Lessons learnt on distributed viewing services Lounaispaikka Map Service and ICZM Map Viewer of the ENVIFACILITATE - PowerPoint PPT Presentation

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Lessons learnt on distributed viewing services Lounaispaikka Map Service and ICZM Map Viewer of the ENVIFACILITATE

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Title: Lessons learnt on distributed viewing services Lounaispaikka Map Service and ICZM Map Viewer of the ENVIFACILITATE

1
Lessons learnt on distributed viewing services
Lounaispaikka Map Service and ICZM Map Viewer of
the ENVIFACILITATE

Antti Vasanen
Regional Council of Southwest Finland

2
Lessons learnt on distributed viewing services

In this presentation I will concentrate on the
characteristics of distributed data management in
internet map services
I will use the Lounaispaikka Map Service and the
ICZM Map Viewer as examples, both of which have
been developed as a part of the ENVIFACILITATE
project
Overview of the presentation
Introduction to the map services used as examples
Description of the service architectures of these
services
Lesson learnt on utilising distributed viewing
services

3
Lounaispaikka Map Service

The Lounaispaikka Map Service is a central
component in the GI services of Lounaispaikka,
the regional GI service and network operating in
Southwest Finland
In the recently renewed map service, all the
previously separate map services of Lounaispaikka
have been merged together
The trilingual viewing service includes a wide
variety of different thematic maps
The easy-to-use service interface takes into
account the needs of both GI professionals and
everyday users with no prior GI knowledge

4
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5
ICZM Map Viewer

ICZM (Integrated Coastal Zone Management) is an
European initiative to integrate different
policies which have an effect on the EUs coastal
regions
The ICZM Map Viewer aims to provide an
easy-to-use interface to relevant spatial data
sets required
to understand the environmental conditions and
land use pressures on coastal regions at an
international scale
to understand and join together the (conflicting)
needs of coastal land use and management
to support the elaboration of coastal strategies
in Finland, Estonia and Latvia
The Map Viewer is available in English and it
covers the coastal areas of Finland, Estonia and
Latvia

6
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7
Distributed Map Services

Traditionally internet map services have included
all the needed data on the same server as the map
service operates
Unlike centralised services, distributed map
services contain a portion of the data on two or
more servers
Both the Lounaispaikka Map Service and the ICZM
Map Viewer utilise distributed methods in their
data management

8
Service Architecture of the Lounaispaikka Map
Service

Most of the data situates on the map server of
Lounaispaikka
This is due to the lack of operators serving data
in a distributed manner in Finland
Thus, the centralised service architecture is
currently dominant in most internet map services

9
Service Architecture of the Lounaispaikka Map
Service

The standardised WMS interface enables the map
application to import GI data directly from the
data provider
The Lounaispaikka Map Service includes WMS layers
from e.g. NLS, FMI and GTK
In Finland, WMS has been adopted as the main
mechanism for creating the national map service,
and thus, most of the data will come from
national WMS services in the future

10
Service Architecture of the Lounaispaikka Map
Service

Distributed database connections are currently
used only to obtain registered bird observation
data from the database of the BirdLife Finland
Database connections are also used in the Marine
Environment service, but the databases are
currently located in the database server of the
University of Turku

11
Service Architecture of the Lounaispaikka Map
Service

Metadata is currently obtained to the
Lounaispaikka Map Service from the Lounaispaikka
metadata catalogue
In the future, when the national infrastructure
becomes more developed, metadata information can
hopefully be acquired directly from a common
national metadata catalogue

12
Service Architecture of the ICZM Map Viewer

The ICZM Map Viewer uses the distributed data
management methods offered by the ESRI ArcIMS
Data covering all three countries are located on
the ArcMap image service running on the
ENVIFACILITATE map server

13
Service Architecture of the ICZM Map Viewer

National datasets are situated on separate
servers maintained by a ENVIFACILITATE project
partner in each country
Due to the lack of software resources, the
Latvian ArcIMS service is temporary situated on
the same server as the Finnish service.

14
Lessons learnt from distributed data management

Data availability increases notably when level of
distribution rises
In addition to basic datasets, distributed data
management enables the adoption of huge domestic
and international data sources
Lately, especially the number of WMS data sources
has increased rapidly
Lounaispaikka Map Service, for example, obtains
species information from a Canadian WMS
interface, which combines hundreds of data
sources world wide from Global Biodiversity
Information Facility (GBIF)

15
Lessons learnt from distributed data management

Maintenance efforts decrease when level of
distribution rises
Maintaining map services and updating its data
content requires most efforts after the actual
development phase
When using distributed data management, related
efforts may decrease considerably
However, if distributed data sources are numerous
and potentially unstable, the overall usability
of the map service may decline in spite of the
decreased maintenance needs

16
Lessons learnt from distributed data management

The need of server capacity is inversely
proportional to the level of distribution
In many cases, map services based on vector GI
data need substantial server capacity to produce
raster format maps readable on the internet
Using distributed data management may accelerate
the map service considerably

17
Lessons learnt from distributed data management

Extensive possibilities for GIS functionality
often requires that the data is situated on an
internal map server
If large scale GIS functionality is needed,
simple image based distributed data management
systems, such as WMS, will not be suitable
However, vector based data transfer methods, such
as WFS (Web Feature Service) may solve this
problem as they become more widely available

18
Lessons learnt from distributed data management

Control over the cartographic visualisation of
the map content may decline notably when
distributed methods are used
The provider of the interface usually defines the
visual expression of the distributed data
Affects most image based systems such as WMS
However, when using coordinate point based data
transfer methods, such as distributed databases,
the interface provider has basically no effect
on the cartographic visualisation of the data

19
Lessons learnt from distributed data management

Map service functionality may become more or less
unstable if many distributed data sources are
used simultaneously
Depends on the used data management system
In WMS services, a malfunction in the data
providers server causes mere absence of the
required data
However, e.g. in distributed ArcIMS services, the
whole map services will collapse in the case of
the malfunctioning in one of its components

20
Conclusions

Distributed data management is a real opportunity
when creating a map service depending mainly on
other data provides datasets
Using standardised data transfer methods, such as
WMS, is recommended for many reasons
easy to initialise and use
large quantity of data sources
well supported in both commercial and open source
applications
In our experience, more stable than licensed
products
However, distributed data management may not be
desirable if for example
advanced GIS tools are needed
the service provider has precise requirements
regarding visualisation
the map service is entirely based on the service
providers own datasets