An active crawler for discovering geospatial Web services and their distribution pattern – A case study of OGC Web Map Service

Li, Wenwen; Yang, Chaowei; Yang, Chen

doi:10.1080/13658810903514172

Cited by 62 publications

(47 citation statements)

References 16 publications

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“…[3,16]. The GetFeatureInfo operation requests metadata for the selected features [16]. Because metadata can help users find the service layers they need and determine how best to use them [36], in general, discovering WMSs means finding the URLs of the GetCapabilities operation.…”

Section: Related Workmentioning

confidence: 99%

“…A WMS provides three operations: GetCapabilities, GetMap, and GetFeatureInfo to support requests for metadata, static maps and feature information about the corresponding georeferenced maps, respectively [1,16]. The GetCapabilities operation is intended to request service metadata, such as service abstract, reference coordinate system, the format, etc.…”

Section: Related Workmentioning

confidence: 99%

“…The GetMap operation enables users to obtain static maps from multiple servers by submitting parameters that include layer names, bounding boxes, format, styles, etc. [3,16]. The GetFeatureInfo operation requests metadata for the selected features [16].…”

Section: Related Workmentioning

confidence: 99%

“…The GetCapabilities operation is intended to request service metadata, such as service abstract, reference coordinate system, the format, etc. [16]. The GetMap operation enables users to obtain static maps from multiple servers by submitting parameters that include layer names, bounding boxes, format, styles, etc.…”

Section: Related Workmentioning

confidence: 99%

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Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

Hou

Chen

2016

IJGI

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Automatic discovery of isolated land cover web map services (LCWMSs) can potentially help in sharing land cover data. Currently, various search engine-based and crawler-based approaches have been developed for finding services dispersed throughout the surface web. In fact, with the prevalence of geospatial web applications, a considerable number of LCWMSs are hidden in JavaScript code, which belongs to the deep web. However, discovering LCWMSs from JavaScript code remains an open challenge. This paper aims to solve this challenge by proposing a focused deep web crawler for finding more LCWMSs from deep web JavaScript code and the surface web. First, the names of a group of JavaScript links are abstracted as initial judgements. Through name matching, these judgements are utilized to judge whether or not the fetched webpages contain predefined JavaScript links that may prompt JavaScript code to invoke WMSs. Secondly, some JavaScript invocation functions and URL formats for WMS are summarized as JavaScript invocation rules from prior knowledge of how WMSs are employed and coded in JavaScript. These invocation rules are used to identify the JavaScript code for extracting candidate WMSs through rule matching. The above two operations are incorporated into a traditional focused crawling strategy situated between the tasks of fetching webpages and parsing webpages. Thirdly, LCWMSs are selected by matching services with a set of land cover keywords. Moreover, a search engine for LCWMSs is implemented that uses the focused deep web crawler to retrieve and integrate the LCWMSs it discovers. In the first experiment, eight online geospatial web applications serve as seed URLs (Uniform Resource Locators) and crawling scopes; the proposed crawler addresses only the JavaScript code in these eight applications. All 32 available WMSs hidden in JavaScript code were found using the proposed crawler, while not one WMS was discovered through the focused crawler-based approach. This result shows that the proposed crawler has the ability to discover WMSs hidden in JavaScript code. The second experiment uses 4842 seed URLs updated daily. The crawler found a total of 17,874 available WMSs, of which 11,901 were LCWMSs. Our approach discovered a greater number of services than those found using previous approaches. It indicates that the proposed crawler has a large advantage in discovering LCWMSs from the surface web and from JavaScript code. Furthermore, a simple case study demonstrates that the designed LCWMS search engine represents an important step towards realizing land cover information integration for global mapping and monitoring purposes.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

Hou

Chen

2016

IJGI

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“…Second, the available data are poorly documented, making it difficult if not infeasible for researchers to understand their lineage and content and to make sound judgment about their applicability for a specific problem. Third, the data are typically produced using local standards with respect to format, metadata structure, etc., resulting in a high degree of heterogeneity and, thus, hampering the goal of achieving geospatial interoperability [7]. Fourth, failures in open collaboration lead to duplicate efforts in the development of software to analyze and process geospatial data.…”

Section: Introductionmentioning

confidence: 99%

A Geospatial Cyberinfrastructure for Urban Economic Analysis and Spatial Decision-Making

Goodchild

et al. 2013

IJGI

Self Cite

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Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making processes. In this paper, we report on our efforts to design and develop a geospatial cyberinfrastructure (GCI) for urban economic analysis and simulation. This GCI provides an operational graphic user interface, built upon a service-oriented architecture to allow (1) widespread sharing and seamless integration of distributed geospatial data; (2) an effective way to address the uncertainty and positional errors encountered in fusing data from diverse sources; (3) the decomposition of complex planning questions into atomic spatial analysis tasks and the generation of a web service chain to tackle such complex problems; and (4) capturing and representing provenance of geospatial data to trace its flow in the modeling task. The Greater Los Angeles Region serves as the test bed. We expect this work to contribute to effective spatial policy analysis and decision-making through the adoption of advanced GCI and to broaden the application coverage of GCI to include urban economic simulations.

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Communicating Information for Development: A Cartographic Approach

Akinyemi

Sester

Balogun

2012

E J Info Sys Dev Countries

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In developing poverty reduction strategies, poverty and welfare maps are made based on estimated values for use in decision making. Targeting public resources is better achieved with information derived from these maps. This use of poverty and welfare maps in shaping policy practically illustrates information use for development. On poverty maps, for example, poverty estimates are depicted as graphic symbols through which information is transferred to the map user. This paper investigates how effective these maps are as graphic communication media. A cartographic approach is adopted to examine the symbolization of poverty and welfare maps with the aim of enhancing their design. Eight criteria were developed and used to infer map communication effectiveness in the context of poverty mapping. These criteria are interpreted as map defects and major ones are overlapping class value, problems with symbol type, choice of color scheme and class differentiation which are all related to map symbolization. Map symbolization challenges within the poverty mapping context are related to the need to visually perceive shared spatial patterns between two related variables, highlight units with high poverty levels as well as emphasize high and low points in a poverty or welfare data. This paper illustrates how to address these by applying basic cartographic principles. These principles are generic to all kinds of maps, but it is their applicability to poverty and welfare maps that is paper's focus.

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An active crawler for discovering geospatial Web services and their distribution pattern – A case study of OGC Web Map Service

Cited by 62 publications

References 16 publications

Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

A Geospatial Cyberinfrastructure for Urban Economic Analysis and Spatial Decision-Making

Communicating Information for Development: A Cartographic Approach

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