Testing INSPIRE data specifications Anders Östman [email protected]@hig.se Imad...
Transcript of Testing INSPIRE data specifications Anders Östman [email protected]@hig.se Imad...
Testing INSPIRE data Testing INSPIRE data specificationsspecifications
Anders Östman [email protected] Abugessaisa [email protected]
Xin He [email protected]
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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