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DataCove Statistical Viewer

Katharina Schleidt and Tomáš Kliment

(Submission #184)


At DataCove, we have developed the concept of Data Ghosting; accessing data made available under Open Government Data (OGD) initiatives, and reproviding it in accordance with INSPIRE data specifications. In addition to providing valuable insights to the process of INSPIRE data provision, Data Ghosting allows us to explore the potential of utilizing INSPIRE compliant data prior to such services being made available by the original data holders. As part of the DataCove data Ghosting process, we explored the statistical data available from Eurostat, falling under the INSPIRE Themes Statistical Units (SU) and Population Distribution (PD). These Themes were of special interest as there is a strong focus on information pertaining to spatial units, in contrast to many of the more spatially focused INSPIRE Themes. Once the WFS services for the INSPIRE Themes SU and PD were operational we designed a simple online viewer to test the usability of the services as specified by INSPIRE. This work was initiated at DanubeHack2 in Bratislava. During the implementation process, various difficulties were encountered, requiring the implementation of workarounds. The problems encountered with GeoServer fall into the following categories: * Problems with WMS with gml:MultiSurface geometry type * Problems with requesting multiple complex features * Problems with stored queries on Complex features and Views Many of the problems encountered with GeoServer in the process of implementing the services required for the DataCove Statistical Viewer will have similar impacts on services for other INSPIRE Themes. Additional difficulties were encountered pertaining to both the INSPIRE specifications as well as the WFS service interface. The INSPIRE data model for PD has been strongly influenced by statistical data models; the tabular nature of these models, paired with a lack of filtering functionality, makes it quite difficult for applications to process the data provided. The following filtering functionalities were implemented: * Simple features providing distinct values available for specific elements; * Stored queries to access data based on non-spatial attributes; * A filter middleware service that accesses the INSPIRE PD features and filters these down to user requirements before provision. Similar functionality will be required by most applications utilizing data from INSPIRE services; thus, a standardization of such INSPIRE helpers would be most valuable. In conclusion, while data provided via INSPIRE compliant services will be of great value in creating new applications and products, for widespread usability the known deficits must first be mastered.


Topic Area:  [2.3] Technologies and tools to support implementing, using and assessing the technical implementation of INSPIRE
Abstract Type:  Oral Presentation

Additional Fields

Comments:   Statistical Units; Population Distribution; implementation issues; Stored Queries

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