Data Quality Management

CS 128/ES 228 - Lecture 14a 1

Data Quality Management

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Geospatial errors can

cause real-life problems!


One management strategy …


Murphy’s Law

Ignoring data quality issues usually doesn’t work very well


Some geospatial goofs


This one’s worse…

Mars Climate Orbiter (MCO) was lost on 23 Sep 1999 when it failed to enter an orbit around Mars, instead crashing into the planet, destroying the $125 million craft, part of a $328 million mission

The root cause of the failure was a computer program that was supposed to provide its output in newton seconds (N·s) but instead provided pound-force seconds (lbf·s).

http://lamar.colostate.edu/~hillger/unit-mixups.html#mco

http://www.boeing.com/companyoffices/gallery/images/space/d2_mars_climate_orbiter_01.htm


And these are really bad!Just a 'map error'? The China Daily website carries a cartoon of the damaged US plane at Hainan Island's airbase and asks sarcastically if Sunday's collision "might be due to another map error“ - a reference to the US bombing of the Chinese embassy in Belgrade in 1999. "Last time it's due to a map error, and this time another map error? What about the next?” http://news.bbc.co.uk/1/hi/world/monitoring/media_reports/1260185.stm

It might be due to another map error

China Daily


What is error?

“Error is the physical difference between the real world and the GIS facsimile”

-Heywood, Cornelius, & Carver, p. 178

Errors are impossible to avoid, but can be managed


A Data Management Model

Data acquisition

Data representation

& analysis

Data outputs


Data acquisition errors

Scientists use the term “error” for two very different concepts:

natural variability actual mistakes


Take a sidewalk …

What’s its width? 1.77, 1.82, 1.69 … meters

a. “Error” (natural variability):mean width = 1.76 m, range 1.69 - 1.82

b. “Error” (actual mistake): mean = 1.67 ft


Accuracy vs. Precision

Figure 10.1, An Introduction to Geographic Information Systems by

Heywood, Cornelius, and Carver


Random error vs. Bias


Where does lack of precision come from?

Natural variability

Poor input assumptions

Imprecise equipment

Sloppy measurement

Accumulated error


Random error is often “normal”

mean

Standard deviation


95% of observations ±2 s.d.

mean

Mean + 2 s.d. Mean + 2 s.d.


Means have smaller variability than single measurements

S. E. (mean) = standard deviation √n

If n = 4 √n = ?


Where does lack of accuracy come from?

Dubious source data Incompatible source data

Data collected at different times through different methods, possibly in different formats

Bias


How can we fix it? Benchmarks

ex. National Geodetic Survey maintains a database of survey “monuments” at

http://www.ngs.noaa.gov/ cgi-bin/datasheet.prl

Otherwise – just measure variability

http://upload.wikimedia.org/wikipedia/commons/thumb/6/66/USCGS-E134.jpg/617px-USCGS-

E134.jpg


Data representation errors Transference error

Data storage errors

Analysis errors


Where does transference error come from?

Typos, etc. Less likely with automated data

collection and transformation Can be prevented through diligence

and software “sanity” checks

Format conversion Many inter-format conversions cause

loss/corruption of data/information


Something got lost in the translation

“geographic information systems is an interesting course”

“ 지리적인 정보 시스템은 재미있는 과정 이다 ”

“The geography information system is the process which is fun”

Thanks to http://babelfish.altavista.com/babelfish/tr


Raster Vector conversions

Aliasing is an intrinsic problem of GIS’s


Digitization errors


Topology errors

Figure 10.5, An Introduction to Geographic Information Systems by

Heywood, Cornelius, and Carver


Data storage/retrieval errors

Hardware failure

Hardware Limitations


What is a hardware limitation? Numbers in a

computer are stored in a finite number of bits.

Using too few bits can cause round-off error.

Box 9.2, Principles of Geographic Information Systems by Burrough and McDonnell


Where do errors of data rot come from?

Link rot Not FoundThe requested URL /cs/dlevine/ was not found on this

server.Apache/1.3.27 Server at www.xxx.edu Port 80

Poor “style” E.g. “Employees may appeal to Sr. Carney” as

opposed to “Employees may appeal to the President of the University”


Where do errors of analysis come from?

How long do you have? …

Mistaken queries

Analyzing layers with different datums or coordinate systems

Comparing attributes with incompatible units


More errors of analysis … Inappropriate resolution

Combining rasters/vectors with different resolutions

Using exact/abrupt surface fits when approx./gradual is appropriate (or vice versa)


Data output errors Maps

Reports


Junket at taxpayers’ expense?Did a politician misuse federal funds to visit Alaska on the way to official business in Japan?

Muekrcke. Map Use, 2nd ed. p. 395


No - Intentional map error*

*More like lying with maps!

Muekrcke. Map Use, 2nd ed. p. 395


Should maps be as accurate as possible?

Map simplification Features are omitted Area features become

lines or points

Exaggeration Features’ apparent

size is “increased” (e.g. hydrants)

Features’ separation is increased on the map for visibility

Must Mapquest be accurate?


Reporting significance of findings Hypothesis testing

What does the term “significant” mean to scientists?


Are two means really different?These two normal distributions have a very large overlap. The

means of the two populations are not significantly different, because the overlap is > 5% of the area under the curves. t would be very small.

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What about these two means?

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These means are also significantly different - why?

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How do we actually test for statistical differences?

Student’s t-test

t = difference in means measure of variability


Three Commandments of Data Reporting

Thou Shalt Not …I. Report insignificant digits

(or omit significant trailing zeros)

II. Report means without also reporting sample sizes and variability

III. Report results as “significant” (or even worth talking about) without doing the appropriate statistical tests.


How do we minimize (NOT avoid) error?

-- “Mad Eye” Moody Defense Against The Dark Arts Instructor Hogwarts School of Witchcraft and Wizardry

“CONSTANT VIGILANCE”

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Data Quality Management

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