testing inspire data specifications anders Östman anders.ostman@hig.seanders.ostman@hig.se imad...

Testing INSPIRE data Testing INSPIRE data specificationsspecifications

Anders Östman Anders.Ostman@hig.seImad Abugessaisa imad@fpx.se

Xin He Xin.He@fpx.se

Implementation rulesMetadata (ready)Information models (data specifications)◦According to themes listed in three annexes

Network services◦Search services◦Viewing services◦Download services◦ Transformation services◦ Invokation services

Why testing? INSPIRE demands that the data specifications shall be balanced

with respect to costs and benefits

Transformation tests: Can the member states deliver data according

to the specifications? At what cost?

Applikation tests: Are the data specifications useful? Which benefits

do they generate?

We have mainly worked with transformation tests related to the data

specifications for Annex I themes.

Five themes have been tested

Adresses

Geographical Names

Cadastral Parcels

Hydrography

Transportation Networks

Method in briefNLS database NLS schema INSPIRE

schema

NLS shapefiles

Transformation rules

Source data consistency

report

Source GML files

Target GML files

Schema transformation

report

Schema matching &

mapping report

Data extraction Schema matching and mapping

Shape to GML conversion

Source consistency

test

Schema transformation

Schema translationA schema specify the structure of a datasetSchema matching – to find corresponding elements

in the source schema and target schema◦ Automation may be based on ontologies and semantic

matchingSchema mapping – to find rules for the

transformation◦ Simple: Datum -> text◦ Difficult: Point -> polygon, different classification systems

Schema translation – to make the translation

Language

NamedPlace

Ortnamn

XKOORD, YKOORD

DETALJTYP

SPRÅK

URSPRUNG

ORTNAMN

ID-NR

typeLocal

Identifier

sourceOfName

Geometry

Text

INSP

IRE

Feature &

Attributes types

Feasdla;ldk;alk

LM

V F

eature & A

ttributes typesF

easdla;ldk;alk

relatedSpatialObject

levelOfDetail

referencePointMeaning

endLifespanVersion

Missing attributes

Conversion Rules

Simple mappings

Code lists -> Text string

2 numbers -> GML Point

Integer -> Text string

Datum -> Datum

Complicated mappings

Reclassification, Ortnamn -> NamedPlaceType

{BEBTX, BEBTÄTTX, KULTURTX, KYRKATX, NATTX, SANKTX VATTDELTX, VATTDRTX,

VATTTX} -> {Others}

{} -> {Road, BasicRoadLink, RoadNode, RailwayLine}

{ANLTX} -> {Airport, Heliport, Others}

{TERRTX} -> {MountainRange, Archipelago}

{FÖRSAMLTX, KOMMUNTX, SOCKENTX, TRAKTTX} -> {Administrative Unit}

{GLACIÄRTX} -> {GlacierSnowfield}

Matching of feature typesINSPIRE Schema INSPIRE  # Matched Pct 

Geographical Names 1 1 100%

Addresses 6 6 100%

Cadastral Parcels 3 3 100%

Road Transport Network 6 2 33%

Railway Transport Network 8 2 25%

Water Transport Network 5 2 40%

Physical Waters 10 7 70%

Hydro Facilities 4 1 25%

Hydro Points Of Interests 4 2 50%

Hydro Man Made Objects 8 4 50%

Air Transport Networks  

Hydrography Networks  

Hydrography Management & Reporting  

In Total 55 30 55%

Matching of mandatory attributesINSPIRE Schema  INSPIRE Transformable Pct 

Geographical Names 3 2 67%

Addresses 7 6 86%

Cadastral Parcels 11 9 82%

Road Transport Network 3 2 67%

Railway Transport Network 4 4 100%

Water Transport Network 4 4 100%

Physical Waters 12 5 42%

Hydro Facilities 1 1 100%

Hydro Points Of Interests 3 2 67%

Hydro Man Made Objects 4 4 100%

In Total 52 39 75%

Summary of matching and mapping

The Swedish Land Survey is able to deliver data to 11 of 14 schemas (79 %)

For these 11 schemas, The Swedish Land Survey can deliver data to 55 % of the feature types (30 / 55)

For these 30 feature types, the Swedish Land Survey can deliver 75 % of the mandatory elements (30 / 55)

The corresponding value for optional elements is 30 % (102 / 342)

Some expensive problemsCadastralParcel.Geometry is to be a simple

polygon. About 7,5 % of the Swedish parcels are represented by a point or line.

NamedPlace.Type, see previous slideRoadLink.FormOfWay: About 80 % are uncertainly

classified RoadLink.RoadWidth: Classes shall be converted

to width in meter

MetadataTheme Completeness At other

place

Information

missing

Addresses 28% 64% 8%

Cadastral Parcels 75% 21% 4%

Hydrography 36% 64% 0%

Geographical Names 54% 14% 32%

Transportation network 75% 25% 0%

Summary The GeoTest project is a part of the Swedish geodata strategy

Transformation tests of data specifications in INSPIRE Annex I are

performed

◦ The responsibility of each agency needs to be reviewed

◦ The cooperation among the agencies needs to be developed

further

◦ Some transformations will be costly

Current metadata do not comply to any standard

Solutions for GML Schema Transformation

Objective To evaluate existing tools for schema transformation

Restricted to tools performing the operations in the XML/GML

domain

Tested Tools Safe FME 2008 Desktop

Altova MapForce 2009

Snowflake Go-publisher 1.4

FME 2008 Desktop

Altova MapForce 2009

Snowflake Go Publisher 1.4

Overview of tools

Types of transformation (Liljergren et.al 2006)

Semantic transformations

◦ Source and target domains may be the same.

◦ Example: Swedish -> English.

Domain transformations

◦ Different domains. May also include semantic transformations

Coordinate transformation

◦ Geodetic reference systems, linear reference systems, …

targetsourcef :

Transformations being studied

Strings and codelists (semantic + domain)

Geometric transformations (domain)

Levels of measurement (domain)

Strings and codelists

Geometric transformations

Levels of measurements

What is the best solution? FME can perform almost all transformations in the matrices.

However, it lacks the ability to handle XML hierarchical

structure.

Both MapForce and GoPublisher can do this job.

However, GoPublisher is not designed for schema

transformation and lacks of developed functions and data

interfaces.

Luckily, MapForce is on the other side.

Conclusions No single tool can fulfill all requirements of the transformation

between GML schemas;

The best solution at present is to use FME and MapForce together.

However, the efficiency of handling XML/GML files are not so high at

this stage.

E.g. GML files that only smaller than 50 MB can be handle by

MapForce at our computers.

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