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1 GIS as enabling technology for an information environment in public administration Monika Heidemann Fraunhofer-Institut für Graphische Datenverarbeitung.

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Presentation on theme: "1 GIS as enabling technology for an information environment in public administration Monika Heidemann Fraunhofer-Institut für Graphische Datenverarbeitung."— Presentation transcript:

1 1 GIS as enabling technology for an information environment in public administration Monika Heidemann Fraunhofer-Institut für Graphische Datenverarbeitung Rundeturmstr. 6 64283 Darmstadt

2 Monika Heidemann 2 Overview  Introduction Situation of Information Technology in the EU Situation of Administration Use of GIS in Administration  Architecture Requirements of the IT-system Architecture Scenario of a soil-protection system Architecture of the soil-protection system Three-tier-architecture Data Management  Example Common GIS  Conclusion

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4 4 Situation of Information Technology in the EU  Goals availability of information and data as a fundamental criterion of competitiveness in the market improved information flow to increase effectiveness frontier crossing communication by the use of information systems  Obstacles standards and rules impeded the availability and exchange of data significant backlog in comparison to the USA

5 Monika Heidemann 5 Situation of Administration  explosion of data stored in administrative databases  huge heterogenous data sets  knowledge is hidden in distributed large data amounts  quality of data differs considerably  existing systems suffer in a lack of user- friendliness and effectiveness  lack in transparency for the citizen  low budgets

6 Monika Heidemann 6 Use of GIS in Administration  between 80 and 85% of all data have spatial reference (e.g. coordinates, addresses)  growing information potential in geographic information systems  GIS no longer limited to a small group of professionals  advantages: redundancy in work and expenses may be reduced optimized decision finding processes spatial analyses of measured data optimized information flow between departments common information source for civil servants and also citizens

7 Monika Heidemann 7 Requirements of the IT-system  easy access to the heterogeneous data and information  user-friendly interfaces  selection, procession, transformation and visualization of data  result evaluation and documentation  combining of different diciplines  exploiration of knowledge about several integrative disciplines  serve to multiple users  fast data retrieval

8 Monika Heidemann 8 Architecture  PC-based client/server technology wide distribution of data and information  server-centric system all process will be carried out on the server side functions and data will be transmitted on demand the system will not be stressed unnecessary  client-centric systems applications perform the processes to the clients not suitable for large amount of data

9 Monika Heidemann 9 Scenario  soil-protection system of one ministry in Germany  different departments are linked Waste Management Offices of Water Supply and Distribution Cadastral and Surveying Offices  Geo Base Data Automated Property Register Automated Property Map  huge amount of structured and unstructured data  quality of applicable data differs considerably  no use of several data stock without previous preparation  plenty of rules, restrictions and standards to be observed

10 Monika Heidemann 10 Architecture of the soil-protection system  combination of GIS and Internet simple and transparent distribution of geo-related data security mechanisms (different ID´s)  simultaneous access to the common data sets  3-tier-architecture client, middleware, server  application server realizes the access to the database and keeps the business logic  not only visual data but also topology, master data etc. is available  transparency and user-friendliness by use of a meta- information-system

11 Monika Heidemann 11 Three-tier-architecture 1. Tier: Data Base Server 2. Tier: Application Server 3. Tier: Internet Client....

12 Monika Heidemann 12 Data Management  working in different data sources  metadata overcome the problem of interpreting the heterogeneous sources  modern software system consists of more or less independent components meet special requirements communicate with other components of the system particular components act autonomously  examples of components geo-coding waste deposits intelligent visualization analysis module

13 Monika Heidemann 13 Data Management II  quality is enhanced by different highly specialized componentes which can easily be replaced  essential to have defined user-interfaces for each component  Interface Definition Language (IDL) user interface specification independence of user interfaces and implementation of functionality  communication between the components is performed by using CORBA

14 Monika Heidemann 14 Data Management III  each component is working on a well-definded data-stock  autonomous administration will lead to redundancy and related consistence problems  there are special components for data administration, the data manager  each information community use their particular data model - the virtual data model  virtual data model access the original data sources via data server interfaces  components must specifiy which virtual data model they should use in order to get reasonable data  automatic integration of data sources into the virtual data model by means of meta-data

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16 Monika Heidemann 16 Example - Common GIS  goal: access and usability of geo-data for everyone from everywhere  visualization techniques in form of maps and statistical graphs  remote access to geo-data  easy analysis of generated maps  specification of data sets and design of visualizations by its own  the system calculates the chosen statistical presentation  guides the user by using special interaction targets

17 Monika Heidemann 17 Example Rationale for offering multiple presentations: Different visualization techniques enable different analysis tasks

18 Monika Heidemann 18 Why? Selection of table data Automatic generation of maps Numeric data Amounts Intelligent structure of data

19 Monika Heidemann 19 Visualisation design Conceptual description of the thematic data Map designer Client Server selected columns Presentation manager map specification Rule base on map design

20 Monika Heidemann 20 Data variables: nominalordinalnumeric is a part of are comparable Combinations of graphical elements: enables comparisons disables comparisons emphasizes inclusion enable estimation of sums and proportions.... Visual variables:

21 Monika Heidemann 21 Pie-chart test of “Intelligence”

22 Monika Heidemann 22 Conclusion  access to geo data even by non-experts  interaction between users via Internet  commercial GIS meet general requirments  special demands by programming  transfer of software and consultancy know-how to member states  focus on new technologies wearable GIS 3D-GIS


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