“The Danish suggestion” for an approach to reduce complexity and still be compliant with the Directive (and IR DS annex 3) 3rd Meeting of the MIG-sub-group on the "fitness for purpose action 2016.1" (Reflection Group) Agency for Data Supply and Efficiency 16 November 2018

Danish agency for Data Supply and Efficiency - Danish INSPIRE coordination body, INSPIRE NCP, MIG (T) etc. We like to promote our architecture, knowledge and SDI-infrastructure as a range of common-public components which other authorities can be part of and thereby be compliant with the INSPIRE directive and integrates with Danish eGov. SDFE G Data WareHouse P Production Data-owner P Production D Digital Map Supply WMS WMTS WFS GML Agency for Data Supply and Efficiency 16 November 2018

Aim and assumptions The aim with this analyse is to generate a GML-file compliant to INSPIRE legal obligations as expressed by the IR DS annex 3. Our assumptions are that feature types and attributes marked “voidable” can be left out of the GML-file (and thereby not included in the file with a VoidReasonValue such as “Unknown” etc). We also allow us self to change the multiplicity in the INSPIRE data model – for instance from 1..* to exact 1 due to the fact that multiplicity is not expressed in the IR DS. Finally we flatten the inheritances and the data types. We recommend flat structures for GML instead of the current complexity in many of INSPIREs data models. Flat structure can be without further configuration be read and interpret by the present user applications. Agency for Data Supply and Efficiency 16 November 2018

The source data: Prospecting for mining at the sea – from the The Danish Agency for Water and Nature Management Agency for Data Supply and Efficiency 16 November 2018

The source data is by the Danish Agency for Water and Nature Management identified as in scope of INSPIRE AM Agency for Data Supply and Efficiency 16 November 2018

Data model for annex 3 theme Area Management… AM data model “unfolded” – this is an example of complexity in IR annex 3… AM data model as it looks like in TG unfolded 16 November 2018

The unfolded data model is undergoing 4 steps aiming to reduce complexity We add a profile “Raastof_profil” as a tagged value to all elements in the unfolded model which are mandatory according to IR DS or to which we have corresponding source data. After adding the profile we run a self- developed script in EA which creates a new application schema containing only the element which has the profile. In the second step we flatten inheritance using ShapeChange. Agency for Data Supply and Efficiency 16 November 2018

The unfolded data model is undergoing 4 steps aiming to reduce complexity Here we flatten the data types into the attribute. In the showed example the attribute “name” haves the data type GeograhicalName which consists of the data type SpellingOfName…. – this kind of complexity is difficult to implement physical in a database and to configure in a web services (WFS) and to read by an application like GIS. And this is why we are in favour of flatten. Agency for Data Supply and Efficiency 16 November 2018

The unfolded data model is undergoing 4 steps aiming to reduce complexity In the last step we reduce the multiplicity by replacing * to the exact number we know we have in the source data. After going through these 4 steps we create – using ShapeChange – a GML application schema. This schema is the foundation for creating the GML file. Now we have to populate the tables in our data base – we create views (sql) where we map the source data (feature types and attributes) to the corresponding elements in our “by the 4-steps” created INSPIRE-AM model. Agency for Data Supply and Efficiency 16 November 2018

Example of the creation of an INSPIRE view Data is now in the data base and the creation of the GML file is carried out in FME. Agency for Data Supply and Efficiency 16 November 2018

Example of a feature member in the INSPIRE AM GML-file (raastofferInspire.gml) In the next slide this GML file is opened directly in QGIS without any kind of translation/converting etc. The result is a flat (no-complex) GML-file with the mandatory (and some voidable) elements from the IR DS AM. Agency for Data Supply and Efficiency 16 November 2018

Agency for Data Supply and Efficiency 16 November 2018

So… the big question is… Are the generated data (GML-file) compliant with the directive – as INSPIRE basic? And is the generated data still interoperable in a pan European context? Action 2016.1 Fitness for purpose – Analysis Outcome of discussions and suggested way forward Agency for Data Supply and Efficiency 16 November 2018

Agency for Data Supply and Efficiency 16 November 2018