ISESS 2005 Tools and Techniques Guidelines for good practises in GIS Andrea 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- Andrea Schukraft, Roman Lenz Page 2

GIS data quality – a problem in planning processes? - Example 1 - Andrea Schukraft, Roman Lenz Page 3 The research project WAVES (TUM) in Brasil Beispiel mit freundlicher Genehmigung von Planungsbüro Voerkelius, Landshut

GIS data quality – a problem in planning processes? - Example 2 - Andrea Schukraft, Roman Lenz Page 4 Landscape plan on a municipality level Beispiel mit freundlicher Genehmigung von Planungsbüro Voerkelius, Landshut Are the wet soils and potential habitats mapped correctly? The farmer said: no! (Scale...)

GIS data quality – a problem in planning processes? - Example 3 - Andrea Schukraft, Roman Lenz Page 5 Data capture (digitising) from analogous basic data Beispiel mit freundlicher Genehmigung von Planungsbüro Voerkelius, Landshut Different location errors of a waste water tube... again the context matters! (absolute vs. relative position)

GIS data quality – a problem in planning processes? - Example 4 - Andrea Schukraft, Roman Lenz Page 6 Quality of the geometries Multiparts

What really is GIS data quality? - Reality and maps - Andrea Schukraft, Roman Lenz Page 7 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

What really is GIS data quality? - Reality and maps - Andrea Schukraft, Roman Lenz Page 8 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!!!

What really is GIS data quality? - Reasons for deviations/differences from reality - Andrea Schukraft, Roman Lenz Page 9 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...

What really is GIS data quality? - Categories of Spatial data quality - Andrea Schukraft, Roman Lenz Page 10 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

What really is GIS data quality? - A classification matrix of data quality - Andrea Schukraft, Roman Lenz Page 11 Space - where? Time - when? Theme - what? Accuracy123 Precision456 Complet- ness 789 Consistency101112

What really is GIS data quality? - Meta-data - Andrea Schukraft – EDV Im Grünen Bereich - Seite 12 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

What really is GIS data quality? - Meta-data - Andrea Schukraft, Roman Lenz Page 13 Minimum-Info Source of data Title Date of publication Purpose of data capture Actuality e.g mapping date Key words Map-Scale Short summary

What really is GIS data quality? - Meta-data - Andrea Schukraft, Roman Lenz Page 14 -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 Andrea Schukraft, Roman Lenz Page 15 How do we solve the problems in practise/reality?

Quick check of spatial precision - Derive precision from origin - Precision of the resulting data set Original dataAnalysis

Sample Implementation - Visualize precision -

Steps for improvements - Example 4 - Andrea Schukraft, Roman Lenz Page 18 Quality of the geometries

Steps for improvements - Example 5 - Andrea Schukraft, Roman Lenz Page 19 Modelling flooding

Guidelines for good practices in GIS Andrea Schukraft, Roman Lenz Page 20 Handbook on GIS data quality (management)

Guidelines for good practices in GIS - Handbook - Andrea Schukraft, Roman Lenz Page 21

Guidelines for good practices in GIS - Contents - Andrea Schukraft, Roman Lenz Page 22

- Example 1 - Andrea Schukraft, Roman Lenz Page 23 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 - Andrea Schukraft, Roman Lenz Page 24 Example 1: Quality of geometries Is it really necessary, to define and demand such trivial criteria? Yes !!!

- Example 2 - Andrea Schukraft, Roman Lenz Page 25 Example 2: Meta-data How did these results occur?

- Example 2 - Andrea Schukraft, Roman Lenz Page 26 Example 2: Meta-data

- Example 3 - Andrea Schukraft, Roman Lenz Page 27 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 little points will be digitised, and hence the data set will not be precise enough

- Example 3 - Andrea Schukraft, Roman Lenz Page 28 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 2005 Tools and Techniques Guidelines for good practises in GIS: Andrea Schukraft, Roman Lenz Thanks for listening!