SDI Convergence - Global Spatial Data Infrastructure Association

”Member States may limit public access to spatial data sets and services [...] where
such access would adversely affect [...] the protection of the environment to which such
information relates, such as the location of rare species.”
We argue here that map-layers represented in static ways powered by static legal- and
policy constraints do exactly that. They do not support conflict resolution and negotiation,
but rather suggest more inflexibility and legal rigidity. INSPIRE based static map
layers may be counterproductive to conflict resolution because of the tendency to be
too general or too specific with no dynamic adjustment possibilities based on flexible
regulative parameters. The interesting difference between a screen showing map layers
already there and those that ‘turn up’ while moving a qualified cursor (like the one
seeking space for open sailing areas) is the affordance of opportunity finding in contrast
with the annotation of an area that is ‘locked up’. The provinces call this functionality
a ‘seeking area’. They have created the unusual legal term ‘seeking area’ to obtain
legal degrees of freedom in development plans that do not occur with fixed parameterisation.
Feedback on the tests with the Flevoland regional development plan prove that questions
like: return all contours on the map that fulfils the legal constraints ‘X’ and ‘Y’, but
not ‘Z’ are answerable. How does one provide such type of opportunity finding for the
user in a meaningful representation that allows for more flexibility? We have argued
that INSPIRE Maps showing Natura2000 areas or sites should enable the functionality
of ‘seeking area’. Simcity game developers who created manoeuvrability using a cursor
and ‘tiles’ with fixed business rules may have developed the answer already. This was
in 1985 when Simcity was still called ‘Micropolis’ (Wright, 2004a).
6. CONFLICT ANNOTATION ENGINE FOR LEGAL ATLAS III
Simcity-like functionality (see Wright, 2004b) resembles the required flexibility or ‘seeking
area’. It is mostly based on Semantic Web Technology. The knowledge models
about the legal constraints and the domain knowledge of the working scenarios are all
described with Resource Description Framework/ Web Ontology Language (RDF/
OWL). We chose RDF/OWL to infer and reason with these models. To publish this information
as a service we use the OpenRDF Sesame server. This server has an
SPARQL (SPARQL Protocol and RDF Query Language)-endpoint, which is an access
point to which SPARQL queries can be sent. The SPARQL-endpoint is accessible
through the web. The RDF that is stored within the OpenRDF Sesame server is processed
with OWLIM. OWLIM is a high-performance semantic repository. It is packaged
as a Storage and Inference Layer (SAIL) for the Sesame RDF database. It reasons
about the RDF data and propagates this by means of rule-entailment. The SPARQLendpoint
is used to fill the Legal Atlas III with information. The Legal Atlas III is as an
interface for the OpenRDF Sesame server, and the SPARQL-endpoint is the interface
between them.
The SPARQL queries are based on the schemata of the RDF/OWL models (van de
Ven et al., 2007). This means that they are independent on the content. This ensures
that different content is annotated with the RDF/OWL models to ensure that the
SPARQL queries are able to retrieve the content. The return is a gigantic list of all the
concepts that can be used for annotation. Such a huge list might not be convenient in a
user interface. Therefore it is better to replace this list with a practical list. Pruning this
list down to a domain is one way to limit the amount of concepts. The following example
shows the SPARQL query for a specific domain, namely the IMRO2006 (Informatiemodel
Ruimtelijke Ordening, Dutch information model for spatial planning) SKOS
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