Data integrity: authenticity

Name:

Date:

Class:

Quick Questions

Shade in the A or B circle for each question.

1. A student finds a spreadsheet of Melbourne rainfall with no author, date or source listed. Is the data's authenticity confirmed?

A No, the source cannot be verified

B Yes, it looks professional so it is authentic

2. Which action best checks the authenticity of a dataset?

A Check that the file has no spelling mistakes

B Trace it back to the original publisher, such as the Bureau of Meteorology

3. A survey file was edited so that several responses were changed to support the researcher's view. What is this an example of?

A Altered data, which is not authentic

B Cleaned data, which is still authentic

4. Data is authentic when it is genuine and really comes from the source it claims.

A False

B True

5. An email attaches a spreadsheet claiming to be from the ABS, but it was sent from an unknown personal address. What should you do?

A Verify it against the ABS website before using it

B Use it because it mentions the ABS

Match the Pairs

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

Left column		Right column
1authenticity		APopularity or wide sharing does not prove data is genuine. The original source must be verified, and the post could be fake or altered.
2Source check: Who published this? Can we contact them?		BCompare the file with the copy on the official ABS website
3Verifying the source: confirming a dataset really comes from the organisation named on it.		CVerifying the source of data to confirm it is authentic.
4Fake or altered data: values changed after collection so they no longer match the original.		DThis confuses authenticity with accuracy or correctness. Authentic data is genuine and from its claimed source, not just error-free.
5Authentic data = data with no spelling or typing errors		EOriginal file: Sales = 450 \| Received file: Sales = 940
6Found on a popular social media post, so the data must be authentic		FData is genuine and really comes from the source it claims to come from.

Definitions

authenticity

Fill in the Blanks

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

IF sourceVerified = ____ THEN ACCEPT data END IF

IF checksumNow __ checksumOriginal THEN ALERT "Data altered" END IF

__ source = "Unknown" THEN REJECT data END IF

authentic = sourceVerified ___ NOT altered OUTPUT authentic

IF modifiedDate _ createdDate THEN SET flagData TO TRUE END IF

Spot the Error

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

Question 1

A claimed = 'ABS'

B actual = get_source(file)

C authentic = False

D if actual != claimed:

E authentic = True

Question 2

A hash_old = 'a1b2c3'

B hash_new = md5(file)

C authentic = True

D if hash_new == hash_old:

E authentic = False

Question 3

A SELECT *

B FROM survey_data

C WHERE source <> 'Official ABS'

D ORDER BY id;

Question 4

A trusted = ['ABS', 'BOM']

B if source not in trusted:

C print('Verified source')

D else:

E print('Check source')

Question 5

A data = load('sales.csv')

B owner = data.source

C if owner = 'unknown':

D print('Not verified')

Answer Key

Data integrity: authenticity

Section A: Quick Questions

A — No, the source cannot be verified

B — Trace it back to the original publisher, such as the Bureau of Meteorology

A — Altered data, which is not authentic

B — True

A — Verify it against the ABS website before using it

Section B: Match the Pairs

authenticity → Data is genuine and really comes from the source it claims to come from.

Source check: Who published this? Can we contact them? → Verifying the source of data to confirm it is authentic.

Verifying the source: confirming a dataset really comes from the organisation named on it. → Compare the file with the copy on the official ABS website

Fake or altered data: values changed after collection so they no longer match the original. → Original file: Sales = 450 | Received file: Sales = 940

Authentic data = data with no spelling or typing errors → This confuses authenticity with accuracy or correctness. Authentic data is genuine and from its claimed source, not just error-free.

Found on a popular social media post, so the data must be authentic → Popularity or wide sharing does not prove data is genuine. The original source must be verified, and the post could be fake or altered.

Section C: Definitions

authenticity — Data is authentic when it is genuine and really comes from the source it claims. Check the source and watch for fake or altered data.

Section D: Fill in the Blanks

IF sourceVerified = TRUE THEN
  ACCEPT data
END IF

IF checksumNow <> checksumOriginal THEN
  ALERT "Data altered"
END IF

IF source = "Unknown" THEN
  REJECT data
END IF

authentic = sourceVerified AND NOT altered
OUTPUT authentic

IF modifiedDate > createdDate THEN
  SET flagData TO TRUE
END IF

Section E: Spot the Error

D — Data is only treated as authentic when the actual source matches the source it claims. The test should be == so authentic becomes True when they match.

D — If the new hash differs from the saved hash, the file has been altered and is no longer authentic. The test should be != so a mismatch sets authentic to False.

C — To keep only data from the verified source, the condition must select rows that equal 'Official ABS'. Using <> returns every row except the verified ones.

B — A source is verified only when it is in the trusted list. Using 'not in' prints 'Verified source' for unknown sources. It should be 'in'.

C — A single = is assignment and causes a syntax error in an if test. Use == to compare the source with 'unknown'.