter discusses the issue of openness first in relation to the requirements of the generalization community and then in the broader context of open standards, open architectures, and open sources for geographic information.