ISESS 2005 Tools and Techniques Guidelines for good practises in GIS Andrea Schukraft, Roman Lenz

ISESS 2005ISESS 2005Tools and TechniquesTools and Techniques

Guidelines for good practises in GISGuidelines for good practises in GIS

Andrea Schukraft, Roman LenzAndrea Schukraft, Roman Lenz

Part 1: GIS data quality – a problem in planning processes?

Part 2: What really is GIS data quality?

Part 3: Steps for improvements

Part 4: The handbook for GIS data quality (management)

- Outline-- Outline-

Andrea Schukraft, Roman LenzAndrea Schukraft, Roman Lenz Page Page 22

GIS data quality – a problem in planning

processes? - Example 1 -- Example 1 -


The research project WAVES (TUM) in Brasil

Beispiel mit freundlicher Genehmigung von Planungsbüro Voerkelius, LandshutBeispiel mit freundlicher Genehmigung von Planungsbüro Voerkelius, Landshut




Landscape plan on a municipality level


Are the wet soilsand potential habitatsmapped correctly?The farmer said: no!(Scale...)




Data capture (digitising) from analogous basic data


Different locationerrors of a wastewater tube...again the contextmatters!(absolute vs. relativeposition)




Quality of the geometries

Multiparts

What really is GIS data quality?What really is GIS data quality?

- Reality and maps -- Reality and maps -


The earth

as globe with people, land use, ... in a permanent change

The map as

representation of the earth

as map sheet representing only partial aspects as a flash light representation


- Reality and maps -- Reality and maps -


Quality is (after DIN) defined as

„the completeness of attributes of a specific unit (product, service) according to its suitability, to fullfill fixed and presupposed needs"

(DIN ISO 8402, 1992). There are no bad or good data!

There are only data, which are suitable for a specific

purpose!!!


- Reasons for deviations/differences from reality -- Reasons for deviations/differences from reality -


Soft transitions or fuzzy borders in nature distinct lines in maps

cartographic treatment

age of data

method of data capture

conversion into a more suitable data format

...


- Categories of Spatial data quality -- Categories of Spatial data quality -


Completeness

Quality in Spatial Data

= lack of errors of omissions in a database

Consistency

= the absence of apparent contradictions in a database

Accuracy (and actuality)

= discrepancy between the encoded and actual value of a particular attribute

Precision (or resolution)

= degree of detail that can be displayed in space, time or theme


- A classification matrix of data quality -- A classification matrix of data quality -


Space - where?

Time - when?

Theme - what?

Accuracy 1 2 3

Precision 4 5 6

Complet-ness

7 8 9

Consistency 10 11 12


- Meta-data -- Meta-data -

Andrea Schukraft – EDV Im Grünen Bereich - [email protected] Schukraft – EDV Im Grünen Bereich - [email protected] Seite Seite 1212

Meta-data are data about data

For example:

1. Description of Geo-data

2. Information about data quality

3. Information about data format (shape, tif, raster, ...)

4. Information about the spatial reference system (e. g. Gauß-Krüger)

5. Additional information (e. g. description of table contents)

6. Availability and sources (public or restricted, price, ...)

7. Contact address




Minimum-InfoMinimum-Info

Source of data

Title

Date of publication

Purpose of data capture

Actualitye.g mapping date

Key words

Map-Scale

Short summary




- Geo-data investigations

- Description of own data, e.g. in the office etc.

- Re-use of data e.g. after a longer period

- After transmission of data, meta-data are an important information for the receiver

- Institutions, who distribute/sell data, describe those in a catalog. The descriptions are meta-data

- Notice: “science” or “theoretical” standards (like FGDC or ISO 19115) vs. reality…

Why do we need Meta-data?

Steps for improvements


How do we solve the problems in practise/reality?

Quick check of spatial precisionQuick check of spatial precision

- Derive precision from origin -- Derive precision from origin -

Precision ofthe resulting

data set

Original data Analysis

Sample ImplementationSample Implementation

- Visualize precision -- Visualize precision -


- Example 4 -- Example 4 -


Quality of the geometries




Modelling flooding

Guidelines for good practices in GISGuidelines for good practices in GIS


Handbook on GIS data quality (management)


- Handbook -Handbook -



- Contents -Contents -




Example 1: Quality of geometries

Quality criteria for geometries will be fixed, e.g.

- for comparison of competing offers e.g. in public calls

- for own data captures

- for data transfer between several project partners



Example 1: Quality of geometries

Is it really necessary, to define and demand such

trivial criteria?

Yes !!!



Example 2: Meta-data

How did these results

occur?



Example 2: Meta-data



Example 3: Pre-definition of digitising map-scale

Why are pre-definitions necessary?- in a large scale, too many points will be digitised, and the data set gets too big- in a small scale, too littlepoints will be digitised, andhence the data set will notbe precise enough



Example 3: Digitising Map-scale

When is it meaningful to pre-define

the map-scale for digitising?

- if different people are digitising

- if data are captured over a longer period

- if a third party is capturing and digitising the data

ISESS 2005ISESS 2005Tools and TechniquesTools and Techniques

Guidelines for good Guidelines for good practises in GIS:practises in GIS:

www.rundertischgis.dewww.rundertischgis.de

Andrea Schukraft, Roman LenzAndrea Schukraft, Roman Lenz

Thanks for listening!

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ISESS 2005 Tools and Techniques Guidelines for good practises in GIS Andrea Schukraft, Roman Lenz