Assessing data against the six integrity characteristics

Name:

Date:

Class:

Quick Questions

Shade in the A or B circle for each question.

1. A school database lists a Year 10 student's age as 212. Which characteristic has the data failed?

A Reasonableness, because 212 is not a sensible age

B Timeliness, because the age is out of date

2. A manager receives a sales spreadsheet from an email address that only looks like the supplier's. Which characteristic is most in doubt?

A Authenticity, because the source can't be verified as genuine

B Relevance, because the file is a spreadsheet

3. A café sets this month's budget using supplier prices from 2019. Which characteristic has failed?

A Timeliness, because the data is out of date for the decision

B Authenticity, because the prices came from a supplier

4. A gym analyses members' favourite pizza toppings to decide which new fitness classes to run. Which characteristic has failed?

A Correctness, because pizza toppings are spelt wrongly

B Relevance, because the data doesn't relate to the decision

5. The postcode field in a customer record contains the word 'Melbourne'. Which characteristic has failed?

A Timeliness, because the customer may have moved

B Correctness, because the value is not in the valid postcode form

Match the Pairs

Draw a line connecting each item on the left to its match on the right.

Left column		Right column
1Student age recorded as 214		APassing one characteristic does not prove integrity. Each of the six must be tested one at a time using evidence from the scenario
2Customer address last updated in 2015		BFails timeliness: the data is out of date, so it should not be used for current decisions
3Testing relevance: does the data suit the purpose? A scenario using it for the wrong purpose fails this test		CFails reasonableness: the value is not believable for a student, so the data should not be trusted
4Testing authenticity: is the data from a genuine, trusted source? A scenario with an unverified source fails this test		DUsing sales data from a bakery to plan stock for a hardware store
5A student says: The spelling matches the form, so the data is accurate. It passes all six characteristics		EFailing any one characteristic means the data has low integrity and should not be trusted
6An analyst finds data that fails timeliness and says: It fails one test, but we can still trust it		FSurvey results emailed from an unknown sender with no way to verify them

Definitions

data integrity

Fill in the Blanks

Complete each line of code by filling in the missing parts.

IF age = 250 THEN failed ← "______________"

IF lastUpdated < "2020-01-01" THEN failed ← "__________"

IF sourceVerified = FALSE THEN failed ← "____________"

IF heightRecorded <> heightMeasured THEN failed ← "________"

failedCount ← 1 IF failedCount > 0 THEN trust ← _____

Spot the Error

Shade in the letter of the line that contains an error.

Question 1

A record: Age = 250

B test: timeliness

C result: FAIL

D action: do not trust data

Question 2

A record: stock count = 12

B shelf count = 9

C test: accuracy -> PASS

D action: do not trust data

Question 3

A record: price list dated 2019

B today: 2025

C test: authenticity -> FAIL

D action: do not trust data

Question 4

A task: plan canteen menu

B data: student lunch orders

C test: relevance -> FAIL

D action: do not trust data

Question 5

A email: bank asks for password

B sender: bank-secure.xyz

C real domain: bank.com.au

D test: authenticity -> PASS

E action: do not trust data

Answer Key

Assessing data against the six integrity characteristics

Section A: Quick Questions

A — Reasonableness, because 212 is not a sensible age

A — Authenticity, because the source can't be verified as genuine

A — Timeliness, because the data is out of date for the decision

B — Relevance, because the data doesn't relate to the decision

B — Correctness, because the value is not in the valid postcode form

Section B: Match the Pairs

Student age recorded as 214 → Fails reasonableness: the value is not believable for a student, so the data should not be trusted

Customer address last updated in 2015 → Fails timeliness: the data is out of date, so it should not be used for current decisions

Testing relevance: does the data suit the purpose? A scenario using it for the wrong purpose fails this test → Using sales data from a bakery to plan stock for a hardware store

Testing authenticity: is the data from a genuine, trusted source? A scenario with an unverified source fails this test → Survey results emailed from an unknown sender with no way to verify them

A student says: The spelling matches the form, so the data is accurate. It passes all six characteristics → Passing one characteristic does not prove integrity. Each of the six must be tested one at a time using evidence from the scenario

An analyst finds data that fails timeliness and says: It fails one test, but we can still trust it → Failing any one characteristic means the data has low integrity and should not be trusted

Section C: Definitions

data integrity — How trustworthy data is. Test it against six characteristics, one at a time: accuracy, authenticity, correctness, reasonableness, relevance and timeliness. Failing any one means it can't be trusted.

Section D: Fill in the Blanks

IF age = 250 THEN
  failed ← "reasonableness"

IF lastUpdated < "2020-01-01" THEN
  failed ← "timeliness"

IF sourceVerified = FALSE THEN
  failed ← "authenticity"

IF heightRecorded <> heightMeasured THEN
  failed ← "accuracy"

failedCount ← 1
IF failedCount > 0 THEN
  trust ← FALSE

Section E: Spot the Error

B — An age of 250 is not a believable value for a person, so it fails the reasonableness test. Line 2 should be 'test: reasonableness'. Timeliness is about how up to date data is.

C — The record says 12 but the real shelf count is 9, so the data does not match the real world. It fails accuracy. Line 3 should say FAIL.

C — A price list from 2019 used in 2025 is out of date. This is a timeliness failure, not an authenticity failure. Line 3 should be 'test: timeliness -> FAIL'.

B — Shoe sizes have nothing to do with planning a menu, so the data fails relevance. Lunch orders would be relevant, so line 2 would not match the FAIL result. Line 2 should be 'data: student shoe sizes'.

D — The sender domain does not match the real bank's domain, so the email is not from the genuine source. It fails authenticity. Line 4 should say FAIL.