Integrating geo web services for a user driven exploratory analysis

Moncrieff, Simon; Turdukulov, U.; Gulland, Elizabeth-Kate

doi:10.1016/j.isprsjprs.2016.01.015

Cited by 5 publications

(5 citation statements)

References 6 publications

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“…These are important considerations when generating maps from big geospatial data and/or when there is a need to create large volumes of maps. For example, MapDesign could be implemented as web services that access distributed big geospatial data sources on the web, similar to the architecture proposed by Moncrieff (2016) for visual analytics; or by orchestrating a number of web services, an architecture proposed by Rautenbach et al (2013).…”

Section: Discussionmentioning

confidence: 99%

“…Researchers have approached this challenge in various ways (Krimbacher 2014;Moncrieff et al 2016;Rautenbach et al 2013). For example, Rautenbach et al (2013) present ThematicWS, a web service that produces choropleth and proportional symbol maps by orchestrating distributed web services: a central controlling process executes web services in a specified order and manner to produce the maps; it also handles any interactions between the web services.…”

Section: Related Workmentioning

confidence: 99%

“…Similarly, Krimbacher (2014) designed and developed a service-orientated architecture for thematic map production. To deal with rapidly increasing volumes of data, Moncrieff et al (2016) developed a platform for the exploration and analysis of large dynamic geospatial datasets. Mapping functionality was encapsulated in standard web services.…”

Section: Related Workmentioning

confidence: 99%

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A Design Pattern Approach to Cartography with Big Geospatial Data

Coetzee

Rautenbach

2017

The Cartographic Journal

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A design pattern approach for conceptualizing the cartographic design process is presented. A design pattern presents a solution to a problem by describing solutions for the commonalities in problems to be solved. The commonalities of the cartographic design process are identified and MapDesign is described, a design pattern for generating a set of maps from big geospatial data. The MapDesign pattern allows increased map throughput through automation and distributed processing, which frees up time for cartographers and geographic information scientists to make sense of big geospatial data and to select and refine map designs. The description of the MapDesign pattern can aid software developers in understanding how to build tools that allow automation and distributed processing in parts of the map design process for visualising big geospatial data. Conversely, the visual nature of design patterns can assist cartographers with understanding how software components interact to produce maps.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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A Design Pattern Approach to Cartography with Big Geospatial Data

Coetzee

Rautenbach

2017

The Cartographic Journal

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“…This then needs to influence how geospatial web services will provide and integrate the necessary underlying data and information. Moncrieff et al (2016) describes a framework that extends the WPS approach to enable ongoing exploratory and user driven spatial analysis across multiple attributes, datasets and spatial/temporal scales. This visual analytic environment is illustrated by a health related case study that integrates the geoprocessing of health records and demographic data.…”

Section: Geo-analysismentioning

confidence: 99%

Cloud/web mapping and geoprocessing services – Intelligently linking geoinformation

Veenendaal

Brovelli

2016

ISPRS Journal of Photogrammetry and Remote Sensing

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We live in a world that is alive with information and geographies. "Everything happens somewhere" (Tosta, 2001). This reality is being exposed in the digital earth technologies providing a multidimensional, multi-temporal and multi-resolution model of the planet, based on the needs of diverse actors: from scientists to decision makers, communities and citizens (Brovelli et al, 2015). We are building up a geospatial information infrastructure updated in real time thanks to mobile, positioning and sensor observations. Users can navigate, not only through space but also through time, to access historical data and future predictions based on social and/or environmental models. But how do we find the information about certain geographic locations or localities when it is scattered in the cloud and across the web of data behind a diversity of databases, web services and hyperlinked pages? We need to be able to link geoinformation together in order to integrate it, make sense of it, and use it appropriately for managing the world and making decisions.

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“…By wrapping existing or new geoprocessing functionality in a WPS and chaining the tasks, the limitations of the standards can be overcome and more sophisticated and diverse thematic map products can be generated (e.g. Cerba and Cepicky, 2012;Rautenbach et al, 2012;Zeng et al, 2013;Krimbacher, 2014;Moncrieff et al, 2016). For an automated, parallel processing of distributed big geospatial data, the software design pattern approach can be used to produce a series of thematic map designs which employ only those cartographic representation methods which are appropriate depending on the input data characteristics (Coetzee and Rautenbach, 2017).…”

Section: Introductionmentioning

confidence: 99%

Training students in Python programming skills and WPS wrapping for geoprocessing tasks by using examples of less commonly applied thematic mapping methods

Stern

Schaab

2021

AGILE GIScience Ser.

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Abstract. Python programming and the application of web services technology can be considered important skills for geomatics students when looking for employment later. A course on Web Processing Services (WPS) as part of the International Geomatics master programme at Karlsruhe University of Applied Sciences takes this into consideration while using the opportunity of making students aware of less-known thematic mapping methods. Students are introduced to automating a complex geoprocessing task and finally wrapping it into a WPS. It is achieved by following the phases of first conceptualizing the single steps before then using ArcGIS ModelBuilder and Python scripts in combination to build the processing chain. The alternate band map method serves as example in the hands-on exercise. Later students are asked to automate the generation of the geometries for the map face and/or map legend supporting other thematic mapping methods like the square density map or the absolute value raster map. The paper discusses the teaching approach and experiences made so far. Conceptualizing the automatization of a given complex geoprocessing problem proved to be the most challenging part for the students.

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Integrating geo web services for a user driven exploratory analysis

Cited by 5 publications

References 6 publications

A Design Pattern Approach to Cartography with Big Geospatial Data

A Design Pattern Approach to Cartography with Big Geospatial Data

Cloud/web mapping and geoprocessing services – Intelligently linking geoinformation

Training students in Python programming skills and WPS wrapping for geoprocessing tasks by using examples of less commonly applied thematic mapping methods

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