1. Gerhard Joos AGIS – GIS lab University of the Bundeswehr Munich Gerhard.Joos@unibw-muenchen.de http://agis.bauv.unibw-muenchen.de Establishing a Quality Control System based on ISO 19114 and ISO 19113 Standards in Action: Workshop at the 13 th meeting of ISO/TC 211, Adelaide, Australia

2. Gerhard Joos Arbeitsgemeinschaft GIS Importance of Quality Gain confidence in geodata Reduce users‘ complaints Get customer’s satisfaction Minimize consecutive costs caused by decisions or actions based on erroneous data

3. Gerhard Joos Arbeitsgemeinschaft GIS Two German examples based on AGIS-projects Bundeswehr Geographic Office Incorporating external data into the central topographic database Stadtwerke München (SW/M) – Utility supply company Munich: gas / water / electricity / heat Capturing utility features by contractors Updating utility and cadastral features

4. Gerhard Joos Arbeitsgemeinschaft GIS Evaluating and Reporting Quality Evaluation Results [ISO 19114] Dataset as specified by the scope Identify a data quality measure Select and apply a data quality evaluation method Determine the data quality result Identify an applicable data quality element, data quality subelement, and data quality scope Conformance quality level Determine conformance Product specification or user requirements Report data quality result (quantitative) Report data quality result (pass / fail) work item 19131 ISO 19113 ISO 19114 5 step process on quality evaluation 1 2 3 4 5

5. Gerhard Joos Arbeitsgemeinschaft GIS Evaluate data captured in an external process Bundeswehr Geographic officeSW/M – Utility supply company Munich DatasetTopographic dataUtility features in connection with cadastral data ScopeGermany: all topographic features – test performed on defined areas Homogeneous lots with different geographic extent and with different feature classes Data quality elements Logical consistencyCompleteness Logical consistency Positional accuracy Thematic accuracy MethodAutomated checking – rules from the product specification Full inspection Automated checking – application specific rules Sampling Conformance quality level –Different conformance quality levels for different feature classes ReportingError listPass / fail Quality Management

6. Gerhard Joos Arbeitsgemeinschaft GIS Experiences with applying ISO 19113 and ISO 19114 The concept behind those standards works In some respect too general E.g. no normative quality measures given Standard on product specification was missing (wi31) System independent description of conceptual rules within the application schema were not available UML constraints (OCL) could be the solution This means that the application schemata have to be available in UML – this is not yet the case It is difficult to determine a conformance quality level

7. Gerhard Joos Arbeitsgemeinschaft GIS Method for determination conformance quality levels Assumptions The more errors are in a dataset, the higher the likelihood of applying erroneous data for decisions or actions Each false decision or action leads to consecutive costs costs on finding the right answer costs due to damages caused by false information e.g. by hitting a pipeline which was documented at a different location hidden costs by loosing confidence of the user community hidden costs due to image loss by the customer A dataset is never completely free of errors The effort to gain a certain quality level costs time and money

8. Gerhard Joos Arbeitsgemeinschaft GIS Conformance quality level The amount of consecutive costs in a certain application from erroneous data can be estimated This amount is better invested into Quality Management of the data With these parameters the conformance quality level can be calculated

9. Gerhard Joos AGIS – GIS lab University of the Bundeswehr Munich Gerhard.Joos@unibw-muenchen.de http://agis.bauv.unibw-muenchen.de Thank you!