Distributed Data Management in Internet Map Services

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1 Distributed Data Management in Internet Map Services Experiences from Lounaispaikka Thematic Atlas Antti Vasanen Regional Council of Southwest Finland

2 Lounaispaikka Lounaispaikka is a regional non-profit GI service and network operating in Southwest Finland Established in 1999 as a co-operative network; Internet portal and GI services opened in 2002 Main goals are: to deliver available GI data and cartographic information within Southwest Finland to all interested parties to enhance regional GI related cooperation to develop mechanisms to reduce unnecessary duplication in the production of GI data to bring forward regional viewpoints to national SDI building Currently supported by 7 public background organisations from Southwest Finland Trilingual Internet portal available at

3 Lounaispaikka Thematic Atlas The most important part of Lounaispaikka GI services are the map services, of which Thematic atlas is the primary and technically the most advanced Its main principle is to offer various thematic maps to a large audience in as usable manner as possible Includes various thematic map layers protected areas, transportation network, population density, land use the data content of the service is in many cases tangent to the core GI datasets identified in Inspire annexes Development work has been carried out with support of the Life Environment project ENViFACiLiTATE Current version in Finnish; development version available also in Swedish and in English

4 Lounaispaikka Thematic Atlas

5 Lounaispaikka Thematic Atlas

6 Thematic Atlas and SDI According to the Finnish national geographic information strategy, a national map service should include: 1) an easy access map viewer 2) an interface offering core datasets to other applications Lounaispaikka Thematic Atlas acts in many ways as a regional test bed for the national map service the service model of Lounaispaikka has been well represented in preliminary work to create national SDI components In Finland, regional GI portals and their services have started to receive increased recognition as an important part of the national SDI Regional GI services not only act as sub-national components of national services, but also bring diversity to the services defined in national and European level SDI

7 Service Architecture of the Thematic Atlas Traditionally Internet map services have included all the needed data on the same server as the map service operates In addition to centralised services, Thematic Atlas utilises distributed methods in data management Distributed data management refers to systems where a portion of the data is stored on two or more computers

8 Service Architecture of the Thematic Atlas Most of the Thematic atlas data is still on an internal map server 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 Thematic Atlas Standardised WMS interface enables the map application to import GI data directly from the data provider in image format in Finland, WMS interface has been adopted as the main mechanism for creating the national map service in Thematic Atlas, current WMS layers include topographic maps, soil maps, meteorological data and biodiversity data (altogether ~15 layers) in the future, most of the data will come from national WMS services

10 Service Architecture of the Thematic Atlas Distributed database connections are currently used only with the Ornithological Society of Turku to obtain registered bird observation data Database connections are more widely used as the distributed data management method in the research-driven map services of Lounaispaikka

11 Service Architecture of the Thematic Atlas Metadata is currently obtained to Thematic Atlas from 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 Lessons learnt from distributed data management Data availability increases notable 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 Thematic Atlas, for example, obtains species information from a Canadian WMS interface, which combines hundreds of data sources world wide from Global Biodiversity Information Facility (GBIF)

13 Lessons learnt from distributed data management Maintenance decreases 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

14 Lessons learnt from distributed data management 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 internet maps using distributed data management may accelerate the map service considerably

15 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

16 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 like 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

17 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 a malfunction in the data provider s server may cause mere absence of the required data, or, at the worst, a total breakdown of the client map service

18 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 initialize and use large quantity of data sources well supported in both commercial and open source applications 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 provider s own datasets

19 Thank you! Additional information:

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