Data integrity: timeliness

Name:

Date:

Class:

Quick Questions

Shade in the A or B circle for each question.

1. A council plans a new bus route using census figures from 15 years ago. Which describes the data?

A It is timely because census data is always accurate for any year.

B It may lack timeliness because it may no longer reflect who lives in the area.

2. Which detail would you check first to judge the timeliness of a dataset?

A The number of columns in the table

B The collection date or the date of last update

3. True or false: Data that is timely for one purpose is always timely for every other purpose.

A False

B True

4. A student needs today's train delays. Which source is more timely?

A A live feed updated every minute

B A report last updated six months ago

5. A dataset has no collection date and no date of last update. What is the problem?

A You cannot judge whether it is timely

B It is automatically timely

Match the Pairs

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

Left column		Right column
1Collection date: 2016		AShows when the data was gathered, so you can judge if it is still up to date enough for the purpose
2Last updated: 3 March 2025		BIF dataAge <= maxAgeAllowed THEN timely
3Timeliness means data is up to date enough for its purpose		CTimeliness is judged by the collection date or date of last update, not by file size.
4Old census figures may be too out of date for planning a new school		DAccuracy and timeliness are different. Data can be accurate when collected but too old to be timely for current use.
5Census from 2006 is accurate, so it is timely for planning 2025 services.		EShows when the dataset was last revised, so you can judge if it is current enough to use
6Timeliness is judged by the file size of the dataset.		FcensusYear = 2011, purposeYear = 2025, gap = 14 years

Definitions

timeliness

Fill in the Blanks

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

SELECT * FROM census WHERE ______________ >= '2022-01-01';

SELECT name, lastUpdated FROM datasets WHERE lastUpdated __ '2024-01-01';

SELECT name, lastUpdated FROM datasets ORDER BY lastUpdated ____;

age ← currentYear - collectionYear IF age _ 5 THEN OUTPUT "Data may be out of date"

SELECT ___(lastUpdated) FROM datasets;

Spot the Error

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

Question 1

A dataYear ← '2016'

B nowYear ← 2025

C age ← nowYear - dataYear

D IF age > 5 THEN

E OUTPUT 'Out of date'

Question 2

A SELECT name updated

B FROM datasets

C WHERE updated >= '2024-01-01'

Question 3

A censusYear ← 2011

B needYear ← 2024

C IF censusYear > needYear THEN

D OUTPUT 'May be out of date'

Question 4

A SELECT title, collected

B FROM reports

C WHERE collected > 2023-01-01

Question 5

A lastUpdate ← 2019

B gap ← lastUpdate - 2025

C IF gap > 3 THEN

D OUTPUT 'Find newer data'

Answer Key

Data integrity: timeliness

Section A: Quick Questions

B — It may lack timeliness because it may no longer reflect who lives in the area.

B — The collection date or the date of last update

A — False

A — A live feed updated every minute

A — You cannot judge whether it is timely

Section B: Match the Pairs

Collection date: 2016 → Shows when the data was gathered, so you can judge if it is still up to date enough for the purpose

Last updated: 3 March 2025 → Shows when the dataset was last revised, so you can judge if it is current enough to use

Timeliness means data is up to date enough for its purpose → IF dataAge <= maxAgeAllowed THEN timely

Old census figures may be too out of date for planning a new school → censusYear = 2011, purposeYear = 2025, gap = 14 years

Census from 2006 is accurate, so it is timely for planning 2025 services. → Accuracy and timeliness are different. Data can be accurate when collected but too old to be timely for current use.

Timeliness is judged by the file size of the dataset. → Timeliness is judged by the collection date or date of last update, not by file size.

Section C: Definitions

timeliness — Data is timely when it is up to date enough for its purpose, judged by its collection date or date of last update. Old census figures may be too out of date.

Section D: Fill in the Blanks

SELECT * FROM census
WHERE collectionDate >= '2022-01-01';

SELECT name, lastUpdated FROM datasets
WHERE lastUpdated >= '2024-01-01';

SELECT name, lastUpdated FROM datasets
ORDER BY lastUpdated DESC;

age ← currentYear - collectionYear
IF age > 5 THEN
  OUTPUT "Data may be out of date"

SELECT MAX(lastUpdated) FROM datasets;

Section E: Spot the Error

A — The collection year is quoted, so it becomes text and cannot be subtracted from nowYear to find the age of the data. It should be dataYear ← 2016.

A — The comma between the column names is missing. It should be SELECT name, updated so the date of last update is shown as its own column.

C — The comparison is the wrong way round. Census figures are possibly out of date when the census year is EARLIER than the year needed, so it should be <.

C — Dates are stored as text in YYYY-MM-DD form, so the date must be in quotes: '2023-01-01'. Without quotes it is treated as a subtraction.

B — The subtraction is reversed and gives a negative gap. The age of the data is the current year minus the date of last update: 2025 - lastUpdate.